INFORMATION SOCIETY TECHNOLOGIES (IST) Accompanying Measure – Key Action II Contract Number: IST-2000-31104 SOCIO-ECONOMIC ANALYSIS AND MACRO-MODELLING OF ADAPTING TO INFORMATION TECHNOLOGY IN EUROPE Deliverable 1 Assessment of IST trends, impacts on growth and first generation scenarios Prepared by: ISIS Report Version: Final Version Date of Submission: 15 January 2004 Contract Start Date: 1st January 2002 Duration: 24 months Project co-ordinator: Cambridge Econometrics Partners: Cambridge Econometrics (UK), Econcept (Switzerland), ISIS (Italy), BIBA (Germany), SINTEF (Norway), RAND Europe (Netherlands), SFSO (Switzerland), FGM-AMOR (Austria)
Transcript
INFORMATION SOCIETY TECHNOLOGIES (IST) Accompanying Measure – Key Action II Contract Number: IST-2000-31104
SOCIO-ECONOMIC ANALYSIS AND MACRO-MODELLING
OF ADAPTING TO INFORMATION TECHNOLOGY IN EUROPE
Deliverable 1
Assessment of IST trends, impacts on growth and first generation scenarios
Prepared by: ISIS Report Version: Final Version Date of Submission: 15 January 2004 Contract Start Date: 1st January 2002 Duration: 24 months Project co-ordinator: Cambridge Econometrics Partners: Cambridge Econometrics (UK), Econcept (Switzerland), ISIS (Italy), BIBA (Germany), SINTEF (Norway), RAND Europe (Netherlands), SFSO (Switzerland), FGM-AMOR (Austria)
Table of Contents
Foreword: the SEAMATE project ................................................................................... i
0. Executive Summary.................................................................................................... ii
1.1. Scope of IST scenarios ....................................................................................................6
1.2. An overall picture of SEAMATE appraisal of IT prospects, business and social impacts .....................................................................................................................................8
1.3. Establishing IST drivers of growth.............................................................................10
1.4. IST indicators ................................................................................................................17 1.4.1. Scope of indicators of adapting to Information Technology....................... 17 1.4.2. Available sources of data............................................................................. 18 1.4.3. Broad list of IST indicators ......................................................................... 25 1.4.4. Data and measurement problems................................................................. 27
2. Setting the stage: the ICT sector .............................................................................. 29
2.2.5. - Cellular telephones..................................................................................... 44 2.2.6. - UMTS......................................................................................................... 45 2.2.7 - TV access to Internet................................................................................... 47 2.2.8 - Wireless Internet - WiFi.............................................................................. 47 2.2.9 – Software and IT services ............................................................................ 48 2.2.10 – World Wide Web and Internet content..................................................... 50 2.2.11 - ITS Intelligent Traffic Systems, traffic control and navigators ............... 57 2.2.12. Health online ............................................................................................. 59 2.2.13. – Assessment of risks ................................................................................. 61
2.2.13.1 - Systemic operational risks........................................................................................... 61 2.2.13.2. - Risks of Untimely Exploiting Available Resources and Occasions ........................... 62 2.2.13.3 - Internet Topology as a Protection from Cascading Failures........................................ 62
2.2.14 – ICT policy outlook ................................................................................... 64 2.2.14.1 – General tendencies...................................................................................................... 64 2.2.14.2 – Long-term technology vision: enhancing the Ambient Intelligence Space concept ... 65 2.2.14.3 – Enhancing cultural competence as a pre-requisite to knowledge production and society.......................................................................................................................................... 66 2.2.14.4 - Measures and Strategies to implement the Ambient Intelligence Space ..................... 67 2.2.14.5 – Threats and risks ......................................................................................................... 68
2.2.15 – A preliminary screening of IST data and trends data: first conclusions... 69
3. Measuring impacts on growth of European Union.................................................. 74
3.1. The growth accounting approach .................................................................................74
3.2. Limits of the growth accounting approach ..................................................................76
3.3. Comparison of GDP trends ...........................................................................................79
3.4 Contribution of ICT to growth ......................................................................................81 3.4.1 ICT Employment ........................................................................................... 82 3.4.2 ICT price trends ............................................................................................. 83 3.4.3 ICT investment trends .................................................................................. 88 3.4.3 The overall efficiency of labour and capital .................................................. 90
3.5 Correlation and regression analysis .............................................................................94 3.5.1. Capital deepening contribution to economic growth.................................... 97 3.5.2. Total Factor Productivity (TFP) contribution to economic growth............. 99
3.5.2.1. The drivers of ICT contribution to economic growth: a comparison......................... 101
3.6. Contribution of Innovation and Learning to Growth..............................................103 3.6.1 Innovation enabling factors: R&D .............................................................. 104 3.6.2 Innovation enabling factors: role of human capital ..................................... 106 3.6.3 Innovation enabling factors: role of entrepreneurship................................. 108 3.6.4 Correlation and regression analysis: contribution of learning to economic performance .......................................................................................................... 109
3.6.4.1 Contribution of individual learning to economic performance...................................... 113 3.6.4.2. Contribution of organisational learning to economic growth .................................... 116 3.6.4.3. Individual and organisational learning: a comparison ............................................... 118
4 – IST first generation scenarios ............................................................................... 120
4.1. Methodology of Scenarios Building - intended as a Preview and an Integration of Modelling Proper ................................................................................................................121
4.1.1. Distinguishability of scenarios .................................................................. 122 4.1.2. Non gratuitousness .................................................................................... 123 4.1.3. Adequate analysis of main scenario feature(s) .......................................... 123 4.1.4. Pedigree - or similarity to well known processes in the past .................... 124
4.2 - Scenario derivation from current trends..................................................................124
4.3 - "Follow the leader" situations ...................................................................................126
4.4 - Impact of exogenous factors......................................................................................126
4.5 - Negative scenario easier to define..............................................................................127
4.6 - The positive and negative EU15 overall vision.........................................................127
4.7 - Outline of a Business-as-usual Scenario to 2010 ......................................................129
4.8 - Outline of a Positive Scenario to 2010.......................................................................130
4.9 - Outline of a Negative Scenario to 2010 .....................................................................133
4.10. Some comparisons.....................................................................................................134
5. The way forward: modelling of adapting to Information Technologies and issues
for further research ..................................................................................................... 136
5.1. Basic approaches to model IT impacts at micro and macro-economic level ........136 5.1.1. Modelling network effects and technology adoption ................................ 136 5.1.2 Input-Output models tracking ICT impacts at the macro-economic level 138
5.2 – Issues for further fundamental research..................................................................141 5.2.1 Evolution of Knowledge Assets - Conceptual Frameworks...................... 141
5.2.1.1. The evolution of information economy according to the Boisot’s perspective. ........... 141 5.2.1.2. Knowledge value and evolution: outline of a conceptual framework.......................... 145
5.2.2. Scale-free Networks ................................................................................. 147 5.2.2.1. Small Worlds ............................................................................................................... 148
5.2.3 Knowledge dynamics and EU socio-economic development .................... 148
Appendix 1 - Correlation and regression analysis ..................................................... 159
ANNEX 1: Screening of data and trends of ICT use and related variables ..................171 Internet users and hosts ........................................................................................ 171 Employment & Revenues from ICT..................................................................... 174 E-commerce.......................................................................................................... 176 E-Business Benchmarking for SME's .................................................................. 178 Mobile commerce ................................................................................................. 179 E-work .................................................................................................................. 181 E-training .............................................................................................................. 183 Literacy, Education, E-learning............................................................................ 183 GDP, employment, productivity, ICT investment and market value ................... 187 Data on innovation from European Commission DG Research “Science, Technology and Innovation Key Figures (2001 and 2003-2004 issues), “European Innovation Scoreboard 2003” and the “OECD Science, Technology and Industry Outlook and Scoreboard 2001” ............................................................................ 189 Acceding and Accession Countries (AAC13) ICT Situation and Impacts........... 191
Annex 2: List of state-of-the-art IST indicators ......................................................... 195
Annex 3: IST research projects related with SEAMATE .......................................... 224
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Foreword: the SEAMATE project The objective of the project SEAMATE – Socio-Economic Analysis and Macro-modelling of
Adapting to information Technologies in Europe - is to analyse the overall economic impact of Information Society Technology (IST) within the context of the European Union (EU) and national policies. This objective is accomplished adopting a structured workflow over a period of two years (2002-2003), as illustrated in the following scheme:
The project is divided in six work-packages (WPs). Research is focused on two systems: the European social system and the European business system. Acting on these systems are technological changes in IST and many other changes in the world (e.g., socio-economic and cultural changes) that are outside the control of EC policymakers. Based on an exploration of these contextual factors, WP1 produces IST outline scenarios representing changes in technology and other external factors. These outline scenarios and the parallel assessment of fundamental prerequisites and drivers of growth are provided as inputs to the subsequent WPs. WP2 and WP3 refine the analysis of the impacts of IST, respectively on the business system and society at large. All together, WP1, WP2 and WP3 will produce their own appraisal of IST impacts and possible strategies of adapting to information technology in Europe, showing key issues, current evidence and relevant research questions to be answered, based on the state of the art knowledge in the fields of technology, economy and society. The microeconomic analysis of WP4 will provide additional insights about the effects of selected technologies on the business system. Based on the above, a set of assumptions on the IST impacts and plausible effects of related macro and sectoral policies was produced and fed into the E3ME model (WP5). This is a macro-economic input-output model apt to simulate structural changes of the national economies for EU 15 countries + Norway and Switzerland. The E3ME model will then be run for several cases (combinations of social and business scenarios). Each case will produce macroeconomic performance indicators. In WP6, the resulting values of the social, business, and macroeconomic performance indicators for the various scenarios and cases are compared to EC policy goals. Implications for policy changes will be identified. Finally, in the process of developing the scenarios and identifying the social, business, and macroeconomic performance indicators, the need for new statistical classifications and data to be collected to track the IST changes and their impacts is identified.
SocialSystem
BusinessSystem
Other Factors
Technologies
MicroAnalysis
E3MEAssumptions
Macroeconomic
Scenarios of
Adapting to IST
Social and BusinessPerformance
Indicators
EC Policy Goals
Compare
Implicationsfor Policy
WP1
WP3
WP2
WP1
WP4
WP5
WP6
ISTAssessmen t
Data Needs
WP1
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0. Executive Summary 1. Introduction The objective of work contained in Deliverable 1 is to provide a systematic overview of the complex dynamics of the digital economy. A conceptual framework has been built by literature review, data collection and analysis, expert assessment of data and trends, scenario building and qualitative substantive debate. A specific aim is to identify and analyse feedback loops that link the performance of EU economies and the dynamic of Information and Communication Technologies (ICT) and related knowledge-based activities. In this context, work firstly carried out concerns data retrieval and evaluation as well as analysis conducive to scenario building. 2. Approach A relevant contribution of WP1 has been the critical analysis of available data. Time series and projections supplied by Eurostat, OECD, DGIST of the EC, EITO and other sources often differ markedly. We compared them and singled out the more consistent and credible. We were, then, able to take a significant step forward compared to available assessment and projections, in that we built up a robust insight into:
• Future developments of ICT proper as conditioned by: - Cultural and economic prerequisites - Main cause-effect relationships in the web of socio-economic impacts
• Digital divide between nations being more relevant than the divide between the digitally literate on one hand and individuals who are old, disabled, living in remote areas or subjected to gender or racial discrimination
• Predictability of continued economic success of nations investing heavily in high level education and dissemination of culture.
The above considerations inspired the decision to consider only 12 indicators grouped in 3 classes: Prerequisites, IST variables and Socio-economic impacts. Prerequisites
1. Investment in R&D as a proportion of GDP 2. Number of researchers as proportion of the total workforce 3. Proportion of population aged 25-64 having upper secondary schooling
IST variables
4. Share of ICT-producing and ICT-using sectors in overall value-added 5. Number of internet users 6. Proportion of companies engaging in purchasing via e-commerce 7. Proportion of companies engaging in sales via e-commerce 8. Share of ICT manufacturing in total manufacturing employment 9. Value of ICT market [measured for EU15 aggregate only]
Socio-economic impacts
10. GDP
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11. GDP per capita 12. Unemployment rate
Seven countries among the EU15 have been considered to be more representative or paradigmatic for the purpose of building IST scenarios: UK, France, Germany, Finland, Ireland, Italy, Portugal. The chosen set of 7 countries accounts for 2/3 of EU15 activity. The countries are divided in three paradigmatic groups: innovators (Finland, Ireland), advanced (UK, France, Germany) and laggards (Italy, Portugal). Scenarios have been outlined to 2010, the year chosen in the e-Europe Action Plan, launched by the 2000 Lisbon European Council, to render Europe the most competitive knowledge based economy and society in the world - in a business-as-usual, a negative and a positive projection. The Northern countries were more successful so far than others in terms of growth of GDP, productivity, employment and recourse to IST. The positive scenario assumes that laggard countries will follow the example of more innovative ones. The negative scenario implies an overall economic slowdown and increasingly strained international relations. 3. Key findings Performance of EU economies, dynamics of IST and related knowledge-based activities are interwoven in multiple feedback loops. Factors involved (boosting productivity) are: investment in R&D and physical capital; improvements in computer power, software, Internet, IST; intellectual property, human capital, workforce skills; role of entrepreneurship and venture capital. Growth opportunities of the new economy are prompted by well-known drivers: IST production and use, science, technology and innovation. In turn developments of IST depend on technological and cultural drivers. Among these: digitisation, increased cost-effectiveness, miniaturisation, standardisation, penetration of IST tools, literacy, education, skills (of experts and of end users). Continued progress of IST depends on penetration of media, ICT products and services. Factors affecting this diffusion involve: increasing of competition, improving the awareness of population and companies and also the roles of the overall European regulatory framework (for tele-communications, infrastructures, networks and services) and of human capital. Prices differentiation existing in European countries has been related to the different pace of liberalisation processes. Early adopter countries, Finland, Sweden and Denmark show lower prices and tariffs. To cope with this complex set of phenomena, SEAMATE WP1 has produced: ü a conceptual framework, mapping the IST issues and classifying the state-of-the-
art IST indicators according to their suitability to study impacts on growth (Chapter 1)
ü a screening of some fundamental data and issues about the ICT sector (Chapter 2); ü an analysis of IST impacts on growth of the EU and other OECD economies
(chapter 3); ü a range of IST first generation scenarios (chapter 4) ü finally, based on the findings of the previous steps, an insight of fundamental
issues for further research aiming to improve the understanding and predictability
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of Information Technology impacts, beyond the insights that SEAMATE can offer with the current limited data and tools of analysis (chapter 5)
According to the conceptual framework of SEAMATE, two main interlinked drivers of growth have been identified: ICT production/use and knowledge based-activities. Based on some IST indicators for a sample of OECD countries, regression models have been carried out in order to assess the key determinants behind these drivers of growth. Concerning the impact of the ICT sector on the overall growth of national economies, as measured by GDP increase, ICT capital deepening and Total Factor Productivity (TFP) growth rates are among the most important indicators which contribute to explain output growth. ICT investments rates and ICT export rates over the period 1996-1999 have been found in turn to be the most significant explanatory variables respectively for ICT capital deepening (correlation coefficient 0.94) and TFP growth rates (correlation coefficient 0.81). Concerning the latter driver of growth, the knowledge-based activities, a strong negative correlation (-0.90) has been found, at 1999, between output growth and educational attainment below secondary education level. IST first generation scenarios include tentative scenarios, mainly speculative, of possible baseline, positive and negative results of the EU economies at the year 2010, when the policy target for Europe to be the most competitive knowledge based economy in the world should be achieved. The scenarios are based on intuitive assumptions about complex causal links tying ICT production, ICT use, workforce skills, R&D and innovation, supply side and demand side enablers of ICT diffusion, innovation prerequisites (e.g educational attainment, entrepreneurship, flows of researchers) and their contribution to GDP growth, productivity and structural change of the economies. Where the review and analysis of EU data has shown that some European countries have been more successful than others in terms of GDP growth as well as in growth of productivity, employment and effective recourse to ICT, one way to forecast a positive scenario was to assume that laggard countries will follow the example of more successful and innovative ones. An important conclusion and vital consideration is the remarkable lag between EU15 countries. This concerns not just ICT penetration or adoption, but the very prerequisites of innovation per se, including investments in R&D and education at all levels. Lacking these, the new tools and networks will hardly impact favourably societal processes and the economy. Then, the conclusion is that energetic policies for higher education, R&D, innovation are critically needed in laggard countries (Spain, Italy, Portugal, Greece). We may even say - based on the SEAMATE WP1 findings - that the decisive policy factor in the feedback loop connecting circularly: GDP growth - investment in R&D - investment in higher education (notably in science and technology) - innovation - production of value added - is in high quality/high level endeavours in education. The Finnish experience is instructive at this regard. The institution of 32 polytechnics in a country with 5 million people and a robust policy of investment in R&D were the drivers of the well known high-tech success and of the strong growth in GDP experienced in the 90s in Finland. This is enhanced by similar policies followed in Denmark and Sweden and by the creation of a techno-scientific network of networks covering Scandinavia. Obviously the Finnish way of creating an osmosis between
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advanced research and economic growth cannot be imitated literally, due to the different organisation of the research activities in different countries. For instance, in Norway advanced research is traditionally concentrated in few large institutions, instead of a multiplicity of polytechnics as in Finland. But the substance of the prescription remains, that is the need of investing in research and ensure that new knowledge skills are promptly exploited in the economic system. In this regard the analysis of the OECD data on education and employment shows that in the majority of EU countries unemployment for the age group 25–29 years (typically including university graduates leaving education to enter on the labour market) is on average lower for high-skilled workers than for unskilled ones - as expected – but with the exception of some countries, notably Italy and Greece, where the unemployment rates of young high-skilled people is higher. This is due to the fact that the industrial system in these countries – e.g. the Italy’s Nord-East industrial districts – are more ready to absorb low educated people even of younger age than educated professionals. The policy prescription discussed above is further supported from the results of the analysis of correlation between growth variables (GDP per capita, labour productivity) and selected drivers of growth – ICT investment and prices, R&D expenditures, patent applications, educational attainment of the population. 4. Recommendations for future fundamental research Understanding the consequences of new knowledge in terms of saving of physical resources, in different socio-economic contexts and devising new productivity measures is indicated in Chapter 5 as an important research task. This direction of research may represent a continuation of the SEAMATE study. This should also incorporate explicitly new approaches based on consideration of scale-free networks. This appears a promising way to improve the modelling of network effects and understand better the dynamic of diffusion of new IT products and services. Different industrial structures and market regimes (e.g. e-commerce oligopolies versus monopolistic competition) should be studied to understand the underlying network dynamics. In some cases the evolution towards oligopolies or a monopoly situation results from the operation of an underlying scale-free network dynamic and the preferential attachment process. Modelling in this way product market development, the success of a node (product) depends from its fitness (value for money) and the number of links already connected to it (the number of existing consumers).
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1. IST: conceptual framework 1.1. Scope of IST scenarios The objective of the project SEAMATE – Socio-Economic Analysis and Macro-modelling of Adapting to information Technologies in Europe - is to analyse the overall economic impact of Information Society Technology (IST) within the context of the European Union (EU) and national policies. IST is changing the structure of economic activity, further increasing the importance of service provision in the generation of wealth in the economy. Therefore, a macro analysis is required for understanding the drivers of structural change and growth of the economies, and devising policies affecting those drivers and their interactions. Key issues to be considered include: ü investment in physical capital, including Information and Communication
Technologies (ICT); ü the impacts of rapid improvements in computer power and connectivity at
decreasing prices; ü software capital accumulation and the Internet; ü use of ICT and their contribution to productivity; ü impacts of intangibles such as R&D and proprietary know-how, intellectual
property, human capital and workforce skills; ü world-class supply networks and brands and the rapid speed with which leading-
edge practices migrate around the world; ü socio-economic factors enabling the use of ICT by households (income, age and
sex, life-style etc.) and firms (size, sector of activity); ü innovation prerequisites such as levels of educational attainment, R&D investment,
migratory patterns of skilled workforce and researchers, role of entrepreneurship and venture capital.
The complexity of the overall SEAMATE task cannot be underestimated. Moreover, a sort of “second order of magnitude” of complexity stems from the fact that while the digital economy is growing faster and the impacts on the overall structure of our societies are becoming more and more pervasive, our economic and business measurement systems are able to track efficiently only traditional tangible goods and, partially, services. A growing share of intangible goods, new services and workforce competence remains unmeasured. In this situation, blind extrapolation of trends or sophisticated modelling of macro-economic impacts can hardly be envisaged as an effective way to produce reliable results, unless some breakthrough improvement of data and model capabilities is introduced. To cope with this complexity, SEAMATE suggests detailed data needs and innovative development and application of macro-economic input-output modelling. Indeed, recent research in U.S. and Europe shows encouraging signs of progress, especially the preliminary econometric work carried out under the auspices of the OECD Growth Project. This has demonstrated a more-or-less robust correlation between intangible
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investment, GDP and productivity growth and some other important correlation (e.g between growth and levels of educational attainment), notwithstanding the limits of data available. A recent OECD work has shown that existing statistical measures are often insufficient for analysing the linkages and dynamics of the new economy and its many dimensions. However, the same work contributed to increase the awareness that the growth opportunities of the new economy can only be seized through a comprehensive strategy based on a policy mix that tackles several growth drivers at the time (OECD, 2000 and 2001a). Key measurement issues are addressed (Colecchia, 2002), including: ü better measuring of firm’s dynamics, ü activities of foreign affiliates, ü e-business, ü size and growth of the information economy, ü investment in software, ü innovation, ü international mobility of high-skilled labour, ü international comparison of ICT current-price investment and ICT prices indices.
This research will produce better data and knowledge in a more distant future, but for the time being efforts are concentrated also on building a wide and consistent set of indicators of growth, science, technology and innovation, educational level and learning, whose reliability is destined to improve over time as and when the key measurement issues are solved1. In this context, SEAMATE WP1 has analysed: ü some fundamental data and issues about the ICT sector (chapter 2); ü the impacts on growth of the EU and other OECD economies (chapter 3); ü a range of IST first generation scenarios (chapter 4).
The latter include tentative scenarios, mainly speculative, of possible baseline, positive and negative results of the EU economies at the year 2010, when the policy target for Europe to be the most competitive knowledge based economy in the world should be achieved. The scenarios are based on intuitive assumptions about complex causal links tying ICT production, ICT use, workforce skills, R&D and innovation, supply side and demand side enablers of ICT diffusion, innovation prerequisites (e.g educational attainment, entrepreneurship, flows of researchers) and their contribution to GDP growth, productivity and structural change of the economies. Where the review and analysis of EU data has shown that some European countries have been more successful than others in terms of GDP growth as well as in growth of productivity, employment and effective recourse to ICT, one way to forecast a positive scenario was to assume that laggard countries will follow the example of more successful and innovative ones. Some insights provided by the IST scenarios have been used to elaborate a specific scenario in SEAMATE WP5 computing the impacts of additional growth of ICT investments in the EU countries.
1 OECD “Science, Technology and Industry Scoreboard. Towards a Knowledge-Based Economy”, 2001.
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1.2. An overall picture of SEAMATE appraisal of IT prospects, business and social impacts A conceptual framework aiming to map the main features of IST which are studied in SEAMATE is presented in the diagram A below. This helps to understand the specific scope and content of the WP1 IST scenarios and the relation with the areas covered by other two SEAMATE work-packages analysing respectively business impacts (WP2) and social impacts (WP3). WP1 research cover and summarise the trends of ICT production and use, their interrelation with the diffusion of knowledge and innovation, and the linkage with the structural change, growth and productivity of the EU economies, and finally possible IST scenarios. Actually, the use of ICT, knowledge intensive products and the diffusion of innovation in the consumer sectors is an area considered both in WP1 and WP2, the latter analysing more in depth all the facets and implications of the potentially most important use of ICT: e-commerce and more in general e-business. Indeed, the real benefits of e-transactions are being felt in areas such as B2B purchasing efficiencies, B2C distribution costs (which become almost zero in case of digitally delivered products) and B2C customer service costs, where in some cases e-commerce will also have a disfunctional impact (e.g. travel booking and ticketing). For some industries potential savings may decrease interaction time and costs by one order of magnitude, which will create a structural dynamic leading to a) greater specialisation, b) greater integration backward and forward in the value chain, with suppliers and customers, c) opportunities for new entrants and agents – i.e. new forms of intermediation. Another important area of intervention - which is not covered specifically by SEAMATE - is e-government or “g-commerce”. According to the conclusions of the High Level Expert Group on the Intangible Economy, a major pan-European g-commerce initiative is needed – in effect a fundamental rethink of the Business-to-Government and Government-to-Citizens (customers) interface.2 The social domain is addressed in SEAMATE WP3, and the main influences of socio-economic factors on ICT use are also considered in shaping future IST scenarios within WP1. Socio-economic factors are important enabling factors, and they include in particular3 income levels, educational attainment, other social and cultural factors which influences the rate of adoption and use of new ICT technologies by different groups (elderly, women) and different vategories of firms (e.g. small business).
2 EC “The intangible economy impact and policy issues” A report of the European High Level Expert Group on the Intangible Economy, 2000 3 OECD, “Science, Technology and Industry Outlook. Drivers of growth: information, technology, innovation and entrepreneurship”. 2001.
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SEAMATE - Appraisal of Information Technology prospects, business and social impacts
ICT
Production
Knowledge-based
activities
Structural change, growth and productivity
of EU economy
WP1 IT prospects
ICT Use
Household
sector
Business sectors
- structural and organisational changes
- effects on productivity and investmentGovernment
partially covered
by SEAMATE
E-government
B2B
B2C
B2E
B2G
G2C
WP2 Business impacts
ICT
acceptance
&
digital d ivide
Relat ions with
family life
Relat ions with
working life
Relations with
social life
Relat ions with
cultural factors
WP3 Social impacts
WP4 Micro-modelling of business impacts
WP5 Macro-modelling of impacts
WP6 Po licy & data needs
- functional changes of sectoral value
chains- employment effects
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1.3. Establishing IST drivers of growth The growth opportunities of the new economy can only be analysed considering several growth drivers at the time to be tackled adopting comprehensive strategies based on a policy mix4. As it is illustrated in the diagram B below, positive causal links can be postulated between GDP growth of EU countries and two broad categories of drivers of growth (even if their actual impacts on GDP growth are far from being precisely determined, mainly due to current failures of data and measurement methods):
• ICT diffusion (production and use)
• Intensification of knowledge-based activities The diagram shows, respectively, the supply side and demand side enablers of ICT diffusion and the prerequisites for the intensification of knowledge-based activities in the economy, i. e. individual and organisational learning and their enablers. A possibly positive interaction between ICT diffusion, knowledge production and learning is also postulated. These basic elements and relationships are briefly discussed below. To track GDP growth across countries and establish the links with causal factors, it is essential to decompose the nature of the observed differences. Adopting a growth-accounting framework5, economic growth can be made dependent on a number of factors, namely increased use and/or improved quality (skills) of labour, more and/or better capital in the production process, and greater overall efficiency in the combination of these factors of production, i.e. multifactor productivity (MFP)6. Those countries that registered an increase in GDP per capita in the 1990s have generally drawn more people into employment (especially increasing female participation to workforce), accumulated more capital equipment (particularly in ICT), improved the average quality of their workforce7, and, in many cases, improved MFP8.
4 To define an effective policy mix is the specific object of SEAMATE WP6. 5 According to this approach, real GDP per capita can be decomposed in the following way: GDP/POP=GDP/H x H/L x L/LF x LF/WAP x WAP/POP, where H denotes average hours worked, L employment, LF is the labour force and WAP denotes the working-age population. 6 Multifactor productivity is also referred to as total factor productivity, reflecting the overall efficiency with which labour and capital are used, MFP is affected by a host of factors, including innovation, technological change and its diffusion, managerial practices, organisational change and, more generally, improved ways of producing goods and services. See OECD, “Science, Technology and Industry Outlook. Drivers of growth: information, technology, innovation and entrepreneurship”. 2001 7 Regression estimates suggest that the long run effect of each additional year of education could raise per capita incomes on average between 4% to 7%. See OECD “Link between Policy and Growth: Cross Country Evidence”, OECD Economic Outlook, n° 68, 2000 8 OECD “Recent Growth Trends in OECD Countries”, OECD Economic Outlook, n° 67, 2000
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MFP growth is measured as a residual factor, after the contributions of increased labour and capital have been accounted for, which makes it difficult to examine all of the factors that influence it. Nevertheless, it is common (though debated) wisdom to include among the factors affecting overall productivity:
• Information and Communication Technologies that may have spill-over effects, and especially the software industry and the diffusion of ICT in the end user sectors;
• the development and diffusion of knowledge such as that emanating from R&D, and the use of new technology coupled with organisational changes and process innovation that generates benefits that exceed the cost of purchasing the equipment.
These two factors are represented in the core of the diagram, as interacting elements. In fact, ICT can be seen both as innovation per se and - due to their general purpose character - as vehicles in the diffusion and achievement of further innovation in other sectors and fields. As an example, many of the recent advances in the field of biotechnology and telecommunications would not have been possible were it not for the developments in computational speed and capacity (EC, Competitiveness, innovation
and enterprise performance, 2001 edition). Furthermore, by adopting information technologies, the very mechanism of innovation seems facilitated. Smooth interplay among actors is essential for successful innovation. Firms are more likely to innovate effectively if they are able to access and implement acquired knowledge rapidly. This accounts for a positive relationship between internal innovation capability and the use firms can make of external linkages (e.g. with large and small firms, universities, public and co-operative research labs, users). A potentially positive feedback loop exists linking diffusion of ICT - innovation – socio-cultural factors - enterprises intellectual capital and organisational improvements – GDP growth. However, this feedback between ICT and knowledge is far from being automatic, and it is to be intended more as a possible virtuous outcome depending from many factors than as certain event. As a matter of fact, circulating human knowledge is not simply a matter of search and retrieval, as some views of knowledge management might have us believe. While knowledge is often not all that hard to search, it can be difficult to retrieve, if by retrieve people mean detach from one knower and attach to another (Brown, Duguid, 2000). This is especially true for the informal know how, which often represent a great part if not all the knowledge used by people in their working practice. Beyond information retrieval, surely greatly facilitated nowadays by the diffusion of ICT, what has to be achieved is learning and understanding, which strongly depend from people capabilities to learn and understand new concepts and practices, and social interaction and imitation (“learning to be” instead of “learning about”), which continue to be facilitated by face-to-face contacts. Albeit aware of the risk to introduce some redundancy in our analysis, the influence on GDP growth has been modelled independently for the two main factors, looking separately at the contribution of ICT and that of knowledge and learning embodied in the innovation processes to growth.
12
Concerning the ICT contribution to growth, a significant impact is accounted for by software capital accumulation, and this impact is surely underestimated due to the currently still poor software expenditure estimation methods9. Collecchia and Schereyer (2001) show that in the 1995-2000 period, software capital accumulation accounted for about 20 to 30 per cent of the overall contribution of ICT capital to output growth across nine OECD countries (see also chapter 3.1 below). On the other side, a long standing tradition of international research is trying to establish a direct link between innovation and growth. Innovation, defined as the development, deployment and economic utilisation of new products, processes and services, influences growth at both microeconomic and macroeconomic levels. At the microeconomic level, innovation enables firms to respond to more sophisticated consumer demand and stay ahead their competitors, both domestically and (increasingly so) internationally. At the macro-economic level, innovation contributes to the three components of output growth: capital, labour and multifactor productivity. Several econometric analysis have been performed which show the positive effect of R&D on productivity growth (OECD 2001). Other analyses have demonstrated a link between the quality of human capital, innovation and growth. This evidence is considered in the diagram B below, showing the positive influence on economic growth and competitiveness which should stem from a stronger presence of “knowledge-based activities” in the country, enabled through “individual” and “organisational” learning. According to a recent OECD study on the new learning economy (see OECD 2001), individual learning refers to the acquisition of information, knowledge, understanding and skills by individual people, through participation in some form of education and training, whether formal (as, for example, within educational institutes) or informal (for example, learning-by-doing in the workplace). The result of individual learning is the stock of human capital, which, in turn, is a form of knowledge capital. Another form of more structural knowledge capital is produced by the organisational learning. Structural capital includes the information and knowledge embodied in, for example, data bases, customer directories, trade marks, manuals and technical solutions. It also encompasses assets related to innovations, such as licences, patents, other kinds of intellectual property rights, copyrights, trade secrets and so forth. These are controlled by firms and other organisations and not by individuals. Moreover, the knowledge and skills encapsulated in firms routines and work processes may, in certain circumstances, be retained by firms and, for example, transmitted to new employees when they join. Thus, organisational learning depends upon individual learning and builds upon it, involving the creation of new knowledge embodied into firms (and other organisations) routines. As it can be seen from the table below (source: OECD, 2001) , individual learning and organisational learning take a variety of forms:
9 An OECD Task Force, working in co-ordination with Eurostat, was set up in October 2001 to recommend procedures and best practice for software measurement.
13
Dissemination of existing
knowledge Creation of new knowledge
Individual learning (resulting in human capital)
A e.g. schooling; vocational
training; learning-by-doing in the working place
B e.g. university-based research by
PhD student; learning-by-doing in the working place
Organisational learning (resulting in structural capital)
C e.g. building data bases, creation
of routines and manuals; appropriation of technological
licences from other firms; recruitment of highly qualified
staff by firms
D e.g. R&D in universities by
research groups; R&D within firms; collaborative R&D
between firms and research institutes
Individual learning, after initial socialisation within the family, it is conventionally associated with formal education in schools, colleges and universities and with formal vocational preparation through apprenticeships and other forms of initial, work-related training. Each of these forms of individual learning is primarily concerned with the dissemination of existing knowledge (Box A). But individual learning apt to create new
knowledge (Box B) is an equal if not even more important prerequisite for innovations
of all kinds. The majority of process and product innovations, especially in science-based industries such as chemicals, biotechnology and electronics, do not occur without access to rather sophisticated forms of scientific knowledge. In this context, therefore, the role which universities and other higher education organisations play in producing
graduates (including those with higher degrees) who have the requisite levels of
scientific and technological knowledge, is crucial. Similarly, organisational process innovations may not occur without the availability of the higher level knowledge available to graduates in, for example, management studies or economics. Certainly, effective arrangements to ensure the flow of graduates with the appropriate specialist
competence from universities and other higher education into firms and other
organisations is a major element in securing the conditions for innovation to occur. Besides formal education and training, learning-by-doing is also a key process allowing individuals to acquire specific abilities to do things. “Know-how” is typically a form of knowledge that is specific to a particular firm or even a group of workers. It is difficult to codify and communicate in formal education and training courses. Quite simply, individuals are able to build significantly on what they learn through learning-by-doing by communication and exchange with others – colleagues both in the work-place and outside. The latter sharing of knowledge (or “learning by interaction”) is at the core of organisational learning, and takes a variety of forms. It may involve the acquisition of existing knowledge from other organisations (Box C), such as firms, universities, R&D institutes and so forth, through the purchase of technological licenses or other less formal types of exchange which result from routine interaction with suppliers and customers. Once acquired, such existing knowledge may be integrated with other knowledge elements in new combinations to produce innovations of various kinds.
14
Similarly, organisations collaborate with others in order to produce new knowledge – an thus potentially innovations – directly (Box D). Firms and research institutes are increasingly forming R&D consortia with the objective of generating new knowledge as the basis for innovations. Likewise, universities and firms can work together to the same end. Although individual learning includes both formal and informal ways of learning, it is difficult to measure individual learning in a broader perspective than formal learning. Therefore, as it is illustrated in the diagram, the analysis of individual learning enablers includes only measurable components as the educational attainment of people, i.e. the percentage of population who complete primary, secondary and tertiary levels of education. By the same token, only indicators of formal organisational learning processes, such as R&D investment, R&D output measured by the number of patent applications, may be used. It is well known that R&D measures are input-oriented – they capture research efforts, not research outcome. One way to capture research outcome is to trace patenting activity and to construct analytical databases from data available from patenting offices. Patents have their own drawbacks, though, mainly because they miss out on the non-patented outcome of the research and innovation process. Hence, a second and complementary tool to measure the effects of R&D is to conduct innovation surveys. Considering the three dimensions jointly (R&D expenditure, patent activity and innovation outcome) would appear to be the best way to grasp the role of science and technology in economic growth and competition. Although not considered in the subsequent statistical analysis of drivers of growth, some other factors are worth of mention. In particular, a specific aspect of human capital development is the growing
international mobility of high-skilled workers and researchers. There is well-established evidence that immigrants add significantly to diversity and are more prone to be entrepreneurial. There is also evidence that the recent U.S. boom in the ICT sector – especially software, where human capital is the key input – has been substantially fuelled and sustained by tapping into the international labour market (HLEG 2000). Highly skilled immigrants, and immigrants in general, are a source of entrepreneurship – e.g. immigrants from China and India created around 30% of Silicon Valley start-ups in 1995-98. Indeed, evidence shows that much of the international migration of scientists and engineers is localised around knowledge-intensive clusters or centres of excellence. New programmes to repatriate scientists and engineers from abroad have helped some countries increase return migration and retain talented workers, although additional efforts may be needed 10. Also the role of entrepreneurship is gaining in importance. In recent years, the emergence and expansion of ICT is placing a greater premium on entrepreneurial traits such as individuality, innovative ideas, flexibility and speed of execution. The falling costs of accessing information mean that certain of the advantages accruing to
10 OECD, “Science, Technology and Industry Outlook. Drivers of growth: information, technology, innovation and entrepreneurship”. 2001.
15
incumbents are diminishing, while new opportunities are arising for individual entrepreneurs, and for small firms, to enter markets. One tangible manifestation of entrepreneurial culture is a high rate of firm formation and of nascent entrepreneurs as well as relatively high rates of enterprise turnover 11.
11 European Commission, “Benchmarking Enterprise Policy”, Luxembourg, 2000. In the context of its “Growth” study, OECD has initiated analysis in co-operation with ten countries on firm-level dynamics of growth and productivity. A more systematic effort to compile enterprise demography data has also been launched and will involve a close co-operation with Eurostat (Colecchia 2002).
16
SEAMATE - Drivers of growth
GDP
Growth
ICT
production & use
+
Knowledge-based
activities
+
+
Supply Side
Enablers
- Network infrastructure
- Hardware & Software
- Prices
Demand Side
Enablers
- Income
- Age and sex
- Household position
Individual
Learning
++ +
Organisational
Learning
+
Learning & Innovation Enablers
- Educational
attainment- R&D investment
- R&D output
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1.4. IST indicators A task of SEAMATE WP1 has been to review the state of the art of IST data and indicators. This was intended to prepare the ground for: ü the identification of variables to measure drivers of growth and to be used in the
regression analysis of GDP growth in EU countries (in Chapter 3) ü the in depth analysis of data requirements according to policy needs performed in
WP6. The results of the review are briefly summarised below, showing:
• the scope of IST indicators and their relevance and suitability for establishing IST drivers of growth;
• the available sources of data;
• a broad list of IST indicators useful to measure impacts and monitor patterns of adaptation of EU countries to Information Technology.
1.4.1. Scope of indicators of adapting to Information Technology.
As stated in the most recent EUROSTAT documents concerning the development of Information Society statistics (e.g. Deiss, R. 2002), much of the current debate on the needs for measuring the New Economy is often narrowly focussed on the macro-economic indicators needed for growth accounting analyses - such as ICT investment series and hedonic indices for ICT. Although these are important, the strategy for developing Information Society statistics has to take into account the wide scope of Information Society policy. This has been set out following the Lisbon European Council of March 2000, where the EU countries agreed to make Europe “the most competitive and dynamic knowledge-
based economy in the world, capable of sustainable economic growth with more and
better jobs and greater cohesion”. Therefore, ultimate objectives of the Lisbon process are high employment and high growth in the context of dynamic, competitive, and modern European economies. For this reason the e-Europe process involves target setting and benchmarking in technological, economic and social domains. In this context, the SEAMATE project focuses on indicators in two main thematic areas:
• ICT sector indicators
• Innovation, human and social capital indicators
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The former concern aspects of ICT production and use, i.e. the left-hand side of the Diagram B on the drivers of growth at page 18, while the latter are strongly related both to the measurement of individual and organisational learning, i.e. the right-hand side of Diagram B. According to OECD, human and social capital are defined as distinct forms of capital, which add on to the more traditional notions of man-made capital12 and natural capital13. Human capital includes the knowledge, skills, competencies and attributes embodied in individuals that facilitate the creation of value added and personal well being. Thus defined, human capital encompasses education, both formal and informal, and health. Social capital includes the networks of shared norms, values and understanding that facilitate co-operation within and between groups. However, its measurement is problematic and still in its infancy. Therefore, proxy indicators of social conditions are used, only indirectly related to the true concept of social capital, which should imply more direct measurement of levels of inter-personal trust and engagement or interaction in social or group activities (mediated or not by ICT).
1.4.2. Available sources of data
As it has been highlighted by the first results delivered by the EU IST project NESIS – New Economy Statistical Information System (Bommel and oth., 2002), a lot of research on the new economy has been performed and predominantly consultants and statistical institutes continue to invest a lot of effort in the generation of new insights. Despite this seemingly abundance of data only a fraction can be used for a publication about the new economy. Table A below is based on an overview of the existing official sources of data, provided in Bommel and oth., 2002. Table A – Official sources of data SOURCE DESCRIPTION
METHODOLOGY SPECIFIC USAGE
ECHP European Community Household Panel
It supplies data on EU social dynamics: i) household demographics, income, accommodation; ii) persons: demographics, employment, unemployment, search for work, previous jobs, income, training and education, health, social relations, migration
EHCP suffers from several operational problems. The most important one is the lack of timeliness of the data. Data collected in 1997 are only available at the EU level at the beginning of June 2001, i.e. with a time lag of 41 months.
After a total duration of eight years (1994 – 2001), Eurostat together with Member States decided to stop the ECHP project and to replace it in 2003 with a new instrument, EU-SILC (see below).
12 i.e. the produced means of production like machinery, equipment and structures, but also non-production related infrastructures, non-tangible assets, and the financial assets that provide command over current and future output streams (OECD, 2001). 13 i.e the renewable and non-renewable natural resources which enter the production process and satisfy consumption needs, as well as environmental assets that have amenity and production use, and are essential for the life support system (OECD, 2001).
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EU-SILC Statistics on Income and Living Conditions
This new instrument to be launched by Eurostat in 2003 will be the EU reference source for comparative income distribution and for social exclusion statistics. The data will be collected at the national level in form of micro-data covering income, labour, demography, housing, education and health at the same time
A legal basis will be developed, consisting in a framework regulation for data definition of the European Parliament and the Council supplemented by Commission Regulations for the implementation. One of the most important Commission’s Regulations will concern the list of variables covered.
From ECHP and SILC can be derived to what extent households and persons have a Personal Computer. This variable can be broken down by households and personality traits. Other indicators concerning social inclusion issues in the new information economy can be built with data coming from this survey.
CVTS European Survey of Continuing Vocational Training in enterprises
The European Commission launched a new survey of continuing vocational training following on the first survey, conducted in 1994. The second survey (CVTS2) was conducted in 2000/2001 in all the EU countries, Norway and nine candidate countries.
There is a solid methodological base which: i) ensures that data are collected on a consistent basis across all participating countries and up to a certain quality standard; ii) ensures that sampling design is according to statistical theory; iii) is flexible enough to cope with the different systems for data collection in different participating countries and in different companies.
The survey provides information about the number of ICT courses and the amounts of hours spent on ICT courses in enterprises. Moreover, information is provided about costs, funding and participation rates. These indicators can be broken down by type of training, internal or external courses, sex and by type and size of company.
Harmonised UNESCO/ OECD/Eurostat data collection on education (OECD Education at a glance)
The goal of the data collection on statistics of education is to provide internationally comparable data on key aspects of the education systems, specifically on the context, participation, and the costs and resources of education
An electronic questionnaire is sent to data providers. These are the National Statistical Institutes or other public bodies. No prerequisites are set in terms of the type of data source the information is extracted from.
The data collection on education provides information about enrolments, new entrants, graduates, class size and educational finance. By means of the ISCED-classification it is possible to select ICT-educations
European Social Statistics. Labour Costs
The Community Survey of labour costs are the only statistical instruments providing detailed comparable data on wages and related employer contributions in the Member States. Questions are asked about the labour costs, direct costs and direct remuneration, number of employees and average number of hours worked during the year.
The surveys on labour costs are at present carried out every four years. The latest refer to 1996 (1997 for Italy and Sweden). The legal basis is a Council Regulation which marks the culmination of a lengthy process involving detailed preparatory work in co-operation with the national statistical services of all Member States.
Comparison of labour costs between industries or services that are knowledge-based and those that are less knowledge-based. A similar comparison can be made for industries that differ in the level of ICT-intensity.
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Third Community Innovation Survey. Harmonised questionnaire
Innovation surveys (CIS) have been developed and undertaken in the EU countries since the publication of the Oslo manual in 1992. Questions are asked about product and process innovation, not yet completed or abandoned innovation activities, innovation activity and expenditure, intramural research and experimental development, effects of innovation, public funding of innovation, innovation co-operation, sources of information for innovation, patents and other protection modes, and other important strategic and organisational changes in an enterprise.
The innovation survey is held on an irregular basis (mostly 3 or 4 years intervals) and is mandatory only in a few countries. These surveys in most countries suffer from some problems of quality due to low response rates. The status of the surveys is ad hoc and the data content varies according to research needs. Moreover, the meaning of variables could vary due to rephrasing of questions.
R&D questionnaires: harmonised questions
R&D surveys have after many years of development reached a certain standard of quality. In these surveys questions are asked about expenditures on R&D with own personnel, expenditures on R&D by third parties and the sources of expenditures on R&D
The R&D surveys are held on a regular basis (annual or every second year). These surveys have satisfactory response rates, are mandatory in many countries and have a fairly stable data contents.
Both the R&D surveys and the innovation surveys can be used almost entirely as the indicators in the survey delineate a picture of the extent to which the economy is dynamic and knowledge-based. Recently several co-ordination options between the R&D and the innovation survey are discussed. There are several reasons to merge or integrate both surveys at least in part. An important reason is that the R&D and the innovation surveys provide inconsistent information about R&D. Moreover, especially at the level of European Commission there seems to be a need for more information on innovation than those provided by the CIS surveys every fourth year.
Eurostat pilot survey on E-commerce 2001
As enterprises have embraced electronic commerce, demand for statistics to analyse the phenomenon has grown, both from policy makers and the business community. In response Eurostat, in conjunction with the EC’s DG for Enterprise, launched a pilot survey on e-commerce. This is a survey on a yearly contract basis. Questions are asked about the use of ICT, the use of e-commerce for purchases and the use of e-commerce for sales.
This is a sample survey based on questionnaires. Eurostat Structural Business Statistics enquiry provides the sampling frame in order to estimate the total value of e-commerce for the sectors surveyed. The data is collected by the National Statistical Institutes. The sampling units are enterprises. The reference period is 2000 for % of sales/purchases data. January 2001 for other data. The sample size should be appropriate for obtaining representative results (at least 2000 filled in questionnaires should be collected in total in each country)
Community Survey on ICT Usage in Enterprises (e-commerce) 2002
This is a survey on a yearly contract basis. Questions are asked to enterprises about: a) general information about ICT systems; b) use of the Internet; c) E-commerce via Internet; d) E-commerce via EDI and networks other than Internet; e) barriers on e-commerce.
The sampling units in this questionnaire are enterprises. The reference period is the year 2001 for the % of sales/purchases data, and January 2002 for the other data. The order and layout in which the questions are set out is up to the contracting country (national statistical office). Eurostat circulates a model questionnaire as a guide. At least 2000 filled in questionnaires should be collected in total per country
Both the survey on e-commerce in 2001 and the survey on ICT-usage (e-commerce) in 2002 are entirely relevant for the analysis of the new economy. The surveys provide information about the extent to which enterprises in the European area use ICT and Internet. Moreover, the economic significance of e-commerce is registered.
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Community Survey on ICT Usage in Households 2002
This is a survey on a yearly contract basis. Questions are asked to individuals and to households about: a) access to selected IC technologies; b) use of computers and internet-location, frequency of use; c) purpose and nature of activities on the internet; d) internet commerce details: activities and barriers
The survey is a household survey with households and individuals as sampling units. The persons interviewed should be between 16 and 74 years of age. The reference period is the first quarter of 2002. The order and layout in which the questions are set out is up to the contracting country, but a model layout and a recommended list of variables is also available from Eurostat. At least 4000 filled in questionnaires should be collected per country
The entire survey is relevant for the analysis of the new economy, including also social aspects.
Structural Business Statistics
Business statistics give information on the wide range of activities of enterprises. The availability of information ranges from firms demography, to data on employment and accounting.
The specific methodology of the Structural Business Statistics has been laid down in Council Regulation (EC, Euratom) No 58/97 of 20 December 1996. The Council Regulation concerns among other definitions, the use of sources, type and frequencies of statistics, the type of breakdown that should be made possible etc. The National Statistical Institutes are responsible for gathering the data and forwarding the results to Eurostat in accordance with the standard coding scheme
From the Structural Business Statistics it is possible to select those enterprises that belong to the ICT-sector (as defined at OECD level, see par. 2.2 of this report for definition). As a consequence, important indicators like production values, the value added of the ICT industry and services, investments in the ICT-industry and services, Import and Export in the ICT industries and services, intermediate consumption of ICT related goods and services by companies and households can be used. The same type of indicators are available for the ICT content sector.
Labour Force Survey
The Labour Force Survey is a harmonised questionnaire that examines the characteristics of the employed and unemployed active population in the European Union. Questions are asked about the demographic background, the labour status, employment characteristics of the main job, hours worked, the second job, previous work experience, search for employment, methods used to find work, main labour status, education and training, situation one year before the survey, income and atypical work
The provision of the indicators in this survey is mandatory for the Member States. A detailed presentation of the information provided by the survey is given in Annex IV of Commission Regulation (EC) No 1571/98, which lays down the rules for applying Council Regulation No 577/98 on the organisation of a Labour Force sample survey in the Community. The National Statistical Institutes are responsible for gathering the data and Eurostat is responsible for the processing and disseminating the information forwarded by the national institutes.
Within the population of the Labour Force Survey it is possible to select ICT-related occupations and break these by background variables like age, sex, education etc. Moreover, a selection can be made of the HRST (Human Resources devoted to Science and Technology) according to the OECD Frascati manual.
Household Budget Survey
The information collected via the household budget surveys (carried out in most countries all over the world) covers a wide variety of items concerning consumption expenditures and income private households, savings and indebtedness, household characteristics etc.
The exact methodology for Household Budget Surveys is laid down in “Household Budget Surveys in the EU: methodology and recommendations for harmonisation”. In all HBS, data collection involves a combination of: a) one or more interviews, and b) diaries or logs maintained by households and/or individuals, generally on a daily basis.
The HBS provides the possibility to calculate the expenses made on products that are typical for a new economy. Examples of these are ICT equipment like computers, internet connections, internet enabled mobile phones etc. However, the use of the European HBS is severely hampered by the fact that the data is only collected about every five years.
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Comext (Trade statistics)
In broad terms, the aim of international trade statistics is to record all goods that add to or subtract from the stock of material resources of a country by entering or leaving its territory. By their nature, international trade statistics are concerned with transportable goods. European foreign trade is available in the Comext (Community External Trade) database. From the basic data provided by the Member States’ statistical services Eurostat compiles the statistics on Community external trade and trade between Member States
The work of Eurostat on the compilation of trade figures for the EU rests on a firm legal basis, which is set out in a series of Council and Commission regulations. Nevertheless, the work is a co-operative effort between Eurostat and the appropriate bodies in the Member States which are responsible for collecting and processing the basic information.
The COMEXT database can be used to register to what extent knowledge intensive products (e.g. PCs) are exported or imported.
The price of Internet access and use (OECD)
For consumers and small business, the most significant costs for engaging in electronic commerce are the prices of local communication access. For a user accessing the Internet, via dial-up service, the following basic charges apply: public switched telephone network (PSTN) fixed and usage charges, and the charges of an Internet Service Provider (ISP). The OECD compares these prices for the largest telecommunication operator in each OECD member country
Prices of local communication access include: a) fixed charge (monthly line rental for a residential use); b) usage charge (price of a local telephone calls – or special rates for Internet access – to an ISP for residential users; c) ISP charge (price of Internet access from the largest telecommunication operator; d) discount scheme (the best available scheme is selected); e) tax (the value added tax rate); f) peak and off-peak prices of local calls during weekdays
Access price is a key variable to analyse Internet diffusion in different countries. Usually, the lower the access prices the more people can afford it.
As can be seen from the table above, only some official sources respect the criteria of having a robust methodology and timeliness. This is true in particular, among other more traditional surveys, of the harmonised R&D questionnaires. Structural Business Statistics and Labour Force Surveys, while methodologically robust, pose some problems of timeliness, especially for monitoring highly dynamic sectors as ICT. The substitution of the now obsolete European Community Household Panel with Statistics on income and living conditions, since 2003, promises to offer in the years to come more comparable and timely data on social conditions. Table B below is based on an overview of the existing non-official sources of data, provided again in Bommel and oth., 2002.
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Table B: Most relevant non-official sources SOURCE DESCRIPTION
METHODOLOGY SPECIFIC USAGE
European Information Technology Observatory (EITO)
EITO is a broad European initiative the objectives of which are to provide an extensive overview of the European market for ICT and to render services to this industry, to users and to public authorities. Since 1993, EITO establishes a yearbook for the ICT market and industry in Europe. Periodically, EITO highlights specific topics like ICT skills, E-economy/E-commerce or technological trends and standards. EITO works together with various major market companies to discuss and assess statistics and other data.
The European Information Technology Observatory by EITO is heavily based on data gathered by IDC (see below). Indeed, the data and trends in the statistical outlook are the result of the overall statistical framework provided by IDC, and the considerations and assumptions by the EITO Task Force. As the methodology is very unclear (opinions instead of statistics) it is doubtful whether or not one should rely on these figures.
At least as far as official statistics on ICT investment and expenditure on ICT goods and services will be made available more systematically from official sources, EITO is the only source available for some key ICT market variables, as the yearly market value of ICT equipment, Software products, IT services and Carrier services. However, the methodology to obtain these estimates is unclear and their reliability is scarce.
International Data Corporation (IDC)
IDC is a leading provider of technology intelligence, industry analysis and market data. The company offers insights and advice on e-business, the Internet and communication technology, apart from forecasting markets and trends. IDC is based in USA but has world-wide analysts working in 43 countries. IDC is notably involved in the European EITO initiative, where it helped create EITO’s overall statistical framework.
Data collection by survey and publication of the ISI is yearly. The top 10 ISI countries include Sweden, Norway, Switzerland, Denmark, the Netherlands, United Kingdom and Finland, apart from the USA and Australia, but supposedly a large number of countries is included. No further information is readily available on methodology and weighting of the index.
IDC establishes a yearly Information Society Index (ISI), being composed of the following four subindexes: “Computer”, “Information”, “Internet” and “Social”.
International Telecommunication Union (ITU)
The ITU is an International Organisation within the United Nations System, where governments and the private sectors co-ordinate global telecom networks and services. ITU was established in 1965 as an impartial organisation. ITU’s standardisation activities have notably helped in the growth of new technologies such as mobile telephony and the Internet. ITU has a long tradition in gathering statistics on telecommunications.
The data are collected from an annual questionnaire sent out by the Telecommunication Development Bureau (BDT) of ITU. Additional data are obtained from reports provided by telecommunications ministries, regulators and operators and from ITU staff reports. In some cases, estimates are made in by the ITU staff, and are regularly noted in the database and publications. It is possible to generate time series from 1975 to 2001. Data for over 200 economies are available. However, the heterogeneity of sources weakens the quality of ITU data.
ITU provides telecommunications statistics which are basic items for measuring the new economy. These include the number of various subscriptions (ISDN, Cable-TV, Mobile phones etc.) and the telephone traffic, the telecommunication’s investment and revenues, full-time employed staff, and the estimated number of PCs and Internet users.
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Eurobarometer (e-Europe action plan)
To make the European Union a full participant in the innovative, knowledge-based economy, the Lisbon European Council endorsed the eEurope Action Plan in June 2000, which targets three areas: a) cheaper, faster and secure internet; b) investing in people and skills and, c) stimulating the use of Internet. Monitoring of the progress of this plan was entrusted to the Working Party on Information Society Services, which drew up, in November 2000, an initial list of 23 indicators.
For data collection on eEurope indicators, the following guidelines applied: a) one methodology should be used for all EU member states; b) data should be recent; c) data was to be cross checked with existing data sources and, d) data should cover all EU member states, Norway, Iceland and, where possible, the US. Therefore, many of the 23 specified indicators are measured by sample surveys, Eurobarometers. The standard Eurobarometer survey is based on an average of 1000 face-to-face interviews per EU member state. The survey is conducted between two and five times a year, with reports published twice yearly. Flash Eurobarometers are conducted, by phone, throughout the EU if and when needed by any service of the European Commission or other EU institutions/agencies.
This source provides the following eEurope benchmarking indicators: 1. % of population who regularly
use the Internet; 2. % of households with Internet
access at home 3. Internet access cost 4. Speed of interconnections
between and within National Research and Education Networks
5. Number of secure servers per million inhabitants
6. % of internet users that have experienced security problems
7. Nr. of computers per 100 pupils in primary/secondary/tertiary levels
8. Nr. of computers connected to the Internet per 100 pupils
9. Nr. of computers with high speed connection per 100 pupils
10. % of teachers regularly using the internet for non-computing teaching
11. % of workforce with at least basic IT-learning
12. Nr. of places and graduates in ICT third level education
13. % of workforce using telework 14. Nr. of Public Internet Access
Points (PIAP) per 1000 inhabitants
15. % of central Government web-sites that conform to the WAI accessibility guidelines
16. % of companies that buy and sell over the Internet
17. % of basic public services available on line
18. Public use of Government online services
19. % of public procurement which can carried out online
20. % of health professional with internet access
21. Use of different categories of web content by health professionals
22. % of EU web-sites in the national top 50 visited
23. % of the motorway network equipped with congestion information and management systems
With the exception perhaps of ITU, the non-official sources above suffered from the fact that, to comply with the task to monitor the new economy, they had to produce their own statistical data by themselves, given the lack of official data.
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Obviously, although the efforts made by some of these non-official sources are remarkable, their statistics lack of the solidity that only new official statistics could ultimately ensure. Some of these sources, e.g. EITO and the Eurobarometer, may benefit in the years to come from the planned developments of the official statistics, that, according to the Eurostat work programme for Information Society Statistics, include:
• definition and consolidation of indicators for eEurope benchmarking (Eurobarometer);
• statistics for macroeconomic analyses, such as ICT investment and hedonic price
indexes for computers.
• enterprise statistics, including ICT usage, computer services, skills, the influence of ICT on business processes and innovation etc.
• household statistics on ICT usage, including use of computers, the Internet, e-commerce, ICT skills, take up of broadband, wireless telecommunications, and new audiovisual services, trust and security issues, electronic interaction with public administration and the digital divide.
• other Information Society aspects of social statistics, including education, training and health (human capital related statistics).
• ICT usage by public administrations. What seems to lack in this rather long “shopping list” for future statistics is an appropriate focus on literacy and cultural level of population. These are aspects obviously related with the production of knowledge and the quality and value of the contents carried through Internet. Actually, there have been recent attempts to build indicators on literacy skills (reading and writing, mathematical, scientific) for the knowledge society, but they need to be further developed and, above all, included into the circuit of official statistical processes, e.g. promoting a Community Literacy Survey. We refer here in particular to the PISA (Programme for International Student Assessment) experience. PISA is an internationally standardised assessment administered in 32 countries (of which 28 are members of OECD) to samples between 4.500 and 10.000 of 15 year old students in the schools. Although the assessment of cross-curriculum competencies is an integral part of PISA, its aim is to define knowledge and skills not merely in terms of mastery of the schools curriculum but in terms of abilities in adult life. These will imply in particular not only the ability to read and write, but also mathematical, scientific and technological literacy.
1.4.3. Broad list of IST indicators
The data discussed in the previous paragraph represent the primary sources for building indicators of the new economy. As stated above, not all these sources are equally reliable and timely, and the situation is also highly dynamic. In this context, there are a sort of “secondary” sources, represented mainly by annual or periodical reports of international organisations (e.g OECD, EC, Eurostat, United Nations etc.), which are helpful because they usually filter the most reliable and updated information available, and elaborate comparable indicators. The indicators presented in these reports refer
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more or less explicitly to the official sources of data presented above, and in some case also to non-official sources (notably ITU). A battery of almost 60 indicators has been formed with the purpose to track the evolution of IST related issues, taking stock of the data and indicators available in the following reports:
• ITU – Telecommunication Indicators in the Eurostat Area – 2001
• OECD – Science, Technology and Industry Scoreboard – 2001
• OECD – Education at a Glance – 2001
• EUROSTAT – Information Society Statistics – Statistics in Focus, 2001
• EUROSTAT – E-commerce – Statistics in Focus, 2002
• UNITED NATIONS – Human Development Indicators – 2000 The main advantage of taking indicators from these reports is that they are regularly published (mainly on a yearly basis), and this will make possible to constantly update the information. The list of indicators taken from each report is given in table C below. A more complete account of the same indicators (short description, measurement issues, time coverage) is given in Annex A. Table C – Broad list of IST indicators SOURCE INDICATORS
International Telecommunication Union (ITU)
• Cable TV subscribers
• Mobile telephone subscribers
• Full-time telecommunication staff
• International outgoing telephone traffic
• Main telephone lines in operation
• Personal computers
• Telecommunication investment
• Telecommunication revenues
OECD Science, Technology and Industry Scoreboard
• Internet hosts
• ISDN subscribers
• Internet access prices
• TV channels per 100 inhabitants
• Gross Domestic Expenditure on R&D (GERD)
• R&D expenditures by business, government, higher education
• Financing of R&D
• Business expenditure on R&D (BERD)
• Business R&D intensity
• R&D in selected services and manufacturing industries
• R&D in high-medium-low technology industries
• R&D in ICT-related sectors
• Gross Domestic Product (GDP)
• GDP per capita and GDP per hour worked – time series
• Breakdown of GDP per capita (Hourly productivity; Average working time; Employment rate; Labour force participation rate; Share of working age population) – Year 1999
• Breakdown of value added by 9 aggregate industry and service sectors
• Value added of high-medium-low technology industries and knowledge-intensive services
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• Import penetration of high-medium-low technology industries
• Export ratio of high-medium-low technology industries
• Contribution to trade balance of high-medium-low technology industries
• Gross Fixed Capital formation
• Foreign direct investment flows
• Technology balance of payments
• Number of patents (triadic patent families)
• Researchers per 10,000 labour force, by sector of employment
• Population 25-64 by level of educational attainment
OECD Education at a glance
• Use of Internet in schools
• Labour force participation rate by educational level and gender
• Unemployment rate by educational level and gender
• Relative earnings by educational level and gender
• Full-time and part-time employment of youth population, by educational level and gender
• Participation to training activities by employment status and gender
• Public expenditure on education
• Ratio of students to teaching staff
• Training outside formal education
• Science graduates in the youth labour force
• Graduates by field of study
EUROSTAT Information Society Statistics
• Number of enterprises in the ICT sector
• Employment in the ICT sector
• Value added of the ICT sector
• Turnover of the ICT sector
• ICT import, export and trade balance
EUROSTAT E-commerce
• Share of enterprises using ICT
• Use of e-commerce for purchases
• Use of e-commerce for sales
UNITED NATIONS Human Development Indicators
• Population by age (0-19, 20-65, over 65) and gender
• Urban population
• Income disparity (ratio of richest 20% to poorest 20%)
• Female activity rate
• Long-term unemployment, by gender
• Part time employment, by gender
Data related to the list of indicators of above have been collected from the various sources and stored into a single data base. Some of these indicators have been used in the regression analyses illustrated in Chapter 3, with the aim to test their explanatory power as drivers of the growth of GDP.
1.4.4. Data and measurement problems
As mentioned above, there are serious problems and limits of the statistical base, especially concerning the ICT data, and the analysis and interpretation thereof must be taken with great caution. Indeed there are both problems of “meta-data” – at least as long as sectoral breakdown of official statistics will continue to combine new economy activities with traditional industries14 - and scarce reliability of non official sources.
14 for instance, the production of computer and the production of office equipment are in the same aggregate. The provision of telecommunication services shares the group with traditional postal services.
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What all current predictions on ICT development have nonetheless in common is that there will be great growth in the entire media and communications sector. But if all the growth predictions for the individual media and communications segments are added together, the total arrived at far exceeds any realistic order of magnitude justified by the expected growth in private consumption and the economy as a whole. For these predictions to be fulfilled there would have to be a substantial shift in expenditures from areas of substitution in other sectors to the media and communications sector. Therefore, a standardised definition and method of registration must be worked out as quickly as possible to trace the development of the media and communications sectors and segments within it, one that can be used both by national statistical authorities and by EU institutions. The recent ECC Report15 provides an overview of the currently unsatisfactory way of recording ICT activities in the national accounting framework. Indeed, there are three segments that count as potential revenue sources for the ICT sector in a country. These are expenditures on media, information and communication goods and services disaggregated according to their having been decided in: - private households (household final demand); - private business (business intermediate demand); - public or state institution (government final demand). There are several problems connected with the task of estimating these data:
• National accounting still lacks a standardised definition of the media and communication sector as a branch of the economy. Companies concentrating principally on the manufacture and sale of media, telecommunications and information technology products are assigned to different areas of the economy. This makes it hard to draw comparisons on an international level, as the individual countries use different conventions.
• Depending on whether a narrower or a broader definition is favoured, divergences will emerge in the basic figures used, leading in turn to discrepancies in the predictions for future development.
• There is not an adequate statistical allowance for areas of substitution. Substitution relationships within sectors exist, for example, between expenditure for print media, video and letter post. Many other examples could be easily done.
The above mentioned problems are well known in the community of statistical experts, and concrete efforts are being undertaken, especially from OECD and EUROSTAT, to ameliorate the coverage and quality of ICT related statistics. However, the boundaries of ICT statistical classifications currently in use doesn’t include the media services and entertainment industry, although some interest exists in measuring digital products and services16.
15 European Communication Council, op. cit. 16 i.e. goods/services that can be ordered and delivered directly to a computer over the Internet, e.g. music, videos, games, computer software, online newspapers, consulting services etc.
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2. Setting the stage: the ICT sector 2.1. Recent evolution At the core of the IST scenarios there is the evolution of the ICT sector. At the outset, the ICT sector was mainly made of isolated computer machines and basic software. Although the development of computers had started in the 1940s, the rise of the “computer age” only started in the 1970s, with evidence of the impact of ICT on aggregate productivity figures only having been recently observed17. However, this lag between the technical leap of the microprocessor since the early 1970s and the first evidence on the aggregate level – measured ex post – in the second half of the 1990s, appears to be rather short in comparison to the “great inventions of the past”. For instance, the cluster of technologies including the internal combustion engine, electricity, petroleum and petrochemicals, telegraph and telephone, developed in the period between 1860 and 1900, is thought to have contributed to the pick up of productivity growth only after 191318. Nowadays computers are networked through the telecommunication network and the Internet. The ICT sector therefore includes telecommunication, hardware and software industries and Internet services. The main technological drivers contributing increased cost-effectiveness in the present transition to a network economy are:
• digitisation
• miniaturisation
• standardisation The basic technological breakthrough is actually digitisation, i.e. the conversion of information into digital units (bits) and its processing and transmission at the speed of light. On top of this, however, there have been the technological advances forecast by Moore’s law. Named after one of the founders of Intel, Mr. Moore predicted back in the 1960s that the computational power of computers would double every 18 to 24 months, and it is remarkable how well this prediction has fitted the real evolution of computer capacities, boosted by the increasing miniaturisation of almost all components in information and communications technologies. The driving force behind this process of miniaturisation is the increasing integration density of micro-processors, i.e. the increasing number of transistors contained on a chip19.
17 In this context, the “Solow paradox” saying, “computers are visible everywhere but in the productivity statistics” from 1987 has become famous (Solow 1987). 18 European Commission, “The EU Economy review 2000” European Economy n° 71 19 The effects of this are illustrated by the development of the Intel processor. While the first microprocessor 4004 from Intel in 1971 contained 2300 transistors, the Pentium II processor introduced onto the market in 1997 has space for 7,5 million transistors. See Madden, A. “The Lawgiver Gordon Moore”, The Red Herring, 1998
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Besides these technical developments, one of the most important preconditions necessary for ICT potential to be realised is standardisation. This is crucial to ensure the compatibility of sub-systems for all concerned, rationalise the learning necessary, and above all foster planning security for further investments. At issue here are above all the so-called de facto standards, which gain general acceptance either trough market based selection processes, as was the case with PC operating systems, or occasionally through the activities of voluntary association of operators, as with the GSM standard in mobile communication. Furthermore, the increasing use of digital technology to store, process and transmit any kind of information is nowadays making the convergence of traditional ICT with the media and entertainment industry a concrete market prospect. Actually, the first stage of convergence consisted in the merging of value chain activities between the telecommunications and the IT sectors, creating “ICT”. The second stage of convergence is taking place at present, with the value chains of the media, telecommunications and IT sectors that are increasingly merging. Two trends especially demonstrate the effects of this process20:
• the transmission of media content is no longer the exclusive domain of the broadcasting networks (cable, satellite and terrestrial networks), but classical telecommunications networks too (telephone and computer networks) are becoming more and more important in the dissemination of content;
• new conditions of competition have also emerged in the field of reception appliances. Appliances from all three sectors (television, telephone, computer) can be used for the reception or operation of the distinct information, entertainment and communication services.
The convergence of the three media and communications sectors entails not only fundamental changes for the media, telecommunications and IT industries themselves, but bring economic consequences that touch numerous areas of the economy and society in general. ICT production stands out from other, more traditional industries, because of the speed with which new innovations occur. Beyond competition on time-to-market, ICT is likely gaining ground because of increasing returns to scale in production. Development costs may be very steep for ICT equipment, but once the product is ready, unit costs will start falling precipitously (e.g. downloadable software is featured by near zero marginal production and distribution costs). By the same token, ICT markets may be benefiting from network effects. When one member is connected to a network – such as the Internet or a widely marketed computer programme – this person can connect to all existing members. In turn, this means that the value of belonging to the network, measured as the number of interconnections that can be established, increases more than proportionately with the number of individuals belonging to the network. The upshot is
20 European Communication Council Report, “ E-economics. Strategies for the Digital Market”, Springer, 2000
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that diffusion of ICT and, consequently, its production, has most likely to attain a critical mass before yielding maximum benefits. As to ICT-using industries, several studies21 show how ICT may boost productivity as increasingly powerful computers are deployed for carrying out the same tasks. By enabling the interconnection of firms and households, ICT may also be unleashing entirely new productive forces. But merely investing in ICT is not enough. Besides the level of ICT spending, the productivity gains will be determined by the way the equipment is employed, notably the accompanying investments in organisational restructuring.
21 evidence of ICT impacts in the using sectors is more deeply investigated in SEAMATE WP2
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2.2 - ICT proper – outlook of technology prospects and policies
2.2.1 - Mainframes
The market for proprietary mainframes is now almost exclusively a replacement market: new system sales are rare. Mainframes sold are mainly used for applications supporting thousands of users, e.g. large banking and airline reservation systems. In very many cases systems are built in which mainframe and network platforms co-exist and work together. New systems are composed of mini- and micro-computer networked systems built on the new open architectures; UNIX, NT, and client server. In the last decade PCs have evolved into powerful information processing machines increasingly miniaturised. Laptops, notebooks and palmtop computers are fully capable of offering powerful computing. Even the powerful processors running UNIX machines are combining with PC chip designs to bring high powered computing to small devices. The computing power of palmtops is tending to surpass levels which in the 1960's were hardly available in mainframes. Consequently plausible scenarios should hardly deal with mainframe development. In what follows attention will be concentrated on current micro, distributed, networked hardware and its rapidly evolving new forms and functions.
2.2.2. - PCs Penetration
Common use of personal computers is a prerequisite to the diffusion of ICT and to the application of the tools and resources it provides (E-commerce, E-business, E-government, etc.). In 1990 PCs penetration in most European countries was between 5 and 10%. Available data are hardly reliable as there is no public registry of PC's, like for cars. However the EUROSTAT time series (see the following Table) represent an acceptable approximation. The data have been processed for the total of the 18 countries listed and also for France, Germany, Italy and UK - accounting for two thirds of the total. This was done by fitting to the corresponding time series Volterra-Lotka equations, well known to depict accurately the growth of parks or populations of human artifacts. The fit was not very good as indicated by fairly high values of standard errors: this reflects negatively on the quality of data (admittedly quite hard to retrieve). However an attempt was made to build credible Volterra equations. The results given in the last 3 columns of the table, are: asymptote, standard error and value of the PC park possibly reached in 2010. Comparison of the totals and of the sum of the values for the 4 selected countries and for the EU15 total, indicates a rough cross-footing. Consequently it is reasonable to assume that in a business as usual scenario the number of PCs in most of Europe will grow by about 70%. This reference level is used in building the outline of tentative scenarios presented later in this Deliverable (Chapter 4).
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Table 1: Personal Computers (million)
Source: Eurostat In order to give a feel for the quality of available data, a comparison follows between numbers of PC's in use as reported by Eurostat and PC shipments as reported by EITO (in "EITO, European Information Technology Observatory 2001"). The table below deduces scrappage for EU15 and Italy from PC park and shipments. It's just an example to show that available data on scrappage may be used, if reliable, to cross-foot other relevant data.
Table 2: PC's park and shipments (in million units) for EU15 and Italy
EU15 Italy PC park 1998 84.7 10
PC park 1999 93.5 11
Increase '99 on '98 8.8 1 PC shipments 1999 25.3 2 PC shipments 2000 28.7 2.43
PC shipments 2001 32 2.8
PC shipments 2002 36 3.1
Presumed scrappage 1999 (= shipments less increase) 16.5 1
Most EITO tables show figures for the years 1998 to 2002. The figures up to 2000 are actual and those for 2001 and 2002 are projections. However, the document does not explain how these forecasts were produced.
2.2.3. - Network computers
Network Computers (NCs) feature much lower unit costs and operating expenses than traditional PCs, they are also strongly standards based to ensure that numerous different hardware and software implementations will interoperate properly. Applications include: decoding cable, digital terrestrial, or satellite transmissions, allowing access to video on demand, and providing access to the Internet. It is expected that many different companies will be producing Network Computers for different applications and there will be many different hardware and software implementations. So it is essential for NCs to conform to a standard Network Computer Profile. This is a standard maintained by the Open Group, which defines the minimum facilities to be provided (e.g. SMTP for sending mail and http for fetching web pages. Details can be found at http://www.opennc.org/). The Mobile Network Computer Reference Specification (MNCRS) is an extension of the Network Computer Profile, with special attention given to the requirements of mobile applications. Details can be found at http://www.mncrs.org/. Most network computers are probably going to be for home use, having lower bandwidth, intermittent, network access and a TV as a display device. Set top boxes are used to access digital or cable TV, with high speed network access. Dumb terminals just display the output of programs run on servers. Normal PCs may also run software conforming to the open standards of network computers. Mobile devices (palmtops, laptops, PDAs) can be used as NCs if connected to a network, but also work independently. It is unlikely that network computers will replace traditional PCs. It has been suggested that they will be used mainly by the many people who do not own a traditional computer because of the high purchase and maintenance costs, and in new applications such as digital TV set top boxes where there are currently no computers. The relative proportion of the number of network computers in use to that of classic PCs will depend on the distribution of cultural and technical proficiency in the population at large. A wide use of network computers may be construed to represent a generalised cultural upgrading of the public, but this would be largely illusory. It would be more constructive to aim at the dissemination of general culture and computer literacy adequate to facilitate the use of more sophisticated machines (successors of present day PCs) by the majority of citizens.
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2.2.4. - Internet
The technology currently referred to as the Internet22 originated in the early 1960s when a division of the US Department of Defence, the Advanced Research Projects Administration (ARPA), developed a system called the ARPAnet to link together universities and high-tech defence contractors. ARPAnet was actually a by-product of the search for a communications network that could link branches of government likely to escape destruction in the event of war. The thinking was that information transmitted on (what we now call) the Internet – since it travelled via packets rather than closed circuits – would still get through even if certain telephone networks were destroyed because such packets would find whatever pathways were still available23. 2.2.4.1 - Basic technology and infrastructure
The infrastructure is organised in a straightforward hierarchy consisting of backbone providers at the top, regional networks next, and Local Area Networks (LAN) at the bottom. The Internet also resembles a road system in the manner in which information is transmitted. As above mentioned, the Internet does not employ circuit-switching technology, as telephone networks do, but utilises a packet-switching technology. In the case of circuit-switching, a circuit must be established between two customers before they can make a phone call, and that circuit must remain open for the entire duration of the call, even in periods of dead silence. The Internet, by contrast, allows more than one sender to transmit data along a pathway at the same time. The data travel in small packets, usually consisting of approximately 200 bytes, which do not require a dedicated circuit. To return to the highway analogy, the time of delivery would depend in this way upon the quality of the road, and the amount of traffic encountered in transit. The technology that allows such data transmission to occur is known as the TCP/IP protocol. Congestion on the network during periods of high user activity can severely inhibit delivery time and performance. As yet most networks have no means of addressing the traffic problem and do not assign priority classes for packets. Delivery remains almost instantaneous when traffic is low, but during high traffic packets enter a queue and are usually transmitted on a first-in-first-out (FIFO) basis, regardless of their importance. As a result, some packets may be substantially delayed or discarded altogether. New technologies are helping to relief congestion without having to ration access. Broadband Internet services are enabling users to surf on the web at much higher speeds. However, as the Internet becomes increasingly popular congestion may arise
22 Internet has been defined as “the globally information system that: i) is logically linked together by a global unique address space based on the Internet Protocol (IP) or its subsequent extension/follows-ons; ii) is able to support communications using the Transmission Control Protocol/Internet Protocol (TCP/IP) suite or its subsequent extentions/follow-ons, and/or other IP-compatible protocols; and iii) provides, uses or makes accessible, either publicly or privately, high level services layered on the communications and related infrastructures described therein” (US Federal Networking Council: Definition of “Internet”, 10/24/95, www.fnc.gov/Internet_res.html). In contrast, the World Wide Web is an application that runs on that network (see Section 2.3.10 below). 23 Tapscott, 1996
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with these technologies too, absent any sort of rationing mechanism24. In the following we will describe in turn the options available to increase Internet capacity on the supply side, and to ration access on the demand side. 2.2.4.2 - Increasing Internet capacity
According to several estimates reported in Section 2.4.1 of this Deliverable, the number of Internet users is rapidly growing. This growth in web usage is expected to be matched by more data-intensive real-time applications such as Internet telephony and video conferencing. These two trends will likely lead to a substantial increase in demand, not only for access more generally but also for high-speed access, particularly that provided by broadband technologies. On the supply side, recent technological developments might serve to ameliorate congestion, absent changes in access pricing. Even a simple increase in backbone capacity can help to solve congestion-related problems, although some observers argue that such expansion would actually increase congestion because users, assuming that the Internet can handle even more data-intensive applications and provide higher levels of service, would step up web usage more than they ever would otherwise.25 According to a recent study, “Broadband is ... defined as the ability to receive and transmit information at high rates of speed. The boundary between narrowband and broadband is variously estimated from 128 kbps to more than 2 Mbps". (from: Enabling
the Information Society by Stimulating the Creation of a Broadband Environment in
Europe, Report of RAND Europe to DG Information Society of the European Commission)26. The 6 options to provide broadband to users are: 1. coax cable and cable modems providing Ethernet-like service at 1 - 2 Mbps 2. telephone network and ADSL (Asymmetric Digital Subscriber Line) at download
speeds of 500 kbps to 2 Mbps and upload speeds of 128 kbps. The new ADSL2+ standard will offer (presumably from 2003) download speeds up to 20 Mbps (and hopefully more) and will overcome narrowband interference over long lines (additional information from Jupitermedia Corp. on www.internet.com)
3. 3G digital wireless, promising speeds between 384 kbps and 2 Mbps (see below Section 2.3.6 on UMTS). Prices announced by Hutchison Whampoa in December
24 a recent survey of the different pricing mechanisms which are (or can be) used to regulate Internet access is provided by Wiseman, 2000. See section 2.3.4.3 below. 25 In a basic book on economics of network industries, Oz Shy demonstrates, applying standard utility and welfare maximisation criteria, that individual usage of the Internet increases quadratically with the capacity of the network and decreases with the disutility of a delay parameter (measuring delays or transmission slow-downs caused by congestion). When the Internet is provided free of charge, the network is a overused by a factor equal to the square of the number of users. In theory, micro-economic analysis claims for the adoption of a socially optimally price which increases with the number of users and decreases with capacity, since a higher capacity level reduces congestion (Oz Shy, 2001, pag. 178-179). 26 This study is the source of some of the following material.
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2002 were €630 for a handset and service rentals for voice, video, internet, messages from €95 to €160/month
4. via satellite - which would be available at 500 kbps even in remote locations, but hardly effective
5. via fixed wireless (see below Section 2.3.8 on WiFi) 6. via fiberoptics. Users' choices of actual broadband options depend critically on past choices of technology used for TV service. At this regard, the figure below depicts penetration of digital broadcast systems (DBS) versus cable TV in US, Canada and EU15. 12% - DBS - * F US 10% - * E * * UK - 8% - - 6% - - * I * CAN 4% - - 2% - * N D DK NL - * P * FIN * S * * * B 0% -| | | | | | | | | | * | Cable TV-10 20 30 40 50 60 70 80 90 100% Penetration rates of DBS vs, Cable TV in Europe (2000) Demand for broadband may be driven by need of faster access to conventional Internet services (paid for with a flat rate or with metered access and to a large extent available for free on innumerable sites) or by wish to access video, entertainment and copyrighted material. The latter may be stymied by snags in transfer of small payments or by distrust of credit cards used for payments on line. Improvements in billing processes will improve the situation. The first original driver - still at the forefront of progress - is represented by the requirements of the research community. In 1984 IBM sponsored EARN (European Academic and Research Network) with international leased lines at 64 kbps run on IBM protocols. Research networks implemented in the early Nineties are:
• RARE (Réseaux Associés pour la Recherche Européenne) a 64 kbps network;
• EBONE (European Backbone, 1991) aimed at introducing the IP networking;
• DANTE (Delivery of Advanced Networking Technologies in Europe) a non profit outfit owned by 29 European National Research and Education Networks, managing TEN-155 (Trans European Networks) and GEANT, an interconnection network at Gbps speeds.
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In 1994 RARE and EARN merged into TERENA (Trans European Research and Education Networking Association), which also organises conferences, task forces, pilot projects. Network effects are also a powerful factor. The value of access to a network is more than proportional to the number of users connected to it and sharing the same or compatible standards. Penetration of standards to a very large extent is commercially driven by the largest suppliers. Wintel (Windows/Intel) dominance has the double effect of extracting high prices from users (Microsoft reported gross margins of 86% on their Windows line) and of non protection of their investment due to the forced scrapping of hardware and software in favour of new faster and bulkier solutions, which provide very small advantages with respect to previous (de facto only partially compatible) versions. A portion of the public, supported by other suppliers (IBM, SUN, etc.) are migrating towards open source software. The future of broadband and of the whole ICT sector will depend on the outcome of these conflicts. Another less radical technological alternative (or even complementary option) to provide wider broadband capacity is to employ “caching” technologies. They reduce Internet traffic by aggregating and maintaining content (such an electronic newspaper’s webpage) in a location that is easily accessible to a pool of users, rather than requiring these users to individually seek the content at its original source. But caching can cause other difficulties, in that the content being stored on the local server can easily become out of date or obsolete between the time that it is originally downloaded and it is finally viewed by a user. Thus, the most prominent technological option remains to move towards widespread broadband access. But how to achieve this is problematic. Indeed, it is important to consider the possibilities of market power on the part of both the backbone providers and providers of broadband services. In the case of broadband technologies, their deployment will provide service that is far superior to that of conventional technologies, such as standard copper telephone wire. Those who provide broadband services may be able to extract monopoly rents from consumers by charging more than competitive prices, especially if only a limited number of broadband providers emerge, given the extremely large start-up costs and current still uncertain prospects, causing collusion to become a more likely prospect than competition. Actually it has been argued that the Internet infrastructure is one of the more likely venues for anti-competitive problems (Wiseman, 2000). According to Laurence White (1999) “even if competition is present in most of the components of a network, monopoly in just a single component may be sufficient to capture all the potential rents from the transactions that use that component”. For a parallel situation in the Internet context, consider the current state of interconnection agreements between regional networks and backbone providers. While most backbones currently do not charge for network connection between one another, a fee is usually levied for each connection from backbone to regional networks, and the smaller networks appear to have limited bargaining power in these transactions. Given that the backbone owners arguably possess an essential facility in the conventional sense, several competitive concerns may
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affect the prospects for infrastructure development. As backbone owners begin to provide integrated services, such as acting as an Internet Service Providers (ISP) to end-users, competition may well dwindle because backbone providers could raise interconnection fees so high that they prevent potential competitors for ISP services from entering the market. Although such a scenario may seem plausible, theoretical studies suggest that backbone providers are more likely to engage in some manner of price discrimination to squeeze as much as value as possible from those firms that must rely on their technologies. 27 Anyway, to what extent government can, or should, intervene to regulate market activities is still an unresolved issue. Some argue that, even in the absence of any sort of external co-ordination by non-market forces, monopoly, oligopoly or perfect competition can theoretically produce equally desirable outcomes with respect to technology diffusion. Some others favour letting the government regulate access, especially if some form of dynamic access pricing were to be introduced, to safeguard against manipulation and other anti-competitive practices. In the case of broadband provision, it can be argued that under a variety of assumptions about market structure mandating access to broadband facilities could enhance both consumer and broadband provider welfare. The issue has been recently stressed also in one of the key-note speeches at the IST 2002 Conference of Copenhagen28. Indeed, so far optical fiber has been deployed in the core of the networks (from country to country and city to city) but not in “the last mile” (from town to town, or town to single houses or office). If the access network remain too narrow in one segment – the last mile - then the overall connections will always be very slow. Another argument for installing optical fiber in the last mile to the homes and offices is that it doesn’t cost more than installing the 100-year-old technology, copper wires. In fact, it costs almost the same in absolute terms and far, far less in relative terms as cost per bit. In contrast, with a true broadband network reaching every office and household in the EU, a wider arena of users will have the opportunity to be a front-runner in creating rich content for future internet applications. According to Finn Helmer: “There are ways to make 10G bit/s connections to end-users a reality: up to 80 % of the
capital expenditure required for new network roll-out goes into civil works – basically
to digging up the streets, putting down ducts and cables, and covering the street again.
Does it make sense that a very high-tech industry such as telecoms today spends billions
of dollars to compete in digging? No. And local governments, cities and villages can do
it better and cheaper, and they can do it without distorting competition between
operators. If you de-couple the civil works layer from rest of the telecom service value
chain, you can create a level playing field and conditions for up-grades to fiber optics.
The City of Stockholm has done just this. It has assigned the provision of telecom ducts
and dark fiber to a city owned company. The result? A thriving competition in
27 A formal analysis according to micro-economic criteria of interconnection and market convergence of telecoms and Internet providers is provided in Oz Shy, 2001, pag. 155-159. 28 Finn Helmer, Intel Corporation, “A bright future for Europe through intelligent investments”, Typescript, IST Event 2002, Copenhagen, November 2002
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broadband markets and highest penetration of very high-speed connections in Europe.
So, there are ways to make it happen. And if getting the fiber to the end user turns out to
be not viable, the very last meters can be complemented with Wireless Local Area
Networks. The new WLANs give a very high bandwidth and are a very cost efficient
means to distribute bandwidth.”
Actually, phone companies (now known as ILECs, for Incumbent Local Exchange Carriers) replace 3-4 percent of their copper twisted-pair subscriber lines because of physical deterioration. Their use of fiber for these installations is scarce, so they perpetuate the bottleneck between high-speed communications going on within our computers - and the high-speed networks available for interconnecting those computers. It is debatable whether the slow progress of broadband is due to a lack of compelling applications or to scarcity of users because of inadequate data rates. New services are: video and music on demand, video-conferencing, distance learning, interactive game playing, multimedia Web searches, and unforeseen new services enabled by data rates measured in Gbps. In the US large cable companies are keenly interested to provide voice, video, and data-access service to residential and small business customers. So they are wiring as many homes as possible, first with TV and then with cable-modem service. Then they can easily add telephone service, connecting to the public-switched telephone network via the ILECs' central offices. Then, exploiting the high bandwidth of coaxial cable, they will also provide high-definition television on the shorter links, strengthening their position as the home portal of choice. The reasons for a fast transition to fiber optics are:
• the lifetime costs of the all-glass solution are less than those of any copper-based solution
• fiber optics need not be replaced when more advanced broadband formats and systems become available.
• fiber's low attenuation entails lower-power transmitters and less sensitive receivers, but also more convenient design rules for installation.
• the passive nature of fiber, and the fact that the electronics is only at the ends-means that provisioning and re-provisioning are accomplished much more quickly than with systems embodying electronics along the right of way.
A number of installations have been made in the US of passive optical networks (PONs). These are tree-like networks in which one fiber leaving the central office reaches up to 32 residences by passively splitting the light by a factor of four, and then splitting each of these lines again by a factor of eight as they branch out to individual homes. PONs are then able to provide three services: voice phone lines, Ethernet, and video. On average, the per-residence cost of a PON installation is estimated at $2000 to $2500. That is low enough for providers offering complete triple-play services for as little as $70 to $100 per month with a payback period of 3 to 4 years. 29
29 Ref.: P. E. Green, Paving the Last Mile with Glass, IEEE SPECTRUM, December 2002
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2.2.4.3 – Pricing Access 30
As anticipated above, with the explosive growth in the number of Internet users and the increased use of data-intensive applications, a major concern today is how best to manage Internet traffic in order to ensure high levels of service quality. The most common method currently used to distribute access to the Internet is flat pricing. This was mostly used in the US, and now is adopted also in some European countries. Users pay a flat fee, usually monthly, that allows them to have an unlimited access to the Internet at a particular service level. When the network is not congested, waiting time is negligible, and all information is transmitted instantaneously. When usage is high, however, flat pricing cannot discriminate between users, and all customers are subject to the same degree of delays and loss of service quality. Another, closely related problem is that the flat price does not discriminate between “high” and “low” value applications. As a result, a teenager sending a video stream can plausibly take precedence over a video conference call of a Fortune 500 company. Despite these problems, proponents of flat pricing argue that it is more convenient for both consumers and providers in that it simplifies accounting, encourages use, and provides a guaranteed stream of revenue with which ISPs can recover the high sunk costs associated with developing network infrastructure. Free access is a viable option corresponding to charge the marginal cost of production of access, which is equal to zero because it costs almost nothing to provide access to a user once the infrastructure is developed. However, such a pricing schedule, though indicative of a competitive outcome, would make it impossible to recover the costs expended by developing the network, and hence to induce private parties to take on the significant investments that accompany network development. Several ISPs in the EU countries recently introduced free access thanks to interconnection agreements with telecoms, which transfer a share of the connection fee paid by the users to the telecom company while using Internet to the ISP. A two-parts tariff has been also used in some European countries in the past. According to this scheme, users pay both the traffic to the telecom company and a fixed subscription fee to their ISP. This is the most expensive option, and under the current market competition is going to disappear, or to develop in the subscription of specific value added services (niche markets). Jeffrey MacKie-Mason and Hal Varian proposed a per-packet auction pricing scheme that would vary with the level of congestion on the network. Under this system, the incremental costs of sending a packet would be zero when the network is uncongested, to accurately reflect the social cost of the transaction at that time, while it will be positive if congestion occurs, delaying the packets of other users. Funding for the infrastructure would be covered by a fixed connection fee that would vary from one consumer to another as a function of their relative willingness to pay. Each user would pay a flat fee for connection to the network and then submit a bid with each packet for
30 The review is based on A. E. Wiseman 2000.
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the amount that he would be willing to pay to have that packet transmitted. One drawback of the auction approach is that many individuals might not find the notion of fluctuating prices attractive. Static priority pricing, first proposed by R. Cocchi and others (1993), provides for packets being assigned a priority position whenever placed in a queue because of network congestion. The basic assumption is that users are likely to place different weights on the value of quick access to the network, depending upon what sort of application is being used (e.g. e-mail vs real-time videos). Then, this system establishes different priority classes for the network, as a function of expected delay, and allows users to select the priority class they would prefer for their packets. A priority system must obviously attach some sort of pricing scheme to its different classes in order to induce efficient self-selection into the classes. The mechanism is “static” because the prices for priority classes are not updated every period in response to the level of the network traffic. This is the most serious drawback of the scheme, that could be in theory mitigated adopting a dynamic priority pricing scheme. This operates in discrete time periods, and in each period a user is presented with a menu of options listing the relative prices for different priority classes as a function of delay time or other qualities (prices are positively correlated with delay times in the previous period, which increase with the number of users in the system). Yet another approach in which users sort themselves according to their respective budget constraints is known as the Paris Metro Pricing (PMP) approach. In this scheme, developed by Andrew Odlyzko (1999), the network is partitioned into independent routes and different prices are assigned to access to each route. The system is named after the Paris metro system, which, until the 1980s, contained first- and second-class seats identical in number and quality, but priced differently (first-class seats cost more). This difference in price led to a de facto difference in quality because more people purchased second-class tickets and congestion on second-class cars increased, while first-class cars remained less occupied and hence more comfortable. When this intuition is applied to the Internet environment, the different prices assigned to the routes will not reflect difference in precedence levels across routes or different quality of service guarantees, as in the static priority pricing model. Rather, the difference in transmission costs will lead to expected differences in quality of services on the part of users, and these will be realized as users sort themselves according to their willingness to pay, reducing congestion levels on the higher priced channels. One attractive property of the PMP system is that once developed it is relatively inexpensive to administer. However, from a technical standpoint, current technologies make still very difficult to actually measure the traffic on the Internet, and thus to design efficient partitions. The last theoretical mechanism worth to be mentioned here, that might ameliorate the efficiency concerns surrounding flat pricing, is the expected capacity pricing scheme proposed by David Clark (1997). In this case, all users send their packets on the same network, but before transmission they make contracts with network access points and pay for the amount of excess capacity to be provided. Such contracts can be considered a form of insurance for priority treatment in the case of congestion. Whenever the
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network is uncongested, all packets are treated identically and forwarded between routers. In the event of high traffic and congestion, the excess capacity contracts take effect. Those packets that have contracted for sufficient excess capacity are forwarded, whereas those that have not must wait on the queue, with their position depending on how much capacity they have reserved. All in all, there are various practical and distributive concerns which make the theoretical pricing alternatives to flat-pricing regimes listed above less likely to be implemented, at least in the near future. First, it is not certain that accounting mechanisms can be devised to make some of these options useful and feasible alternatives to flat pricing. Second, even if it becomes possible to implement a given access pricing system, it will have to be tested against each of the others, not just a flat pricing regime, to determine which might prove most efficient under various circumstances. Third, and perhaps more importantly, it seems plausible to suppose that any new congestion pricing mechanism could only be accepted and implemented if consumer demand will become high enough to justify it. For instance, looking nowadays at the experience with car traffic, one notes that even the wealthiest car commuters are hesitant to pay for lower travel times, and by the same token one might also question whether there will ever be sufficient demand for introducing a congestion sensitive pricing system in the Internet environment.31 2.2.4.4. – Governance structure
Apart from the above mentioned needs and prospects for infrastructure enhancement and/or pricing access, possibly another challenge in the future might derive from the lack of centralised authority to govern the Internet. While the infrastructure is continuously developed through a combination of public and private investment, different parts of the network operate more or less independently. So far, the most basic issue requiring co-ordination was the domain name registry. A domain name is the term given to the proper name assigned to the IP address of a web page (e.g. www.seamate.net ). For some years, the system of domain names was administered solely by the Internet Corporation for Assigned Names and Numbers (ICANN). Recently, however, private domain-registration names have emerged. Anyone can apply, directly or indirectly through a registration company, for a domain name from ICANN. The right-hand side of the domain name refers to the top-level domain. The list of generic top-level domains includes commercial enterprises (.com), networks (.net), educational institutions (.edu), non-profit organisations (.org), government (.gov), international organisations (.int), US military organisations (.mil) and, more recently, a television category (.tv). There are also top-level country code domains. The estimated distribution of generic and country specific domains is shown in the figure below (source Internet Domain Survey, Internet Software Consortium http://www.isc.org/ds, January 2001):
31 This argument could be less stringent in a longer term perspective, whenever the current digital divide will be substantially reduced and the demand for Internet services will be diffused all over the planet.
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As the Figure shows, 86% of the generic top-level Internet domains are either “.com” or “.net”. Most of those domains are owned by individuals or firms located in the US, so the share of this country in the country specific domains tends to understate the extent to which United States currently dominates ownership of domain names. Finally, an unsurprising difficulty that has emerged in recent years is that some organisations have similar names or abbreviated names, but each can have only a single domain name. There are also only so many generic terms for activities to which a company or organisation may wish to lay claim via its domain name, that a scarcity of desirable domain names is to be expected.
2.2.5. - Cellular telephones
As the analysis of Internet users later in this Deliverable indicates (cfr. Section 2.4.1), today about 100 million of US residents have access to the Internet. Nearly all of these people go online using personal computers with wired connections to servers – telephone modems, cable modems, and direct service lines (DSLs). A small but rapidly increasing number connect to the Internet via wireless technologies, including satellite and microwave services and cellular phones. Trends and prospects of cellular phone usage in Europe are more favourable than in the US. The following table shows the diffusion of cellular phones in Europe (from: EC-EUROSTAT – Telecommunication indicators in the Eurostat area – Working Group Statistics on Communication and Information Services, February 2001):
Penetration and growth rates are different from country to country. Market saturation levels cannot be computed from the above time series since no acceptable set of Volterra-Lotka equations can be built to fit the data. It appears likely that in general penetration will largely exceed 50% of the population. As briefly illustrated in the following section, much will depend on whether, how far and when substitution of present cellulars by UMTS/3G will take place. The i-DoCoMo version (giving access to Internet) has been a success in Japan, with 30 million users. We anticipate the viewpoint that impacts of portable equipment of this kind will probably represent a fad rather than a significant socio-economic or cultural factor. This does not mean that the fad will be necessarily short lived. It may well continue to flourish - and be a symptom of generalised superficiality, rather than an element of increased social efficiency. The issue is debatable and will be analysed more deeply throughout the SEAMATE work.
2.2.6. - UMTS
Universal Mobile Telecommunication Systems, or 3Gs, have been expected to begin penetration in the market in the third or fourth quarter of 2002 or in 2003 providing users with transmission speeds between 144 and 384 kbps. Strong doubts have been voiced about their adoption. Data transmission to and from mobile terminals does not appear to constitute a mass market. Access to TV programs, real time images from cameras or camcorders, or to Internet may be hardly popular, given the diminutive dimensions of receiver screens as well as the initial fairly high price of handsets (€250 to €750).
1980 1985 1990 1995 1996 1997 1998 1999
Austria 0 10 74 384 599 1160 2293 4206
Belgium 0 0 43 235 478 974 1756 3193
Denmark 0 46 148 822 1317 1444 1931 2629
Finland 23 68 258 1039 1502 2163 2947 3364
France 0 0 283 1303 2463 5817 11210 21434
Germany 0 1 273 3725 5512 8276 13913 23470
Greece 0 0 0 273 532 938 2047 3904
Iceland 0 0 10 31 47 65 91 173
Ireland 0 0 25 158 289 533 946 1655
Italy 0 6 266 3923 6422 11738 20489 30296
Luxembourg 0 0 1 27 45 67 131 209
Netherlands 0 5 79 539 1016 1717 3351 6900
Norway 0 63 197 981 1261 1677 2106 2745
Portugal 0 0 7 341 664 1507 3076 4671
Spain 0 0 55 945 2998 4338 7051 12300
Sweden 0 73 461 2008 2492 3169 4108 5165
Swizerland 0 0 125 447 663 1044 1672 2935
UK 0 50 1114 5736 7248 8841 14878 27185
Total 23 322 3418 22916 35546 55468 93997 156432
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In Japan 3G phones are on the market, but their start is slow, with about 100,000 subscribers. A similar outcome may be expected to obtain in Europe which would spell failure for UMTS, since the growth of a mass market would be imperative given the size of the gamble recently made by large European firms, some of which have been reported to be in dire straits and to regret their huge investments. A plausible estimate indicates that total investment (including licences, infrastructures, implementation) for Europe may exceed 200 G€. Yearly revenue from data/image/Web traffic has been estimated at 8 G€ - one order of magnitude down with respect to revenue from voice traffic. The very size of the amounts paid for licences (see Table below) provides food for thought.
Average amounts paid for licence by each licensee in 12 EU countries and in some Eastern countries and Switzerland are shown in the following diagram, together with average amounts paid per licence and per capita. It is remarkable that the total amounts per capita shown in the last line of the table above (which are more significant than the amounts paid for licence by each licensee
per capita shown in the diagram) started out at extremely high levels in 2000 and decreased markedly in 2001. It appears that the initial levels were belatedly estimated to be non realistic compared to expected yearly revenues. According to EMC (www.emc-database.com ) the 27 countries which have awarded licences up to June 2002 have obtained revenues of about 112 G$.
According to pc-week, GPRS (General Packet Radio Service) should begin to be phased out in 2002, whereas by 2006 one third of mobile phones will be third generation (3G). As noted above, this forecast may well end up to be far from reality. Prof. Hannu Kari from Finland claims that using the 2.4 GHz band, mobile telecommunications access
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may be achieved up to 11 Mbps, although some interference problems could be met (see www.vnunet.com ). Developments of UMTS/3G will have to be reviewed and analysed when they occur. This will happen well within the time limits of SEAMATE activity: Hutchison Whampoa Ltd. have invested 16 G$ to establish a new 3G mobile phone network in Europe. Their plan calls for launching the service in October 2002 in UK and in November 2002 in Italy, expecting to have 100,000 British customers by year end and one million by the end of 2003. This is the first major test of 3G technology in Europe. The outcome will give significant indications of future likely trends in the sector. However it will not be conditioned only by the public acceptance of 3G performance featuring: fast downloads from the net (news, weather, traffic reports, sports scores, stock prices, games), mobile TV access, improved voice service, but also by incidental factors, like Hutchison Whampoa Ltd. finances. Recently they have recorded much reduced profits. Negative factors may be offset, however, by support from China and opening to them of the huge People's Republic market.
2.2.7 - TV access to Internet
A recent study of Jupiter Media Matrix suggests that iTV (interactive cable TV) will represent in the future a major factor in the success of E-commerce. For the moment there are no field data confirming this view, based rather a priori on the concept that TV sets already have reached deep penetration in all European countries and they are allegedly more user friendly than PCs. In 2001 Microsoft seems to have bet on the same assumption as they launched in Portugal jointly with TV Cabo (a local station) a venture to sell goods by means of iTV. The same Jupiter reports acknowledges that for the time being E-commerce sales B2C on Internet have been much more successful than iTV. Cable TV is not very common in Europe. Considerable success has been scored in UK by supermarkets as TESCO (offering also goods from more than 100 shops of all kinds) and SAINBURY's. As in many other instances, development of iTV is too scarce to allow the formulation of any forecast or scenario.
2.2.8 - Wireless Internet - WiFi
WiFi is the name used for the wireless network system for Internet access based on the 802.11b IEEE standard. It allows data rates from 2 to a theoretical maximum of 11 Mb/s by radio connection (in the infrastructure mode in the 2.4 GHz industrial, scientific and medical spectrum) to an access point connected to the 10/100 Mb/s Ethernet cable network. With terminal devices operating at a power of 100mW (USA) or less (Europe) an access point can provide service in a radius of about 50 metres in the open and half that in enclosed spaces. The functions offered are very effective, but they are subjected to loss (on the path and due to multipaths) and to RF interference. Research is carried
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out in order to exploit the 5 GHz frequency band aiming to reach speeds up to 54 Mbp/s. In mid 2002 the largest (reportedly the third largest in the world) WI-Fi access spot provider in Europe is Telia, with 400 points in hotels, convention centres, airports, cafès, in Finland, Sweden, Norway and Denmark. British Telecom has announced in April 2002 their plans to establish 400 access points in Britain by June 2003, growing to 4,000 by 2005. Japanese service providers announce the much more ambitious intention of creating 4 million access points by 2005. South Korea Telecom is in the process of creating 100,000 access points, followed by Hanaro Telecom and SK Telecom. There are high hopes that WiFi will represent a major breakthrough in telematic networking. However interoperability is a major hurdle. It is already certified by Agilent/Silicon Valley Networking Lab, but differences (e.g. in encryption) exist and they may limit future flexibility. A recent hardware development that may favour and hasten the penetration of wireless Internet is represented by gallium nitride (GaN) transistors featuring much increased efficiency and heat resistance together with high speed and high power handling. In December 2002 Intel announced they are going to market their Banias microprocessor equipped with 802.11b early in 2003 and in June 2003 also 802.11a, a faster version. Also in December 2002 the US Department of Defense has invoked limits to WiFi since it could interfere with the operation of military radars. A solution could be recourse to DFS, Dynamic Frequency Selection, which would be more expensive than currently envisaged designs. The issues will be decided in June 2003 at the World Administrative Radio Conference in Geneva. Cognate and accessory advantages may be provided by Bluetooth technology first introduced by Ericsson in 1994, but not yet widely accepted. This is a coded wireless system to connect directly over short distances (10 m) information machines of all kinds. These include: desktops, laptops (Mac and Wintel), palm and pocket PC organisers, cellular phones, printers, headsets and camcorders. Bluetooth connectors are priced above € 100 and are much slower than WiFi. Advantages offered are: elimination of mazes of cables around work stations; ease of transferring files between PCs with no need to go on line or swap diskettes; chatting from one PC to another in a secretive way in the presence of extraneous third parties; avoiding interference from 2.4 GHz cordless phones, by means of automatic frequency hopping. All this appeals probably almost exclusively ICT-geeks. Problems of compatibility and standardisation are to be expected since there are more than 1,000 companies working on Bluetooth products.
2.2.9 – Software and IT services
Software development at all levels and in all sectors is obviously the lymph of ICT. Contents, functions, innovations are so numerous and complex that to even attempt a brief and sketchy review and trend evaluation would be outside the scope of the present
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study. However socio-economic impacts of ICT depend critically on the software and on the instruments and functions available to millions of end users. Some basic highlights concerning the recent evolution of both the software sector and IT services have been provided in EITO 2000. The software sector can be subdivided into the two market segments, system software and user software, both of which enjoy an equally large market volume. The system software on the one hand includes systems-infrastructure software allowing the operation and control of the most diverse hardware platforms in systems. Here the range runs from complex systems-solutions for the management of business enterprises’s IT capacities, through server software such as UNIX, to operating systems such as Microsoft Windows. On the other hand system software also incorporates the various third (e.g. FORTRAN) and fourth generation (4GLs) programming languages. The Internet has become recently a key driver even for system software development, with the evolution of software platforms based on reusable code and intelligent agents in order to allow the intrinsic interoperability of the applications offered by the same or collaborating organisations. Developed in different languages and running on different platforms, middleware is becoming a key infrastructural element. The generic term “middleware” actually refers to a wide range of basic software that offers a solid interface for programming by hiding the specific characteristics of the hardware, the communication protocol stack, the operating system and, in some cases the different programming languages. Besides the traditional languages of COBOL and Fortran, and the more modern C/C++. Java and scripting languages (Javascript, Ecmascript, VBScript etc.), the Extended Mark-up Language (XML) has been confirmed as the emerging language for web applications. This is a language for describing the contents of data structures that constitutes a major evolution of HTML. The importance of XML is due to its widespread acceptance as a generalised method for exchanging information between computer programmes over the Internet. User software refers to software designed for individual functions such as word processing and spreadsheets, which target both the end consumer and the business customer. It also includes complex applications for business management, which as with the programme R/3 from SAP can range from handling of production supply to accounts and personnel management. A recent development in the software sector that can have important implications for future prospects of software suppliers is the so-named “open source” concept, i.e. software programmes that are available free of charge, normally via the Internet. The open source community (http://www.opensource.org/) is highly active in concretely promoting distributed component models for software development that will soon be capable of producing better software than traditionally proprietary and closed models, and its philosophy is not only based on free access to source codes, but also on free redistribution with no discrimination against person, groups or fields of endeavour. More in general, it has been observed that the open source phenomenon will profoundly change the ICT business from a product-oriented to a service-oriented model (EITO,
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2001). In the Internet world, access products such as browsers should be free, whereas the accessed services have to be paid for and can lead to greater business opportunities. Finally, owing to the complexity inherent in the IT industry, the services sector has taken a central role within it. The increasing need to cut costs within business concerns has led to a sharp growth of operations management and co-ordination, rather than execution, thanks to the increasing outsourcing of partial tasks, or even to the complete handing over of IT management to independent firms. The second biggest market in the service sector is system-integration, which denotes the technological implementation of individual IT solutions. As a rule this entails all or some of the following steps: the drawing up of operations and functions, the choice of hardware and software, the programming of individual software applications and the implementation of the system and training. A third area is composed of classical support services such as telephone call centres. In addition to these, a whole range of electronic support services such as Internet providers, web-sites developers etc. have been developed in the last few years. This branch of services perform mainly in combination with technological services such as operations management and system integration.
2.2.10 – World Wide Web and Internet content
The World Wide Web (WWW) is a collection of hyper-linked pages of information distributed over the Internet via a network protocol called HTTP (Hyper Text Transfer Protocol. It was invented in 1989 at CERN laboratories in Geneva, and since then it is constantly growing. The WWW was initially used for text (ASCII) only. Graphics was introduced in the early 1990s after a browser called Mosaic was developed. Both the most commonly used browsers Microsoft’s Internet Explorer and Netscape Navigator are based on Mosaic. But Internet content is considerably more diverse and the volume certainly much larger than commonly understood32. First, though sometimes used synonymously, the WWW (HTTP protocol) is but a subset of Internet content. Other Internet protocols besides the Web include FTP (file transfer protocol), e-mail, news, Telnet and Gopher (the most prominent pre-Web protocols. Second, even within the strict context of the Web examined in this section, most users are aware only of the content presented to them via search engines such as Google, Altavista etc., or search directories as Yahoo! etc. . Eighty-five percent of Web users use search engines to find needed information, but nearly as high percentage cite the inability to find desired information as one of their biggest frustrations, according to some surveys of Web usability (see http://www.gvu.gatech.edu/user_surveys/) .
32 This section is based on the information provided by BrightPlanet Corporation, in the White Paper “The Deep Web: Surfacing Hidden Value”, by Michael K. Bergman. Some information of this document is preliminary, and mainly referred to the situation of the WWW in the year 2000. BrightPlanet plans future revisions as better information and documentation is obtained. Updated versions of the White Paper can be eventually found at the BrightPlanet site.
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But searching on the Internet today can be literally compared to dragging a net across the surface of the ocean. While a great deal can be caught in the net, there is still a wealth of information that is deep, and therefore, missed. The reason is simple: most of the Web’s information is buried far down on dynamically generated sites, and standard search engines never find it. Traditional search engines create their indices by crawling surface Web pages. To be discovered, the page must be static and linked to other pages. Thus, traditional search engines cannot see or retrieve content in the deep Web – those pages do not even exist until they are created dynamically as a result of a specific search. Therefore, a distinction between a “surface” and “deep” Web has to be done, although there is no bright line that separates content sources on the Web. Indeed, there are circumstances where “deep” content can appear on the surface, and, especially with specialised search engines, when “surface” content can appear to be deep. As mentioned above, surface Web content is persistent on static pages discoverable by search engines through crawling, while deep content is only presented dynamically in response to a direct request. However, once directly requested, deep Web content comes associated with a URL, most often containing the database record number, that can be re-used later to obtain the same document. Now, if we do a comprehensive research on a database33, and post the results on our own Web page, other users could click on this URL and get the same information. Importantly, if we had posted this URL on a static Web page, search engine crawlers could also discover it, use it and then index the contents. It is by doing the searches and making the resulting URLs available that deep content can be brought to the surface. The most authoritative studies to date of the size of surface Web34 have come from Lawrence and Giles of the NEC Research Institute in Princeton, NJ. Their analyses are based on what they term the publicly indexable Web. Their first major study, published in Science magazine in 1998, using analysis from December 1997, estimated the total surface Web as 320 million documents. An update to their study employing a different methodology was published in Nature magazine, using analysis from February 1999. This study documented 800 million documents within the publicly indexable Web, with a mean page size of 18,7 kilobytes exclusive of images and HTTP headers. In partnership with Inktomi, NEC updated its page estimates to 1 billion documents in early 2000, and a related content size of 18,700 GBs. This is the baseline figure of the size of the surface Web used in the BrightPlanet White Paper to estimate the size of the deep Web (see section 2.3.10 above). However, since 2000 a more recent study from Cyveillance is now estimating the total surface Web size to be 2,5 billion documents, growing at a rate of 7,5million per day. Other key findings from the NEC studies were:
33 M.K. Bergman to illustrate this point takes the example of a query using one of the best searchable database on the Web, 10Kwizard. 34 see section 2.3.10 of this Deliverable for an explanation of the distinction between “surface” and “deep” Web.
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• surface Web coverage by major search engines has dropped from a maximum of 32% in 1998 to 16% in 1999, with Northern Light showing the largest coverage;
• meta-searching using multiple search engines can improve retrieval by a factor of 3,5 or so, though combined coverage from the major engines dropped to 42% from 1998 to 1999;
• more popular Web documents, that is, those with many link references from other documents, have up to an eight-fold greater chance of being indexed by a search engine than those with no link references.
It is important to understand that, although the boundaries can be sometime fuzzy, the distinction between surface and deep Web is a permanent one, due to the impossibility of complete indexing of deep Web content. Consider how a directed query works: specific requests need to be posed against the searchable database by stringing together individual query terms (and perhaps other filters such as date restrictions). If you do not ask the database specifically what you want, you will not get it. Now, it is infeasible to issue many hundreds of thousands or millions of direct queries to individual deep Web search databases. It is implausible to repeat this process across tens to hundreds of thousand of deep Web sites. And, of course, because content changes and is dynamic, it is impossible to repeat this task on a reasonable update schedule. For these reasons, the predominant share of deep Web content will remain below the surface and can only be discovered within the context of a specific information request. The mentioned distinction between surface and deep Web was growing in importance with the evolution of the World Wide Web itself. In the earliest days of the Web, there were relatively few documents and sites. It was a manageable task to post all documents as static pages. In July 1994, the Lycos search engine went public with a catalogue of 54.000 documents. Sites that were required to manage tens to hundreds of documents could easily do so by posting fixed HTML pages within a static directory structure. However, beginning about 1996, three phenomena took place. First, database technology was introduced to the Internet through such vendors as Bluestone’s Sapphire/Web and later Oracle. Second, the Web become commercialised initially via directories and search engines, but rapidly evolved to include e-commerce. Third, Web servers were adapted to allow dynamic serving of Web pages (for example, Microsoft’s ASP and the Unix PHP technologies). This confluence produced a true database orientation for the Web, particularly for larger sites. It is now accepted practice that large data producers as many international and national statistical sources, not to mention whole new classes of Internet-based companies, choose the Web as their preferred medium for commerce and information transfer. As anticipated above, the BrightPlanet White Paper provides an estimate of the size and other features of the content of the deep Web. The reliability of the methodology used to provide this estimate is difficult to assess35, but the attempt is worth to be considered, being the first trying to investigate a literally unknown land.
35 For the details on the methodology used, see M. K. Bergman, “The Deep Web: Surfacing Hidden Value”
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According to BrightPlanet researchers, the deep Web is about 500 times larger than the surface Web, with, on average, about three times higher quality, based on the documents’ linguistic scoring methods adopted by them (however, also according to these scoring methods, absolute quality remain very poor, because only 12,3% of the documents in the deep Web sample passed the quality thresholds, against 4,7% of the documents in the surface Web sample). Total number of deep Web sites likely exceeds 200.000 today and is growing rapidly. Though individual deep Web sites have tremendous diversity in their number of records, ranging from tens to hundreds of millions (and showing a skewed size distribution, with a mean of 5,43 million records per site and a median of only 4.950 records), these sites are on average much larger than surface sites, achieving a mean database size (HTML-included basis) of 74,4 MB. More than 95% of this deep Web information is publicly available without restriction. The same source provides the following table, showing a somewhat surprising uniform distribution of e-content across several thematic areas:
Deep Web Coverage Agriculture 2,7%
Arts 6,6%
Business 5,9%
Computing/Web 6,9%
Education 4,3%
Employment 4,1%
Engineering 3,1%
Government 3,9%
Health 5,5%
Humanities 13,5%
Law/Politics 3,9%
Lifestyles 4,0%
New, Media 12,2%
People, Companies 4,9%
Recreation, Sports 3,5%
References 4,5%
Science, Math 4,0%
Travel 3,4%
Shopping 3,2%
Finally, the BrightPlanet White Paper, while providing estimates of the deep Web size, is warning about possible double counting. Observations from working with deep Web sources and data suggest that there are important information categories where duplication does exist. Prominent among these are yellow/white pages, genealogical records etc.. Duplication is also rampant on the surface Web. Many sites are mirrored. Popular documents are frequently appropriated by others and posted on their own sites. Common information such as book and product listings, software, press releases, and so forth may turn up multiple times on search engines searches. And, of course, the search engines themselves duplicate much content. On the other hand, there are entire
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categories, especially of deep Web sites, whose content appears uniquely valuable. These mostly fall within the categories of topical databases, publications, and internal site indices – accounting in total for about 80% of deep Web site – and include such sources as scientific databases, library holdings, and unique government data repositories such as statistical databases, satellite imaging data and the like. Considering the above, it is clear that the older model of crawling static Web pages – today’s paradigm for conventional search engines – no longer applies to the evolving information content of the Internet and the growing importance of databases. Clearly, traditional search engines will continue to be used, but a better understanding of their limitations is now coming to the fore. Complementary approaches to enhance data retrieval and information processing on deeper layers of the Web will most probably be developed in the future. Indeed, the surface Webs in the year 2000 contained an estimated 2,5 billion documents, growing at a rate of 7,5 million documents per day36. The largest search engines have done an impressive job in extending their reach, through Web growth itself has exceeded the crawling ability of search engines. Today, the three largest engines in terms of internally reported documents indexed are Google with 1,35 billion documents (500 million available to most searches, see http://www.google.com/) Fast with 575 million documents (see http://www.alltheweb.com/) and Northern Light with 327 million documents (see http://www.northernlight.com/) . But a legitimate criticism has been levied against search engines for their indiscriminate crawls, mostly because they provide too many results. There are also significant overlaps. And, last but not the least, because new documents are found from links within other documents, those documents that are cited are more likely to be indexed than new documents. Actually, search engines obtain their listings in two ways: Authors may submit their own Web pages, or the search engines “crawl” documents by following one hypertext link to another. Crawlers work by recording every hypertext link in every page they index crawling. To overcome the limitations of random search, the most recent generation of search engines (notably Google) have replaced the random link-following approach with directed crawling and indexing based on the popularity of pages. In this approach, documents more frequently cross-referenced than other documents are given priority both for crawling and in the presentation of results. This approach provides superior results when simple queries are issued, but exacerbates the tendency to overlook documents with few links. All in all, the result is that the Web surface is far from being uniform, and it is actually heavily fragmented. On a “plain and open” surface we should reach any point from anywhere with the same effort. On the contrary, starting from any page, we can reach only about 24% of all documents indexed on the surface Web. This estimate is given by Albert-Laszlo Barabasi, author of a book analysing networks constituted by nodes and
36 see http://www.cyveillance.com/web/us/downloads/Sizing_the_Internet.pdf
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links, and used to model road, railways, airports and air routes - linking cities - and telephones, as well as Internet and WWW networks linking individuals, organisations, companies (see: LINKED, by Albert-Laszlo Barabasi, Perseus Publishing, 2002)37. As it is clearly illustrated in this book, this is a consequence of the fact that for various technical reasons the links of the Web are directed, because along a given URL we can travel only in one direction. Directed networks such as the WWW does not form a single homogeneous network. Rather, they are broken into four major continents (see the figure below, reproduced from A.L. Barabasi, pag. 166), each determining different Web’s navigability.
The first of these continents contains about a quarter of all Web pages. Often called the central core, it gives home to all larger web sites from Yahoo! to CNN.com. Its distinguishing feature is that it is easily navigable, since there is a path between any two documents belonging to it. This does not mean that there is a direct link between any two nodes of the central core. Rather, there is a path along nodes belonging to the core that allows you to surf between any two nodes. The second and third continents, called IN and OUT, are just as large as the central core but much harder to navigate. From the pages of the IN continent you can reach the central core, but there are no paths from the core taking you back to IN land. In contrast, the nodes belonging to the OUT continent can be easily reached from the central core, but once you have left the core, there are no links to take you back. The OUT land is populated by corporate Web-sites that can be easily reached from outside; but once you get in, there is no way out. The fourth continent is made of tendrils and disconnected islands, isolated groups of interlinked pages that are unreachable from the central core and do not have links back
37 See infra paragraph 2.3.13.3 and 5.3.2.2 for details.
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to it. Some of these isolated groups can contain thousands of Web documents. About a quarter of all Web documents are located on such islands and tendrils. These four continents significantly limit the Web’s navigability. How far we can get surfing depends on where we start. Taking off from a node belonging to the central core, we can reach all pages belonging to this major continent. No matter how many times we are willing to click, however, about half of the Web will still be invisible to us, since IN land and the isolated islands cannot be reached from the core. If we step out of this core, into the OUT land, we will soon hit a dead end. If we start our journey from a tendril or an isolated island, the Web will appear very tiny because only the other documents on the same island will be reachable. If your Web-page is on an island, the search engines will never discover it, unless you submit your URL address to them. This fragmented structure of the Web is not coming to pass, as long as the links remain directed. The continents are by no means a property peculiar to the World Wide Web. They appear in all directed networks, as for instance a network crucial for our ability to find scientific information: the citation network. Actually all directed networks breakdown into the same four continents. Thus, their existence does not reflect any organising principles particular to the Web. Moreover, topological features of the Web combine with social features and human behaviours, encouraging segregation and social fragmentation of the emerging online universe. Therefore, the four continents are not the only isolated structures of the Web. On a smaller scale, these continents are sprinkled with vibrant villages and metropoli. These are the Web-sites brought together by a joint idea, hobby, or habitat, forming communities of shared interest. Communities are essential components of human social history. Granovetter’s (1973) circles of friends, the elementary building blocks of communities are increasingly recorded in the Web’s topology. A side effect of our digital life is that our beliefs and affiliations are publicly available. Each time we link to a Webpage, we are endorsing its relevance to our intellectual curiosity. Identifying such Web-based communities has tremendous potential for applications (Barabasi, 2002)38. The most prominent example of this potential is perhaps given by the big Internet bookseller Amazon.com. In terms of technological innovation this company has been at the forefront of web site engineering in constructing a scalable infrastructure that can seamlessly handle million of customers a day, as well as developing distribution and logistic systems to fulfil customer orders quickly and reliably. Probably the most visible innovations that Amazon.com customers see are the recommendations system, 1-Click ordering and wish list. For registered customers the Amazon.com web site will attempt to make intelligent recommendations of goods you might like based on what you have purchased and viewed in the past. This innovation is viewed by the company as one of
38 One type of external file commonly downloaded from sellers’ Web servers is known as a “cookie”. This is a small text file recorded in the hard drive of the computer of the visitor to the seller’s site. The seller’s Web server can read information stored on the cookie to “remember” users across the pages of a site. If the visitor does not delete the cookie from the computer’s hard drive, the seller’s Web server can read the cookie during a later connection session and recognise the potential customer as a return visitor to the site.
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its most significant technologies to make online shopping as easy as possible. To build customer trust and loyalty Amazon.com has also been successful in promoting the communal ethos whereby shoppers become actively involved in the company beyond simply spending money. This feature is seen most obviously in the facility to write and post short book reviews on the web site; it has proved to be popular. Also, thousand of customers have signed up for the Associates program, which has been a particularly successful initiative. It is a form of micro-franchising where other web sites list goods such as books and CDs (usually in a specialised niche) which are linked to Amazon.com for purchasing. The owner of the Associate site earns a small commission of between 5 and 15 percent for every sale generated for Amazon.com. The above is just an hint of the Web’s potential for e-commerce applications. Returning to the broader issue of Internet content, however, and beyond the problem of the unavoidable fragmentation of the Web surface mentioned above, it will remain crucially important in the future to enhance the accessibility of deep Web information. Searching must evolve to encompass the complete Web, and directed query technology is the only means to integrate deep and surface Web information. However, client-side tools are not universally acceptable because of the need to download the tool and issue effective queries to it.39 Pre-assembled storehouses for selected content are also possible, but will not be satisfactory for all information requests and needs. Specifical market services are already evolving to partially address these challenges. These will likely need to be supplemented with a persistent query system customisable by the user that would set the queries, search sites, filters, and schedules for repeated queries. Anyway, the crucial challenge in the future will be to match any “supply-side” technology improvement apt to enhance the accessibility to the deep web, with a “demand-side” improvement of users capability to absorb additional amounts of information and elaborate new knowledge. This is a mainly cultural challenge which should be put at the forefront of future IST policies, as it is more extensively sustained in other sections of this Deliverable.
2.2.11 - ITS Intelligent Traffic Systems, traffic control and navigators
Information and Communication Technology provides the theories, the software and the hardware on which are based Intelligent Traffic Systems (ITS). These are constituted typically by Transportation Information Centres (TIC) and Transportation Control Centres (TCC). They have major impacts on mobility, environment and quality of urban life. However the actual positive relevance of these impacts depend on the actual ways in which solutions are implemented, mutually integrated and incorporated in urban planning programs utilising procedures, tools and principles of system engineering. It is common knowledge that even the best designed and implemented ITS systems often fail to provide the positive impacts and the advantages for which they were planned (and which they would be capable of providing) due to lack of integration of
39 Most surveys suggest the majority of users are not familiar or comfortable with Boolean constructs or queries. Also, most studies suggest users issue on average 1,5 keywords per query; even professional information scientist issue 2 or 3 keywords per search.
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overall transportation management, lack of maintenance or inadequate ability in setting up and maintaining the software. Consequently many transportation experts rate ITSs rather lowly as to their actual success in improving the quality of urban life, efficiency, environment. For this reason we will hardly be able to analyse explicitly the possible positive socio-economic impacts of ITS. We reiterate that they will depend critically on the professional and technical levels of operators and city managers as well as on the public's understanding of problems and cultural level. We list below the main function provided by ITSs:
• Traffic Control Centres: urban and interurban traffic monitoring and control
• Information to the users - Multimedial information centres - Organisation of services and info processing - Traffic information, including real time news of congestion in various parts
of the system, preferred routes and modes, navigation advice (also provided by on board units)
- Meteo information - Territory information - Evaluation of travel time - Information on public transport to optimise users' choices
• Special services for goods transport
• Special services for public transport: tele-ticketing to reduce access time, reservation services, dial-a-ride and Polybus (or Buxi) (collective transport on demand on variable routes - also accessible by flagging and from cellular phones)
• Media for information dissemination
• Cellular phones (SMS, WAP, UMTS etc.) also used for automatic traffic counts in real time
• Traffic Message Channel -TMC- through RDS or other media
• Variable Message Sign -VMS-
• Exchange of information between operators
• Radio Communication (iso-frequency network and services)
• Technologies for the collection of information
• Traffic measurements
• Meteorological parameters measurements
• Advanced traffic monitoring systems Besides the above mentioned ITS potential applications, another field where the Internet and especially mobile communications are taking a growing role is in the relation between operators of public or intermediate (demand responsive) local transport and their customers. There are already several examples in Europe (notably in the cities of Bologna and Rome in Italy) of use of call centres for customer services, web-sites providing real time information on service availability, use of SMS to send customised information to the owners of public transport subscriptions, and finally – as in some
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municipalities of Finland – m-ticketing (the use of the mobile phone cards to charge public transport tickets). A major breakthrough in the application of ITS to the efficient management of transport systems can be expected from the implementation of the GALILEO satellite system. Thanks to its accurate positioning function, GALILEO will contribute in many ways to the performance increase of transport systems. Notably: ð GALILEO will provide direct support to traffic management, allowing to optimise
the choice of itinerary in real time, e.g. by flagging in advance the presence of obstacles (adverse weather conditions, accidents, congestion episodes, etc.), thus contributing, in general, to increasing the fluidity of traffic. With respect to the currently existing systems (which in some experimental cases already avail themselves of satellite-based devices), GALILEO will offer a higher level of territorial coverage and, more importantly, a better resolution and accuracy, which will prove particularly useful in urban environments. Altogether, this will yield significant decreases in the average trip length and duration.
ð Specific applications of GALILEO are also expected in the area of road pricing, where the use of the satellite technology for vehicle identification will allow to remove all physical barriers geared to the payment mechanisms (toll booths and similar devices currently required by most payment schemes). The achievement of seamless road tolling systems will further contribute to traffic fluidity and the subsequent reduction of a variety of social costs (travel time, air pollution and other nuisances produced by congested traffic)
ð Furthermore, the implementation of GALILEO will prove useful in the rationalisation of a variety of subsystems, such as e.g. in the management of vehicle fleets (goods distribution, taxis, other public services such as ambulances etc.)
ð Safety and security are also likely to be boosted by the generalised use of GALILEO, which will allow to keep track of vehicle movements in real time, thereby contributing directly to prevent thefts (of consignments, of the vehicles themselves), as well as threats to the safety of individuals.
2.2.12. Health online
As reported below dealing with e-Health promoting policy of the European Commission (see pag. 64), according to the last Eurobarometer survey, in June 2001, 60% of all primary care providers were equipped with an internet connection, compared to 48% in May 2000. In the same period, communication with patients via e-mail has become much more common: the percentage of general practitioners using the internet to communicate with patients rose from 12% to 34%. Existing applications are too numerous to be mentioned: a current updated survey is available in the online magazine www.ehealthinternational.org including: Health education: guides are needed to help the public's orientation in the existing more than 30,000 health oriented websites. E-learning for physicians; telediagnosis;
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telesurgery; prevention of medical errors; patient records systems for epidemiological research - are currently being produced in large quantities. Two critical clusters of problems have been tackled only marginally since they are extremely hard:
• Choice of physician or medical centre. This is a management problem confronting patients and is dependent on local availability of competence and instrumentation, on patients income, on public and welfare services organisation and efficiency.
• Decision making in uncertainty conditions depending on basic patients' culture, knowledge, psychology, tradition and MDs' knowhow.
IST may help to support these tasks by means of directories, databases, guides. At a more basic level, prerequisites to efficient health care are:
• dissemination of biological, medical, nutritional, environmental knowledge;
• refresher and specialisation online courses for MDs and paramedics. Organisational issues are as relevant as medical professional ones: they are analysed and reported on www.hospitalmanagement.net. A large number of study and research contracts are in progress in the IST framework, among which:
• BEPRO - Enabling best practice for oncology
• DIAFOOT - Remote monitoring of diabetic foot
• E-SCOPE - Fully digital microscopy for diagnostics
• IHELP - Electronic remote assistance in Operating Room for neurosurgery
• RESHEN - Regional secure Healthcare networks
• SCREEN TRIAL - Screening Mammography softcopy reading trial Relevant applications have been suggested to establish world wide networks intended to avert major epidemics, the probability of occurrence of which is largely unknown. E. Kilbourne, professor of immunology and microbiology at New York Medical College, Valhalla, has proposed the creation of a world wide net to collect analysis results obtained on suspect influenza patients by using automatic kits in order to centralise the obtained data and carry out early assessment of possible ultra virulent influenza epidemics and make possible mass production of vaccine to avoid outcomes similar to the "Spanish flu" epidemics which killed 20 million patients in 1920. Decisions to participate in this endeavour have been taken by the University of California at Los Angeles, the Los Alamos laboratories, and the Center for the Control of epidemics, CDC in Atlanta as well as some private firms (Genomics, Innova).
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2.2.13. – Assessment of risks
The review of ICT proper technological trends and forecasts cannot be completed without introducing some considerations about the potential risks of systems breakdowns, or those risks possibly created by untimely actions or omissions. 2.2.13.1 - Systemic operational risks
Growth of traditional telephones (POTS - Plain Old Telephone Systems) has slowed down markedly as cellular telephones expanded very fast providing us with instant communication - wherever we happen to be. At the same time asynchronous communication of written material, audio, music, images and TV is now available on the World Wide Web, partly using old telephone networks, partly on fibre optics, but more and more on radio links. The risks of congestion and downgrading, though, have not disappeared. We have now the danger of programming glitches in the software steering the computers controlling the interconnected telecommunications networks. A few years back one of these programming errors blocked for many hours the telephone networks on the US East Coast and caused serious disturbances also to air traffic control. A fault on a telecommunications satellite blocked all the cellular telephones in a fairly wide area. The risk of negative interactions between different technological systems and the risk of congestion will always be with us. The remedy is not to be found in fragmenting the systems, nor in applying the tenet "small is beautiful". The general principle to be applied is that of integration: between adjacent systems, of public and private decisions and plans, between academia and industry, of nations and continents. But there are no simple rules for wide ranging interdisciplinary, international integration. It is an enterprise requiring intelligence and a dramatic upgrading of cultural levels - both of the population at large and of the best experts, planners and designers. In the future congestion may threaten the Internet. In fact satisfactory operation of the WorldWide Web requires the achievement of a complex balance between overall and local demand and supply of service,. This entails that investments and implementations in communication networks (including local distribution, large fast dorsals, Ethernet networks feeding WiFi access points and also service providers hardware) be adequately balanced matching current demand. Co-ordination between public and private decisions in this field is piecemeal and relies on the consultative advice of the Internet Engineering Task Force. So technological risks exist and they are more threatening in some contexts which are ignored by the public at large. Large technological systems are proliferating, without an overall global design, and they impact more and more on each other. Instability and blockage of one system (telematics or energy, say) could cause a gridlock of all systems in the more advanced nations where progress is blueprinted and implemented. Consequences could be dramatic and wide reaching.
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2.2.13.2. - Risks of Untimely Exploiting Available Resources and Occasions
Significant risks are represented by untimely actions or omissions. Among these:
• Investing (betting) on new technologies that are quickly made obsolete by alternative breakthroughs or by failed market acceptance. An example of this is the very heavy investment by European Telecoms and also new competitors in the sector in licences for UMTS and 3G (see previous Section 2.2.5), development and acceptance of which appear now to be in danger. If the investment is made in hardware, write-offs may end up being even heavier than in the previous example.
• Missing potential chances in technology due to fear of events like those described in the previous point, thereby renouncing significant potentially successful innovations
• Procrastination in exploiting networks and their functions in business and cultural applications, entailing braking down further innovation and renouncing the production of added value to other sectors.
It appears very hard, if feasible at all, to forecast future risks of these types. This consideration increases the uncertainty affecting proposed scenarios or models, which have also problems of reliability due to the scarce quantity and quality of data as repeatedly pointed out in the present document. 2.2.13.3 - Internet Topology as a Protection from Cascading Failures
Cascading failures on Internet may be exempt from any hardware component, and consist just of incorrect instructions affecting many configurations of settings or routers at IP's. Similar events may occur because of human error or of premeditated actions of virus originators. This may imply socio-economic adverse consequences of all kinds. This excerpt from LINKED (by A. L. Barabàsi, The 11th Link, p. 154) is relevant : "A few well trained hackers could destroy the net in 30 minutes from anywhere in the
world. There are many ways to accomplish this, from breaking into the computers
running several key routers to launching denial-of-service attacks against the busiest
nodes. "The Code Red worm ... is a good example of a technology that could achieve
just that destruction. ... More sophisticated versions could result in unparalleled
damage. Disabling a few major nodes would nit be sufficient to break the network into
pieces, but the cascading failure of other routers resulting from the redirection of traffic
to smaller nodes would finish the job.
"Most crackers or hackers with the know-how would have no interest in taking the
whole Internet out. A successful attack would take away their favorite toy, denying them
access to the Net as well. So a large scale action taking on the entire Internet would
never be the work of true hackers. But it could easily be the goal of rogue nations and
terrorists. Understanding the Internet topology will help us protect it." Actually, threats to telematic networks may originate with hackers, vandals (producing viruses and extreme congestion with refusal of service) or international terrorists.
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Attacks by anonymous agents are well known to have caused severe damage to tens of thousand and even to millions computers. Carnegie Mellon University's Computer Emergency Response Team's (CERT) Co-ordination Center reported 3,700 attacks in 1998 and more than 50,000 in 2001. As shown in the two graphs on the following page both vulnerabilities and incidents handled are growing fast. These CERT data have been incorporated in the Draft of the National Strategy to Secure Cyberspace (see: www.whitehouse.gov/pcicb/cyberstrategy-draft.pdf) prepared by the Advisory Panel to Assess Domestic Response Capabilities for Terrorism involving Weapons of Mass Destruction, working in the context of the President's Critical Infrastructure Protection Board. The above Draft incorporates provisions and organisational policies to make safer the Web and all the E-activities (including defence and E-government) which rely on it. The co-operation of private parties, citizens and corporations are considered essential for success. One of the suggestions made concerns stricter monitoring of Internet and e-mail by law enforcement agencies. A directive to that affect was recently adopted by the European Parliament, envisaging the operation, by mid-2003, of a Cyber Security Task Force (CSTF – see pag. 69 below). The above US draft contains caveats intended to assure privacy and freedom of speech. However many civil liberties advocates and associations are voicing dissent and considering with suspicion any attempt to monitor the Internet. Many Internet Providers object to the obligation they might be forced to accept of storing for many years all the messages in transit through them. Apart from these debates, we observe that the very task of retrieving messages among the billions being exchanged is a daunting one. This difficulty is also a built-in protection of privacy.
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2.2.14 – ICT policy outlook
2.2.14.1 – General tendencies
Micro-miniaturisation is continuing at a fast rate. Recourse to a wireless web will increase entailing intrusion of computing machinery in our environment, monitoring and managing homes, factories, roads, vehicles. Some authors anticipate that the innumerable networked computing devices will no longer be considered as computers proper. There are already dozens of processors that adjust very many functions in our cars - and we don't think of them as separate decision factors until a malfunction forces us to appreciate how scarce is their transparency and how hard it is to fix them. Attempts are made to insert intelligence both in current software applications and in tools or everyday objects. The risk here is that the intelligence used is often rudimentary, so that attempts to second guess the user are ineffective and irritating. However the trend toward so called ubiquitous computing is getting stronger (or, at least, more talked about). The World Wide Web is supporting more and more of our activities and also establishing remote links between us and our appliances, when we are away. Some examples of innovative ubiquitous processes are mentioned in the following. AOL Time Warner is proposing Gnutella, a program that lets PC users link directly to each other's hard drives through the Internet. The result is a Napster-style free file-sharing without a central database or server that copyright owners can shut down. A computer employing such software uses the Internet to locate other machines running the same program; these machines are connected to even more machines, forming webs that can propagate search requests and files. Gnutella's power to copy and move documents around the network could make it easier to store information wherever disk space is available, for example, and also to avoid censors. Both at CERN in Geneva and at Argonne National Laboratory in Illinois software is being developed to unify supercomputers around the world into a single "grid" assigning parts of computational tasks to facilities that have spare processing capacity. The EC 6th Framework Programme includes GRID computing (with very high bandwidth and quality networks) in its goals for Integrating European Research and Structuring the European Research Area. (see www.eu-datagrid.org ) In the spring of 2002, Intel announced plans to build radio transceivers into all of its silicon chips by 2010. This development could reduce the number of components in - and the cost of - mobile, connected devices. These chips should accelerate the development of portable information appliances-as well as networked sensors and controllers. To be practical, such highly distributed systems will need the ability to diagnose and fix their own bugs and to re-route messages around lost nodes. Major system innovations in progress include:
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• Next Generation Internet (NGI), funded by the US National Science Foundation and DARPA aimed at ultra high bandwidth on demand for national and local networks, dynamically controlled optical networks, multicasting, network management. In 2000 150 sites were connected experimentally to provide an increase in speed of 2 orders of magnitude compared to current levels (see www.ngi.gov ).
• Internet2 (see www.internet2.edu ) a collaboration of 120 US universities with government and industry to develop advanced Internet technologies and applications in support of higher education. Internet2 co-operates with Eurolink Consortium which includes European and Middle East members.
According to Coffman and Odlyzko (IDC, 2001, quoted in Enabling the Information
Society by Stimulating the Creation of a Broadband Environment in Europe, Report of RAND Europe to DG Information Society of the European Commission), backbone capacity should not stymie the developments described here since fibre speed and storage capacity are expected to grow as shown in the following table.
Year Fibre capacity Gbps Worldwide hard disk storage capacity TB
1996 20 147
1997 40 335
1998 40 695
1999 80 1,463
2000 400 3,222
2001 800 7,240
2002 800 15,425
2003 3200 30,340
2004 3200 56,559
2005 4000 126,767
2006 4000 266,211
2007 6400 559,043
The complexity of inter-linked hardware, software, humans and the processes they steer or are involved in is proliferating. We can piously hope that further developments will be well planned and judiciously implemented. However we should not forget that socio-economic impacts of ICT depend critically on the average public cultural level, not only as concerns computer literacy, but also interest, knowledge and abilities conducive to positive impacts (e.g. to increases in overall efficiency due to E-commerce and E-government being widely used). Demand for IT services is not only B2B, to achieve adequate success stakeholders from the general public should also participate competently. 2.2.14.2 – Long-term technology vision: enhancing the Ambient Intelligence Space concept
The IST Advisory Group (ISTAG) has made consistent efforts to get a higher level of focus and a higher pace of development in Europe on ICT. To give these efforts a longer-term perspective a scenario planning exercise was launched during 2000, whose results are now considered to shape long term horizons for technology development in
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Europe. The scenarios were developed by the IPTS (part of the European Commission’s Joint Research Centre) in collaboration with DG Information Society and with the active involvement of 35 experts from across Europe. The aim was to describe what living with “Ambient Intelligence” (AmI) might be like for ordinary people in 201040 Ambient Intelligence Space is defined by the ISTAG as the set of "new policies based on new technologies, integrated and managed so that they span the different spheres of life with seamless operation across various environments". The concept of AmI provides a vision of the Information Society where the emphasis is on greater user-friendliness, more efficient service support, user empowerment, and support for human interactions. People are envisaged to be surrounded by intelligent intuitive interfaces that are embedded in all kind of objects and an environment that is capable of recognising and responding to the presence of different individuals in a seamless, unobtrusive and often invisible way. AmI scenarios are not traditional extrapolations from the present, but offer provocative glimpses of futures that can (but need not) be realised. Each scenario has a script that is used to work out the key developments in technologies, society, economy, and markets necessary to arrive at the scenario. But these specific scenarios should not be read as end-objectives in themselves. They are rather ways to uncover the specific steps and challenges in technology, and qualitative changes and trend breaks that have to be taken into account when anticipating the future. 2.2.14.3 – Enhancing cultural competence as a pre-requisite to knowledge production and society
As stated in the ISTAG Report published in June 2002: Strategic Orientations and
Priorities for IST in FP6, "more is needed than more technology" to satisfy the need for content-oriented tools adequate to guarantee the success of this major endeavour. Here we analyse basic issues, measures and strategies and finally risks and threats implied by this enterprise - not only a new infra-structural paradigm, but also a social and cultural one. The basic issue here is cultural competence - a pre-requisite to upgrading of human values, social stability, generation of added value and hence to prosperity. The downturn in ICT (hopefully temporary) is showing us that the threat of a bottleneck in availability of high-skill labour is not coming to pass. It was already apparent that said bottleneck is less important that the overall cultural inadequacy of the population at large even in the more advanced countries. In 2001 and 2002 claims were frequently voiced to the effect that about 2 million IT jobs in Europe were available, but not filled because of a lack of adequately trained experts. This skills bottleneck was considered as an adverse factor tending to stymie growth of the IST sector. As noted above, it appears that this threat is not coming to pass. In May 2003 guilds were sharply criticising the British government for giving out 21,000 work permits/year to IT workers mostly coming from India. This was considered unfair to out-of-work British experts, 56,000 of which were then unemployed.
40 see http://www.cordis.lu/ist/istag.htm for further information on ISTAG, their recommendations and reports.
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Frequent reports are made available to the effect that tens of millions of citizens are functionally illiterate. These bad news are reported mostly by the American press. In the US the National Science Foundation carries out periodically surveys of the public understanding of science and other institutions try to gauge cultural literacy. In many European countries this type of research is just budding. It is to be expected that sad news will be generated as and when local situations are objectively analysed. Functional illiterates, then, are defined as unable to perform even simple tasks required to perform in to-day's society - and even less to carry out telematic procedures. The European Computer Driving Licence (ECDL) level is achieved by a very minor portion of the population, especially in Southern Europe. Certainly, young citizens should be trained to acquire advanced skills. However progress towards the Information Society will continue to be stymied, if the average level of culture is not upgraded markedly. So the whole argument of the digital divide (early adopters vs. laggards) should be seen in a different perspective. Problems and inequalities suffered by the elderly, women, residents in remote areas, disabled people indeed exist and should be remedied, but their societal/national impacts are lighter than those of entire nations being laggard and/or failing to fulfil their potential. The situations of EU15 - leader (Finland, Ireland, Sweden, UK) and laggard (Italy, Greece, Portugal) countries have been analysed in the SEAMATE study. There is a major digital-divide between Countries which has cultural and socio-economic causes and which affects young urban professionals, who are relegated below the digital-divide threshold particularly in Southern European nations. The real division is between people who are able to produce added value in large amounts and people who are not. Which tools are used is to a large extent irrelevant. Certainly modern ICT tools are effective for processing, amplifying, generating knowledge needed to produce value added in any sector: manufacturing, agriculture, arts, teaching/learning, health, science. However traditional tools should not be forgotten. They are the only ones available to many - and they have been ignored or misused to a tragic extent. Hard lessons are to be learned from the sorry state of most TV stations public and private, of many newspapers and periodicals and of the many schools where attempts are made to measure the quality of learning (exams), but not the quality of teaching. 2.2.14.4 - Measures and Strategies to implement the Ambient Intelligence Space
Some recommendations (2 and 6) in the June 2002 ISTAG Report suggest that industry leaders and also emerging SMEs be engaged to co-operate across the European Research Area to realise virtual enterprises and so contribute to implement the Ambient Intelligence. It appears necessary to enrol the help also of professional communicators, experts in languages and media, artists. They should be assigned the task of tailoring messages and overall communication to the special characteristics of the groups to be addressed. Both utilitarian real time information and more general knowledge will have to be expressed at a number of different levels and in different formats in order to be understandable by widely varying addressees. As aptly described in the ISTAG February 2001 Report Scenarios for Ambient
Intelligence in 2010, a large amount of chores can be avoided or made lighter by
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facilitating the acquisition of information on natural and artificial environments, transportation, the expression of one's identity or standard responses. The ultimate goal of Ambient Intelligence Space will be much wider encompassing not just the elimination of chores, but carrying out a major socio-cultural task, the need of which was illustrated above. This task is unprecedented. It will be necessary to recur to total quality management applied to the generation and dissemination of cultural products and to the assessment and validation of contents. Dissemination of information/knowledge is a practical task: its obvious prerequisite is the invention/generation of contents. A case in point is given by the naive attempts to provide intelligent supports to word processing: often the syntactic or grammatical suggestions or the attempts at second guessing the user are just ludicrous, not intelligent. It may well be appropriate to derive inspiration from the modus operandi of peers' review, so successful in science. Contents and formats should be revised by referees possibly organised in telematic networks. It would be very dangerous to assume that knowledge and/or intelligence can be univocally defined in every instance and readily transferred to the public. Debate and controversy are vital ingredients of cultural progress and sanity. "Bio-diversity" of theories, schools, disciplines, trends must be preserved - pruning out degraded pseudo-cultures. A major endeavour as AmI must recur to a wide societal call to arms. 2.2.14.5 – Threats and risks
Ambient Intelligent Space is rightly described by ISTAG as "not to be designed, requiring a coherent development across a broad community". The key word here is "coherent" - a feature that can be achieved only recurring to total quality management, not only with cross fertilisation, but also with cross assessment of approaches and results. Otherwise the risk is run of unchecked proliferation, conducive to the creation of vulnerable or ineffective networks. A correct balance between complexity needed to create a huge complex structure as AmI and robust simplicity needed to provide resilience cannot be defined in a concise way. Massive recourse to high quality systems engineering is called for - again requiring total quality management. Other risks that can be imagined (but the list is certainly not exhaustive) are:
• Illusory solutions- technology based, but lacking substance
• Forced standards imposed by suppliers (icons, proprietary S/W)
• Delegate processing to nameless centres without spurring end users to understand/reformulate problems statements and solutions
• Equate (wrongly) cyberworlds with real world
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2.2.15 – A preliminary screening of IST data and trends data: first conclusions
In the previous sections of Chapter 2 we have considered data and policy prospects of ICT proper, looking mainly at technological trends from the supply side. In addition, a parallel screening of data concerning the use of these technologies and wider aspects of the Information Society has been performed, to check the availability and reliability of IST data in full. This work was: • preliminary to the deeper analysis undertaken in WP2 of IST business impacts and
in WP3 of IST social impacts, and • provided a factual as well as a conceptual basis for building first generation IST
scenarios that are presented in Chapter 4. The results of the preliminary screening are shown in Annex I. The screening covers: ü Internet users and hosts ü ICT employment and revenue figures ü E-commerce ü E-business ü Mobile commerce ü E-work ü E-training ü Literacy, Education, E-learning ü GDP, employment, productivity, ICT investment and market value ü Innovation ü ICT situation and impacts in Acceding and Accession Countries (AAC13)
Some of the tentative conclusions that can be drawn from the data considered appear to be obvious. UK and Germany are at the top as regards the portion of the workforce attaining upper secondary education and they are at the top of E-commerce use by end customers and companies. The reverse is true for Greece and Portugal. This seems to indicate the existence of a general underlying factor which we are tempted to identify simply in the GDP per capita. It is reasonable to surmise, though, that there are here multiple feedback loops involving:
• wealth
• investment in R&D and in education
• education
• competence in use of ICT tools
• use of telematic networks (E-commerce, etc.) The levels of activity which are the consequence of wealth and education appear to be self perpetuating. In this sense we may feel that a final conclusion is already looming in the future, waiting to be more aptly defined. It can be worded as follows:
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Investment in the ICT sector and adoption of its modern tools are not per se
adequate prerequisites to obtain positive socio-economic impacts. A nation's
shift towards ICT requires in turn boosting investment in R&D and in
education - which can be done if adequate resources are available. We may
want to argue that a positive win-win operation of the loop can be obtained by
starting out to prime the education factor. Investment here is rewarded by the
high gain inherent in this section of the causal chain.
A specific evidence supporting this statement comes from Finland’s recent growth patterns, reported in the table below:
Table 4: Percentage point output growth (business sector) 1995-1999
Finland France Germany Italy Japan UK USA
growth of output 5.62 2.6 1.73 1.93 1.1 3.48 4.43
growth due to ICT investment
.62 .33 .35 .36 .38 .47 .86
growth due to total invest.in capital services
.57 .82 .95 1.01 1.07 1.23 1.69
ICT/total 1.09 .38 .36 .36 .36 .38 .5
from: Colecchia & Schreyer, ICT Investment and Economic Growth in the 1990s, STI
Working Papers 2001/7, OECD, Paris In Finland the growth of output is more than double the average for other European countries. This corresponds to a ratio of ICT growth to total capital services growth which is about 3 times as large as the average for other EU15 countries and double the US level. This result is confirmed by the following table showing Average Labour Productivity (ALP) in the 4 sectors in which ICT may be disaggregated (from European Central Bank Working Paper N°122 "New Technologies and Productivity Growth in the Euro Area", by F. Vijselaar and R. Albers, February 2002).
Table 5: Average % Labour Productivity growth 1995-98
ICT using sectors, manufacturing 4.5 3.1 2.5 1.3 1
ICT using.sectors, services 3 -1.6 1.7 -0.8 0.1
Total 38.2 34.2 28.1 3.6 7.5
The Finnish Prescription - stressing investment in ICT related R&D - is suggested then as the core content for defining positive prescriptive scenarios. Note that Finland has 32 Polytechnics and 20 Universities with a population of only 5.1 million. The following table compares the ratio Tangible/Intangibles for some European countries, Japan and USA as reported in "New Indicators for the Knowledge Based Economy". It is interesting to note that the T/I ratio (which is lower when intangible IST
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activity increases) is lower than in Finland only in UK and USA. However the trend in the right direction is about twice as fast in Finland compared to all other countries.
Table 6: Ratio of tangibles/intangibles
Finland France Germany Italy Japan UK USA
1985 T/I ratio 9 6 5 12 7 4 4
1997 T/I ratio 4 4 5 9 6 3 3
1985/1997 2.25 1.5 1 1.33 1.16 1.33 1.33
from www.researchineurope.org/newkind Univ of Sussex, OST Paris, MERIT Infonomics The case history of Finland rightly deserves to be called, as above, the "Finnish Prescription". The cause-effect relationship between number of students (obviously of high proficiency) especially in polytechnics as well as in open universities and continued education is shown by the following table and graph depicting growth of GDP and employment. The fact that GDP growth in 2001 was only .7 % is not to be represented as an anticlimax, but as the consequence of a well known worldwide slowdown especially in ICT. In particular, the diagram shows that, after the crisis of 1990-92 (due to various causes, among which the demise of the former USSR) GDP growth from 1993 to 2000 has been of 40%. From the low point in 1994 to 2001, employment grew 15% . Unemployment is still sizeable, which entails that further growth is in the cards, spurred by appropriate policies in R&D and education. Table 7: Number of students (000's) at Finnish higher education institutes and %
GDP yearly growth
Year Polytechnics Universities Open universities
Continuing education
GDP yearly % increase
1991 115 43 62
1992 7 122 50 71
1993 14 126 60 78 - 1
1994 24 128 68 96 + 4
1995 31 135 75 98 + 3.8
1996 45 138 75 109 + 4
1997 64 143 74 123 + 6.2
1998 + 5.2
1999 + 4.1
2000 + 5.5
2001 + .7
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Three quarters of the industry operates on the networks, which entails a trend towards strategic partnerships and marked increases in productivity. Science parks hosting technology centres connected with universities, corporate incubators and business accelerators have been in operation in the last decade at Innopolis and at Otaniemi in Espoo. The latter employs 8,000 professionals and trains 14,000 students. More than 100 companies are taking part in these developments fostering scientific know-how transfers and consulting services. Employment of professional and skilled labour is increasing. New jobs created in 2002 are 70,000 (up 60% from 2001). Repeated application of the Finnish prescription appears to be effective. Key findings of the recent European Commission Innovation Scoreboard and OECD Science, Technology and Industry Scoreboard (see Annex I) provide support to the above arguments, showing that the current slowdown of growth in Europe is accompanied (and we are tempted to say that it is caused) by a slowdown in innovation activities, especially notable in some countries. These key findings may be listed as follows: • Europe's growth in production of scientific publications is slowing down: numbers
are rising, but EU15 share of world publications is declining. • The number of valuable patents (valid also in US and Japan) is lower than in these 2
countries - especially in biotechnology and ICT. • % share in world hitech exports has gown in the last e years by 2 percent points.
Consideration of the slack in needed prerequisites indicates that this improvement will be short lived.
• Innovation indexes and in knowledge investment are increasingly lagging in EU15 with respect to US. There are large disparities among EU countries, as depicted in the following diagram (European Innovation Scoreboard 2003 Source), which includes also new accession countries.
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Here ordinates plot Innovation trend indicators levels and abscissae their % growth. The field is subdivided in 4 quadrants for: Losing momentum vs. Moving ahead and Falling further behind vs. Catching up. It is apparent that some Southern European countries are catching up energetically - notably Portugal, Greece, Spain. Also catching up are a number of Accession Countries. At the top of the pack we still find USA, Finland, Japan, Sweden. The Losing Momentum & Falling further behind quadrant Italy is the only EU15 country - and it should be termed "Europe's Sick Man" - together with Bulgaria. The above analysis is the basis for the choice and description of scenarios in Part 4 of this deliverable. The most recent data acquired indicate that the Negative Scenario presented thereof is to be considered the most likely.
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3. Measuring impacts on growth of European Union 3.1. The growth accounting approach According to the so named “growth accounting approach”, per capita GDP growth of a nation over a time period can be decomposed into single components or “determinants”, as it is shown in the table below. Following this approach, we will summarise the fairly numerous attempts to explain the total GDP growth through the growth of the single components – productivity, average working time, employment rate, labour force participation rate and size of the working age population – and the influence of specific explanatory factors (which can be named “enablers, “prerequisites” or “drivers” of growth). Real GDP per capita
Determinants æ
GDP/H Hourly
productivity
æ
H/L Average
working time
æ
L/LF Employment
rate
æ
LF/WAP Labour force participation
rate
æ
WAP/POP Percentage of working age population
Enablers/ Prerequisites/ Drivers
æ
ICT investment ICT prices ICT use R&D intensity Educational attainment Migratory flows of researchers/high skilled workers
æ
Firms by size Flexible time
æ
Skill levels Training
æ
Female participation rate
æ
Natural dynamic Migratory flows
Impacts to assess
æ
PRODUCTIVITY æ
IMPACTS OF INFORMATION TECHNOLOGY
æ
LABOUR UTILISATION æ
IMPACTS OF INFORMATION SOCIETY
The determinants and drivers of growth in the table are grouped into two broad categories:
• change in labour utilisation, which includes the four components – the ratio of persons of working-age (15-64 years) to the total population, the ratio of those in the labour force to the working-age population, the ratio of those employed to the labour force, and finally the number of working hours per person employed – whose
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aggregate change ultimately determines the total quantity of working time available to the nation;
• change in productivity, measured at the aggregate level in terms of GDP per hour worked (the fifth component of the growth accounting formula), and dependent from the specific productivity of labour and capital inputs, as well as from the overall efficiency with which labour and capital are used, the so named “multi-factor productivity” (MFP) or “total factor productivity” (TFP).
On one hand, labour utilisation is surely an important component of the GDP growth. Labour utilisation rates have strongly contributed to the economic growth both in Europe and United States. Recent estimates for 1998 indicate that the lower labour utilisation rate in Europe accounted for two thirds of the gap with the US level of per capita GDP41. Several reasons, other than cultural factors, i.e. women’s employment rates, can be identified behind the different labour utilisation rates across OECD countries. In particular, Information Society trends, as for example change of life-style, mix of working and leisure time, participation of knowledge workers in the workforce and extension of the working age limits, population ageing etc. as well as labour market or immigration policies usually have a more direct effect on labour utilisation than on labour productivity. Some of these trends and impacts are addressed in other SEAMATE work-packages (WP2 and WP3). On the other hand, also the estimated impacts of labour productivity on economic growth for OECD countries have been significant, on average more than 60% over the period 1990-98, as shown in the following table42:
GDP Contributions GDP Incidence of
per capita from labour utilisation Per hours worked labour productivity
USA 2.1 0.6 1.5 71.4%
UK 1.8 -0.1 1.9 95.0%
The Netherlands 2.1 0.3 1.8 85.7%
Ireland 5.5 1.7 3.8 69.1%
Sweden 0.8 -0.9 1.7 65.4%
Denmark 2.1 -0.2 2.3 92.0%
Germany 1.0 -1.5 2.5 62.5%
Belgium 1.7 -0.5 2.2 81.5%
Finland 1.3 -1.6 2.9 64.4%
Portugal 2.4 0.2 2.2 91.7%
France 1.1 -0.7 1.8 72.0%
Spain 2.2 0.4 1.8 81.8%
Greece 1.1 0.2 0.9 81.8%
Italy 1.2 -0.8 2.0 71.4%
Therefore, a significant part of GDP growth must be explained from an increase in productivity, and in the following paragraphs we will concentrate our analysis on the contribution of Information Technology to productivity. However, the above table
41 The EU Economy review 2000, chapter 3, page 98 42 Based on OECD Scarpetta et al. “Economic growth in the OECD area: recent trends at the aggregate and sectoral level”, 2000, page 15
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shows also that in some countries, e.g. Italy, France, Germany, Sweden, Finland, Denmark, despite the productivity growth rates per hours worked higher than in the USA, lower employment rates, fewer hours worked and in general negative labour utilisation rates decreased the GDP per capita growth rates. 3.2. Limits of the growth accounting approach The simplified scheme of linear relationships proposed by the growth accounting approach is far from being perfect. Firstly, it doesn’t take into account non linear relationships and feedback loops between variables that clearly exist, and in some cases are important (as for example retroaction of diffusion of ICT products and services on ICT skills of human resources, or the interaction between ICT and innovation). But, more importantly, it suffers of some serious conceptual drawbacks, which limit the ability of the approach to explain the growth of national economies. These limits are twofold: 1. the growth accounting framework looks mainly at supply side factors influencing
productivity and growth (labour productivity and utilisation, working age population etc.), while important demand side factors which may cause structural shifts of business and household consumption patterns are ignored;
2. more seriously, the framework fails to consider appropriately technology and the
influence of innovation on growth, especially of services. The second is the well known issue of whether, or to what extent, ICT usage raises productivity in sectors outside the ICT-producing sectors. In fact, most of the computer investment is concentrated in sectors where output is least well measured or even the concept of output is not well defined, for instance in financial services (not to say increasingly important public services and government activities). As these service sectors have substituted ICT equipment capital for labour, and given the measurement procedure, the incorrect measure of output combined with maintaining or increasing the use of inputs results even in apparent productivity declines. However, it is even difficult to fully estimate the impact of this problematic issue on the final computation of GDP growth. For instance, Triplett (1999), argues that most of the computer using services do not show up in aggregate statistics because they are intermediaries. Business services do not constitute a problem for aggregate productivity measurement because any error is netted out in the aggregate GDP measure. So, even if there is a measurement problem it is only the fraction of services which is included in private consumption that constitutes a problem (together with the long standing problem of measuring the real value for money of government services, which are no less important than private consumption as far as they concern important aspects of the citizens’ well being and wealth of a nation). Anyway, the issue of how to measure and then to explain productivity at the aggregate level has been very controversial since the beginning – with the work of Tinbergen and
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others in the 1940s – and continue to cause problems.43 The term “residual” to indicate the share of productivity left over when the growth of measured capital and labour inputs are factored out has become standard in the lexicon of economists. The term is especially apt for several reasons. It describes how productivity analysis was often done, especially in the 1940s and 1950s, ascribing any leftover or residual growth in measured output growth that cannot be explained by growth in measured inputs to changes in productivity. It serves as a reminder of a common finding of research on productivity – that the unexplained, residual element has been substantial in many studies and for many time periods. And, finally, it conveys the main challenge still unresolved of productivity research, which is to seek an economic explanation for this residual and how it has changed over time. Recently, the term “residual” has been substituted with “total factor” or “multi-factor” productivity, in the attempt to give it a more positive substance. But we should refrain from purely nominal changes, as far as the substance of the residual term is left unchanged. Obviously, we cannot hope to solve here long standing and significant controversies which exist also in the very definitions of variables and factors of productivity research, but because we will make use in the following widely accepted definitions and generalisations we think necessary to cite briefly the contrasting views and consequent caveats. For some authors44 multifactor productivity (MFP) "cannot be measured directly and is
difficult to estimate in practice". This uncertainty in definition is reflected in diverging assessments of connected factors. For example in the reference45 a Table is given of R&D as a factor strongly correlated to MFP according to different sources:
Source Period R&D domestic R&D int'national
Coe &Helpman 1971-90 .08 - .1 .06 -.09 Engelbrecht 1971-85 .06 - .08 .06 - .09 DG EC FIN 1973-97 0.11 0.08 Variations go from 50% to 80% indicating that measures and estimates are unreliable. Actually the periods considered overlap only partially, but the variations in TFP ranges are so strong that they cannot be attributed to this discrepancy. It is outside the scope of SEAMATE to provide a composition/solution of existing differences between various scholars and practitioners. However, problematic issues have to be highlighted to clarify the underpinnings of the work. It is to be hoped that co-operative efforts in this direction may also contribute to a wider discussion and clarification of critical issues. In order to stimulate such a discussion, we reproduce in the box below the conclusions of the Zvi Griliches retrospective on productivity research46.
43 a recent account of this issue has been provided in Z. Griliches, 2000 44 see European Central Bank Working Paper N°122 "New Technologies and Productivity Growth in the Euro Area", by F. Vijselaar and R. Albers, February 2002 45 EC “The EU Economy review 2000”, European Economy n° 71, pag.104 46 Z. Griliches, 2000, pag. 87-90
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Reminders for travelling the productivity research road ahead
The following are “few obvious statements that sometimes get lost in our rush towards
modelling” by Z. Griliches: 1. productivity growth is not technical change, and vice versa. Productivity is also affected by
the efficiency with which existing industrial enterprises and other social institutions are operating. It changes as the result of changes in capacity utilisation, scale, organisation, learning by doing and more. Technical change is a change in how things are done, primarily as the result of changes in equipment, materials, and methods of operation. One can think of it as both the appearance of new blueprints and formulas (a shift in the production possibilities frontier) and the spread of the actual new products and processes that embody them. The latter, the diffusion of the best available techniques, has received too little attention in the literature. Also, technical change need not imply a growth in productivity per se.
2. R&D is not the source of all productivity growth. Besides basic science, which does not fit
the purposeful R&D mold, many productivity advances come from learning on the job and from informal attempts to improve production and distribution processes by the participants in them. Such “informal R&D” may be an important source of improvement, but we have relatively little systematic evidence about it or understanding of how best to promote it. It may be that informal R&D is correlated with private, formal R&D activity and thus captured by our focus on the latter, but we cannot be sure until we have useful measures of those informal activities.
3. Knowledge is not a free good. It takes effort to develop it, to transfer it, and to absorb it.
One of the major components of any research effort is re-search, trying to find out what is already known about some of the components of one’s problem. Moreover, much of the available knowledge is highly technical and cannot be absorbed without specific and intensive training, and even more of it is tacit and not easily communicated even by the one who knows it. In this sense, models that treat all knowledge as both freely applicable and transferable everywhere are wildly optimistic.
4. Neither the world, nor the economy, nor the individuals in it are in continuous equilibrium.
The opposite is the normal state. Individuals continually strive to change the situation around them, either because they are dissatisfied with it, because they think that they see opportunities for improving it, or out of boredom. But this unease (…) is a major source of the changes around us. Moreover, nobody knows everything, and therein lies the source of both inefficiencies and opportunities. “Any approach … which in effect starts from the assumption that people’s knowledge corresponds with the objective facts of the situation, systematically leaves out what is our main task to explain”.47 The study of growth will require embracing more seriously a view of the economy where decentralised information and incentives in a constantly evolving world make all the difference. But progress will lie in merging those general insights with useful theory, careful measurement, and serious econometric work.
47 Hayek, F. A. 1945. “The Use of Knowledge in Society”. American Economic Review. 35(4): 519-530, page 530.
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5. Accounting is not explanation. We can take a productivity growth calculation and allocate it in great detail to the various missed components, reducing thereby the role of the “unallocated” residual. But this, while very instructive and valuable, only shifts the problem to a new set of questions: Why was there all this investment in human capital ? Will it continue ? Where did the improvements in capital equipment come from ? What affects the rate of capital utilisation and the institutions within which both production and invention are pursued ? … Real explanations will come from understanding the sources of scientific and technological advances and from identifying the incentives and circumstances that brought them about and that facilitated their implementation and diffusion. Explanation must come from comprehending the historical detail from finding ways of generalising (modelling ?) the patterns that may be discernible in the welter in it. This lead us back to the study of the history of science and technology and the diffusion of their products, a topic that we (the economists) have left largely to others.
6. Increases in total factor productivity are not synonymous with increase in social welfare. Most reasonable measures of social welfare pay some attention to the distribution of income and wealth. Changes in TFP can go hand in hand with increases in measured equality (as seemed to occur in the 1950s) or increases in measured inequality (as in the 1980s). The relation between productivity and welfare will depend on the underlying economic forces shaping productivity growth as well as on public policies towards distribution.
3.3. Comparison of GDP trends The past decade witnessed a remarkable difference in economic performance between the EU and the USA, and among the EU countries themselves. With an average annual growth rate of 2 per cent in the 1990s, the pace of growth was moderate in the EU and accelerated to a range of 3 – 3,5 only at the very end of the decade. In contrast, in the USA real GDP grew on average by 3,2 per cent per annum over the last decade and by 4,5% per cent between 1996 and 2000. The uneven growth rates experienced in OECD countries over the past ten years have raised growing interests and studies concerning factors affecting economic growth48. A comprehensive analysis focusing over long-term trends in growth rates of GDP and GDP per capita shows, on one hand, a broadly common pattern: dramatic slowdowns in coincidence with the two world wars, and then rapidly increasing trends after the 50s followed by relatively constant trends during the 70s and 80s. On the other hand, different growth trends among OECD countries can be observed in particular during the 90s for three groups of countries49:
1. United States, Denmark, Finland, Norway, the Netherlands and UK, with increasing growth trends:
48 Inter alia, it has to be mentioned the OECD extensive monitoring and analysis of economic growth under the Growth Project. 49 The figures show the growth rate of GDP per capita (left axis, dark line) and the growth rate of GDP (right axis, light line), estimated through the Kalman filter. Bart Verspagen, “Economic growth and technological change: an evolutionary interpretation”, OECD Working Papers, 2001.
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2. Germany, Italy, Switzerland and Japan, that seem to experience decreasing
growth trends;
3. Spain, France, Belgium, Austria and Sweden, with stable growth levels.
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Over the past 10 years, considering growth rates adjusted for differences in the business cycle, only four countries registered markedly stronger growth rates of GDP per capita compared to the 80s: United States, Australia, Netherlands and Ireland50.
Moreover, over the past ten years disparities in trend GDP per capita growth rates within the European Union have doubled51. 3.4 Contribution of ICT to growth As anticipated above (cfr. par. 3.1.), the reasons behind the improved performances of particular countries during the 90s rely on a complex set of factors, involving labour utilisation rate, i.e. persons employed to the total of population, rate of investment and overall efficiency of labour and capital, or multifactor productivity (MFP). In some case the high performance attained for one single factor does not represent a condition for a stable growth, as for France, Italy and Belgium cases, having high productivity levels associated with low levels in the labour utilisation rates52. The ICT sectors, i.e. computers, computers software and telecommunications, contribute to the above growth-driver factors in several ways (EU, 2000):
50 OECD, “Science, Technology and Industry Outlook. Drivers of growth: information, technology, innovation and entrepreneurship”. 2001, page 11 51 OECD Scarpetta et al. “Economic growth in the OECD area: recent trends at the aggregate and sectoral level”, 2000, pag.13 52 OECD, “The new economy beyond the hype”, 2001, page 18
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• A first channel is the avenue of ICT capital accumulation. Investment in ICT boosts an economy’s productive potential because it raises the stock of capital. When integrated into a growth-accounting exercise, additional investment in ICT would show up in capital deepening, thus contributing to higher labour productivity even if the MFP growth remains constant.
• A second channel focuses on the rapid technical progress currently occurring in the production of ICT goods, as illustrated by Moore’s law, and its influences on MFP as well as on the demand for new products and employment in the ICT sector. The magnitude will depend on both the speed of technical progress and the share of the ICT sector in the overall production.
• A third channel relates to the possible externalities (either embodiment effects or economy-wide network externalities) as the usage of ICT increases productivity in business’ outside the ICT sector. This effect should become visible in higher MFP growth outside the ICT sector itself.
3.4.1 ICT Employment
The ICT sector has played a significant role in fostering a major employment growth. During the past years, despite the ongoing capital-substitution process, the job creation in the ICT sectors has been playing a growing role in the overall net increase of employment. In the period 1992-1999, it has been calculated that the strongest employment growth in OECD countries concerned either high technology or ICT-related sectors53. The so called “knowledge workers” (scientists, engineers, ICT specialists and technicians) grew by 3.3% annual rate, compared to 2.2% of “service workers”, 1.6% of “management workers”, 0.9 of “data workers” and the negative trend of –0.2% of “goods-producing” workers. The following figure shows the relationship between employment rate in 2001 and ICT expenditure as % of GDP, 1992-199954 for a sample of OECD countries. It can be observed that higher utilisation rates are associated with countries where ICT expenditure share has been higher (correlation coefficient 0.8).
53 OECD, “The new economy beyond the hype”, 2001, page 56, and COM (2001) 711 final, “The impact of the E-Economy on European enterprises: economic analysis and policy implications” 54 ICT expenditure rates measures the diffusion of computer hardware, communication equipment and telecommunication services, including expenditures by business, household and government sector. It has to be mentioned that for Europe no official data are available, but figures are collected from surveys by private sources, i.e. IDC.
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3.4.2 ICT price trends
Declining prices for semiconductors and ICT capital, e.g. computer prices, have fostered capital-intensive substitution process. For instance, in the United States the producer price index for computer fell by over 14% between December 1990 and December 200055. This has also affected the composition of manufacturing trade for OECD countries over the past ten years, characterised by a growing role of high-technology products, which soared to an index by 220 in 1999 (1990=100), compared to a value of 140 of low-technology and of 125 for medium technology products. In Europe, price index change fell by 17.6% over the period 1980-1990 for hardware, - 29.6 over the period 1995-1998, by –3.3% for software and –1.8% for communication products.
Table 8: Price change of ICT investment goods (relative to output price)
1980-1990 1990-1995 1995-1998
Hardware -17.6 -16.6 -29.6
Software -3.3 -3.4 -4.2
Communication -1.8 -3.5 -3.8
Source: The EU Economy 2000 Review
Other effects of the rapid ICT price drops can be found in the increased share of IT capital goods in total investments in G-7 countries, which rose steadily over the 90s,
55 OECD, “Science, Technology and Industry Outlook. Drivers of growth: information, technology, innovation and entrepreneurship”. 2001, page 21
EMPLOYMENT RATE (2001) AND ICT EXPENDITURE AS % OF GDP (1992-1999)
0
10
20
30
40
50
60
70
80
90
0.0
1.0
2.0
3.0
4.0
5.0
6.0
7.0
8.0
9.0
Employment rate
ICT expenditure
84
accounting for 5-10 per cent of total non-residential gross fixed capital formation56 and in the so called “compositional effect”, i.e. “capital services have grown at a more rapid pace than the capital stock”, leading to more efficient capital productivity57. It is important to note that the liberalisation of the telecommunications sector has led both to the introduction of cost-savings measures, leading to tariffs reduction, and to the increase of the number of new competitors in the market. A survey on prices for telecommunication services, i.e. fixed and mobile telephony, linked to the EC 1999 Communications Review58 showed that the costs of communications during the 90s fell steadily. The falling trends in real terms of communications services were due to the decreasing costs for telecom operators and increasing competition among operators.
Figure 1: Total cost per line to a residential user of fixed telephony
Figure 2: Total cost of a mobile subscription to a residential users
56 A.Bassanini et al. “Knowledge, technology and economic growth: recent evidence from OECD countries, 2000, page 15 57 See Scarpetta et al. “Economic growth in the OECD area: recent trends at the aggregate and sectorial level”, 2000, pag.28 for a discussion on the concept and measurement of the compositional effects OECD
85
Source: Consumer Demand for Telecommunications Services and the Implications of the Convergence of Fixed and Mobile Networks for the Regulatory Framework for a Liberalised EU Market, page 15
Concerning the number of competing operators, the following table clearly show the progressive opening to the competition both with reference to fixed infrastructure networks and cellular mobile infrastructure in OECD countries. Table 9: Competition in OECD countries – number of operators - mobile and fixed infrastructure
Mobile infrastructure Fixed infrastructure
Year Monopoly Duopoly Three Four
or more
1989 24 6 0 0
1990 23 7 0 0
1991 23 7 0 0
1992 22 7 1 0
1993 19 8 3 0
1994 15 10 4 1
1995 15 9 4 2
1996 12 11 4 3
1997 6 15 4 5
1998 0 16 6 8
1999 0 10 12 8
2000 0 8 12 10
2001 0 6 12 12
Source: “The new economy beyond the hype”, OECD, 2001 Over the past 13 years, the number of operators competing in the field of fixed infrastructure has been growing at fast rates, i.e. by the beginning of 2001 only three OECD countries still had monopolies (Turkey, Hungary and the Slovak Republic). With reference to the mobile infrastructure, an open competition environment has been characterising the market, i.e. from monopoly (dominating the market by 86% of OECD countries in 1989) to three or more operators in 80% of OECD countries in 2001. However, despite the increasing opening of the market to new operators and the generally decreasing trend for prices and tariffs59, prices continue to differ among OECD countries. The example of the prices for leased lines is illuminating. These lines are usually used to transport large volume of information between firms, providing the backbone for B2B electronic commerce, and favouring Internet access. The European Commission in recent years has stressed the importance, not least for the provision of
58 “Consumer Demand for Telecommunications Services and the Implications of the Convergence of Fixed and Mobile Networks for the Regulatory Framework for a Liberalised EU Market”, June 1999 59 Recent data show that some degree of tariff rebalancing has been taking place in all Member States, i.e. “the cost of international and long-distance calls has fallen and the cost of local calls and line rental has risen. The price of both 3-minute and 10-minute long-distance calls fell by around 39% between 1997 and 2000”. “Sixth Report on the Implementation of the Telecommunications Regulatory Package”, COM (2000) 814, 07-12-2000
Year Monopoly Duopoly Open
Competition
1989 26 1 3
1990 26 1 3
1991 25 1 4
1992 24 1 5
1993 23 1 6
1994 22 1 7
1995 22 1 7
1996 21 1 8
1997 19 0 11
1998 8 0 22
1999 7 0 23
2000 6 0 24
2001 3 0 27
86
cheaper Internet services, of the rapid availability of leased lines at cost-oriented prices60. Although the liberalisation processes has led to price reductions, the prices of leased lines still vary remarkably from one country to another.
Figure 3: The cost of leased lines in The OECD, august 2000
Source: “The new economy beyond the hype”, OECD, 2001 Taking as 100 the average OECD area, the charges range from a level under 25 in Iceland, Finland, Denmark and Sweden to more than 200 in Hungary and Czech Republic. Another example concerns the cost of Internet access for consumers: according to a 1997 OECD report61, “20 hours of Internet use cost $38 in Finland, $64 in the UK, and $74 in Germany, compared to $29 in the US”. On September 2000, 40 hours of Internet use at peak time were charged $22 in the US, $42 in Finland, $60 in UK and $50 in Germany. Notwithstanding a general reduction in access prices, it can be observed that price difference can be still found across European countries. The price is a key variable for enhancing Internet use and related electronic services. As the recent report from EC has stated62, there are empirical evidences about “the fundamental prediction that the demand curve of Internet services is downward sloping”. The empirical evidence is based on the fact that countries with low average access costs over the period 1995-2000 registered a higher number of Internet hosts than other countries with higher access costs. The figure below shows a group of OECD countries with higher Internet hosts and lower access prices, i.e. United States, Finland, Norway, Sweden, and Iceland.
60 “Sixth Report on the Implementation of the Telecommunications Regulatory Package”, COM (2000) 814, 07-12-2000 61 Quoted in Green Paper on the convergence of the telecommunications, media and information technology sectors, and the implications for regulations towards an information society approach. COM (97) 623, 03-12-97 62 “Competitiveness, Innovation and enterprise performance” A selection of graphs and tables from the Competitiveness Report, the Innovation Scoreboard and the Enterprise Scoreboard, 2001
87
Figure 4: Access costs and Internet hosts in OECD countries
Source: “The new economy beyond the hype”, OECD, 2001
The same correlation for European countries between use and prices can be verified in the case of leased lines costs (average price index for 64 kbit/s and 2 Mbit/s) and connections to the Internet: Iceland, Norway, Denmark, Sweden and Finland resulting the European countries with lower prices and higher connections63. The analysis of costs and tariffs for leased lines and Internet access leads to the identification of a group of European countries with low costs and tariffs and greater Internet use, i.e. Finland, Sweden, Denmark, compared to other countries with higher costs and less Internet diffusion. It’s worthwhile to note that countries that moved early to liberalise their telecommunication industry show a wider use of ICT. The table below compares some regulatory issues, i.e. local access and leased lines regimes, between countries with lower prices, i.e. Finland, Sweden, and Denmark, and laggard countries, i.e. Italy. It can be observed the different pace of the regulatory framework (under the column overview) and its impacts (on local access conditions and leased lines prices): early and comprehensive in Finland, Sweden and Denmark, lately and incomplete in Italy.
63 See OECD “Science, Technology and Industry Outlook”, 2001, page, 37
88
REGULATORY ISSUES
Overview Local Access Leased Lines
FINLAND Finland has a light regulatory regime places greater emphasis on market forces than on detailed regulation.
A full unbundling of the local loop (LLU) has been available as
a matter of law since June 1997
Latest comparative data indicate that national leased line tariffs remain low by comparative EU standards.
SWEDEN Competition on the fixed telephony market has developed since September 1999, with several new players entering the market and end-user tariffs falling.
95% of all households are serviced by more than one network
The prices for national leased lines (analogue, 64 Kbit/s and 2 Mbit/s) were among the lowest in
Europe
DENMARK The full local loop unbundling was introduced in July 1998
Latest comparative cost data for leased lines indicate that retail rental prices for national leased lines are among the cheapest in the EU
ITALY Detailed regulations are still urgently needed in certain areas, and have been adopted late in other areas (cost accounting, rights of way), and there are difficulties in implementing the regulations in other areas (tariff re-balancing, numbering).
With a view to meeting the concerns of new entrants regarding the lack of access networks competing with those provided by the incumbent, on 16 March 2000 the NRA adopted the Decision on the unbundling of the local loop (*).
In 1999 the incumbent was still the sole supplier of leased lines. Competition is now developing in long-distance and backbone services provided by alternative operators. The incumbent still dominates the local and short-distance markets.
(*) The unbundling of wireless local loop in Italy has been carried out on May 2002, with the assignment of license to private operators.
3.4.3 ICT investment trends
The growing role of the ICT capital stock in enhancing economic development, measured by its contribution to GDP growth, has been recently analysed in a comparative study of nine OECD countries64. The following table shows the percentage contribution of ICT capital stock to GDP growth in nine OECD countries. During the second half of 90s, in three countries where economic growth has been stronger, United States, Finland and Australia, a high contribution of total ICT capital stocks to GDP growth can be observed: 0.9 percentage points in the United States, 0.6 percentage points in Finland and Australia.
64 A.Colecchia, P.Schreyer, “ICT investment and economic growth in the 90s: is the United States a unique case ? OECD Working Papers, 2001
89
Table 10:Percentage point contribution to annual average GDP growth, business sector
United Finland Australia France Japan Italy Germany
States
IT and 1990-1995 0.3 0.2 0.3 0.2 0.2 0.2 0.2
Communication 1995-1999 0.6 0.4 0.4 0.2 0.3 0.2 0.2
Equipment
Software 1990-1995 0.1 0.1 0.1 0.1 0.1 0 0.1
1995-1999 0.3 0.2 0.2 0.1 0 0.1 0.1
Total ICT 1990-1995 0.4 0.2 0.5 0.2 0.3 0.2 0.3
1995-1999 0.9 0.6 0.6 0.4 0.3 0.3 0.3
Source: “The new economy beyond the hype”, OECD, 2001, pag 20
Evidences about the ICT growth contributions to GDP by the various types of ICT capital goods, i.e. software, hardware and communications equipment, have been also provided for European countries and US by the STAR Project65 over the period 1991-1999. As illustrated by the results shown in the table below, there is factual evidence of:
• a growth contribution of computers relatively smaller in Europe than in US
• a growth contribution of software lower in Europe than in the United States
• a growth contribution from communications equipment in Europe higher than in the United states, particularly in those countries with a lower degree of adoption of new technologies, i.e. Greece, Portugal, Spain.
Table 11:The growth contribution of ICT capital and its components 1991-1999
(data in percentage points)
GDP ICT HW SW TLC
US 3.34 0.94 0.50 0.36 0.08
Ireland 6.91 0.64 0.30 0.12 0.22
Denmark 2.87 0.52 0.29 0.14 0.09
The Netherlands 2.83 0.68 0.33 0.22 0.13
UK 2.68 0.76 0.39 0.26 0.11
Portugal 2.47 0.43 0.18 0.05 0.19
Austria 2.33 0.45 0.23 0.12 0.11
Spain 2.32 0.36 0.17 0.06 0.14
Greece 2.25 0.34 0.12 0.04 0.18
Finland 2.13 0.45 0.27 0.10 0.08
Belgium 1.88 0.48 0.23 0.14 0.11
Sweden 1.86 0.59 0.38 0.13 0.08
Germany 1.65 0.49 0.24 0.12 0.13
France 1.64 0.41 0.20 0.11 0.11
Italy 1.41 0.31 0.15 0.05 0.11
Source: STAR, report N.1, May 2001, page 27
65 “Growth and Employment Effects of Information and Communication Technologies in Europe”, May 2001
90
3.4.3 The overall efficiency of labour and capital
The contribution of ICT to the productivity growth, i.e. both the labour productivity (output per man hour) and the multi-factor productivity index (MFP), is a more controversial issue66. The productivity gains arising from ICT use can be differentiated in two sectors:
• Growth in labour productivity for the ICT producing industries, by increasing the amount of capital deployed per worker
• Growth in productivity gains for the ICT-using sectors While there is less doubt about the productivity rising for the sectors producing ICT, i.e. by 24% in the 90s for United States, according to the “Economist”'s survey67, empirical evidences in the United States over the period 1987-1997 suggest that the reverse is true for the ICT-using sectors. The table below illustrates that the sectors which used IT most intensively, i.e. banking and education, showed declining productivity rates.
Table 12: America’s total factor productivity by industry, -Annual average % change 1987-1997-
Annual average total productivity
Spending on IT as %
output
Mining 4 0.6
Wholesale trade 2.5 0.9
Manufacturing 2.2 1.7
Public Utilities 2.2 1.8
Insurance 1.8 2.1
Transport 1.7 0.9
Communications 1.7 1.8
Retail Trade 1 0.7
Construction 0.2 0.2
Business Services -0.2 0.6
Education -1 2.5
Health -2.3 0.6
Banking -3.8 2.8
Source: The Economist “Survey on the New Economy”
66 Notwithstanding such empirical correlation, it remains unclear how much of the MFP depends on ICT contribution or other factors such as the increase of R&D or organisational improvements. Cross-country regression aiming at explaining the rate of MFP growth with a group of selected variables found that ICT production share accounted by more than 20% and R&D capital expenditure by 10%. 67 The Economist, “Survey of the New Economy”, 23rd September, 2000
91
A recent study from Van Ark (2001)68 addressed the issue of ICT structural effects on labour productivity growth in ten developed countries. He regrouped the industries into three different groups: ICT producing industries, ICT-using industries and industries without any links to ICT. While the classification of ICT-producing industries broadly coincides with the OECD classification, that of ICT-using industries has been defined by the author, using the share of ICT investment on industry output and the industry share in the ICT capital stock in the US and the Netherlands as criteria69. According to this study, whose main results are reported in the table below, in all countries surveyed – except Japan where the share was very high already in the beginning of the ‘90ies – there has been a significant increase in the ICT-producing and ICT-using industries’ share of aggregate labour productivity growth from 1990-95 to 1995-99. Table 13: Percentage-point contribution to labour productivity growth 90-95
and 95-99 ICT-
producing industries
ICT-using industries
Non ICT-industries
Total
Canada 1990-95 0.19 0.33 0.69 1.20
1995-99 0.26 0.41 0.29 0.96
Denmark 1990-95 0.26 0.20 1.55 2.01
1995-99 0.17 0.58 0.20 0.95
Finland 1990-95 0.60 0.07 2.65 3.33
1995-99 1.41 0.61 0.70 2.72
France 1990-95 0.18 0.15 0.75 1.09
1995-99 0.43 0.18 0.65 1.27
Germany 1990-95 0.10 0.53 1.46 2.10
1995-99 0.40 0.52 0.47 1.66
Italy 1990-95 0.19 0.52 1.12 1.83
1995-99 0.25 0.23 0.11 0.59
Japan 1990-95 0.28 0.38 0.12 0.77
1995-99 0.39 0.31 0.10 0.81
68 Unpublished manuscript, quoted in J. Jalava, Quantifying the New Economy: challenges for economic statistics, paper presented at the 17th CEIES Seminar, The New Economy – Key Measurement Issues, Rome, 4-5 March 2002 69 using the ISIC – rev.3 classification, ICT-producing industries include: Office, Accounting and Computing Machinery; Insulated Wire and Cable; Radio, Television and Communication Equipment; Medical Appliances & Instruments & Appliances for Measurement; Post and telecommunications; Computer and related services. ICT-using industries include: Publishing, Chemical and Chemical Products, Electrical Machinery, Apparatus etc.; Medical, Precision and Optical Instruments; Wholesale Trade; Financial Intermediation; Insurance and Pension Funding; Activities Related to Financial Intermediation; Renting of Machinery and Equipment; Research and Development; Other Business Services
92
ICT-producing industries
ICT-using industries
Non ICT-industries
Total
Netherlands 1990-95 0.09 0.32 0.86 1.27
1995-99 0.52 0.61 -0.20 0.93
UK 1990-95 0.38 0.56 1.53 2.48
1995-99 0.56 0.50 0.15 1.21
USA 1990-95 0.31 0.29 0.55 1.15
1995-99 0.65 1.37 0.52 2.54
Source: Van Ark, 2001
The shares have increased so much that the combined contribution of ICT-producing and ICT-using industries to labour productivity growth is greater than the contribution of non-ICT industries in all countries, with the exception of France. However, these results strongly depend on the aforementioned classification criteria – and especially those used to classify ICT-using industries – which are far from being definitive and stable. Moreover, it has to be considered that some of the benefits from ICT application cannot be easily captured through the GDP figures or productivity statistics. Considering the service sectors (banking, business services, wholesale and retail trade), the benefits due to the application of ICT do not come simply from costs saving but from increased quality, convenience and customer service differentiation, not easy to be taken into account by statistical surveys. Summing up, we can say that the effects of ICT use on productivity are mainly shaped by two facts:
• the use of ICT in business firms creates a potential for productivity increases. But this potential has to be realised with the adoption of new business processes, and complementary investment in human resources and skills;
• the application of ICT can lead to improved service quality in the service sectors. This improvement is in many cases difficult to measure and, depending from the market situation, could not affect the prices. This means that current ways of measuring service output fails to measure their real value for money, and productivity estimates are under-estimated.
Another factor to be considered for the proper assessment of the ICT contribution to overall productivity is the time necessary for a full emerging of benefits from ICT. Some economists argue that a technology has to reach at least the 50% of penetration rate in order to have a significant effect on productivity. Assuming the Personal Computer per 100 people as proxy indicator for penetration rate of ICT, in the United States the threshold of 50% was reached only recently, and the other OECD countries still lag behind70.
70 In 1999, behind United States ranked Sweden (51%), Australia (48%), Canada (47%), UK (37%), Japan (33%), France and Germany (32%), Italy (24%).
93
Despite the difficulties in the measurement, the main ICT contribution to productivity growth appears to be through the channel of MFP growth rates. While the capital deepening process can be spurred by losses in employment rather than acceleration in investment, as in Spain, Portugal and Finland during the first half of 90s, the MFP growth rate is more directly affected by technological improvement and innovation. At present the MFP growth accounts for more than 50% of productivity growth in the EU and USA, and represents the real advantage for the US economy, comparing to the EU.
Source: The EU Economy 2000 (see Ref.[36] )
Confirmation of the link between ICT and MFP growth rate emerges both from a supply side point of view, i.e. the link between ICT production share and MFP growth rates, and from a demand side approach, i.e. the link between ICT use and change in MFP growth rates. The following figure addresses the supply side point of view, suggesting over the period 1992-1998 a relationship between ICT production and MFP growth rates.
Source: The EU Economy 2000
94
However, it is important to note again that the remarkable MFP growth rate of countries like USA, Sweden, Finland during the 90s can not only be explained through the existence of higher ICT production shares, but has to be integrated with the demand side: the ICT using propensity. A recent study71 found a positive correlation between the largest increase in the penetration of PCs, and the growth in MFP in some OECD countries.
Figure 5: MFP growth and increase in ICT use
Source: “The new economy beyond the hype”, OECD, 2001 In conclusion, there are several possible explanations of the changing economic growth pattern during the 90s in the OECD area, and the ICT sectors, with their contribution on employment, capital investments and productivity rates, can be considered as one of the key explanatory factors. 3.5 Correlation and regression analysis In order to support with further empirical evidence the findings on the contribution of ICT to GDP growth discussed in the previous chapter 3.4, a correlation and regression analysis has been carried out72. The following indicators related to ICT have been considered:
71 OECD “The new economy beyond the hype”, 2001 and OECD Information Technology Outlook 2000. The correlation coefficient related to the above relationship is 0.61 72 See also Appendix 1 for details on the outcomes and statistical parameters
95
• ICT investment 1999 (ICT INV). Investments in communications equipment, hardware and software calculated as nominal shares on GDP in percentage points at 1999 for the USA and EU countries, and at 1997 for other OECD countries (Australia, Japan, New Zealand). The USA leads the ranking with about 5 percentages point of GDP, followed by UK and Sweden with approximately 4 points. Source: STAR Project, Report n. 1
• ICT price reduction index 1990-1997 (ICT Price). Price level variation for communication equipment, hardware and software in OECD countries between 1990 and 1997. The USA, Denmark and France showed the higher price reduction, on average between –40% and –42%. This variable has been standardised in order to calculate the corresponding ICT price reduction index taken as input for the correlation analysis. Source: F. Daveri “ Is growth an information technology story in Europe too?” University of Parma, 2000, pag. 30
• R&D expenditure in ICT industries 1995-1999 (ICT R&D). This indicator is calculated as the share of ICT enterprises indicating expenditures in R&D on the total business R&D expenditures. The classification of ICT enterprises is based on the ISIC Rev.3, and includes divisions 30 (office, accounting and computing machinery), 32 (radio, television and communication equipment and apparatus) and 33 (medical, precision and optical instruments, watches and clocks). It can be observed that Finland, Sweden, the Netherlands and the USA showed the higher percentage of ICT enterprises spending in R&D. In particular in Finland, with an average of more than 40% ICT enterprises. Source: OECD, STI Scoreboard 2001, table A.4.3.1
ICT PRICE LEVEL 1990-97
-50
-40
-30
-20
-10
0
B DK FIN F D I NL E S UK USA
ICT R&D EXPENDITURE 95-99
0
10
20
30
40
50
B DK FIN F D I NL E S UK USA
As % of business enterprise sector R&D expend.
ICT INVESTMENT 1999
0
1
2
3
4
5
B DK FIN F D IRL I NL E S UK USA
Nominal share on
GDP
96
• ICT export 1996-2000 (ICT EXP). This indicator shows the average yearly growth rate of exports in M € during the period 1995-2000 for ICT sector. It can be assumed as a proxy variable addressing the presence of a strong manufacturing ICT sector in the national economic structure. Finland, Sweden and US, with an average growth rate of more than 25%, have a vital ICT sector. Source: for the EU countries: Eurostat, Information Society Statistics, 2001, n.34, table 6. USA data are estimated for the period 1996-1998 from OECD, Communication Outlook, 2001, table 10.1
• Tertiary educational attainment 1999 (TER EDU). This indicator shows the number of science graduates per 100,000 persons in the labour force 25-34 years of age. Science fields include life sciences, mathematics and statistics, computing, engineering, architecture and building. France and Finland showed the higher percentage of graduates. This indicator has been selected because represents the potential supply of high-skilled workers in the national economies. Source: OECD, STI Scoreboard 2001, table C.4.4. For Belgium, Denmark and Italy, data estimates from EC, European competitiveness Report, 2002, Table II.5.
• ICT spending as GDP share 1992-1998 (ICT SPE). The ICT spending is calculated as the average nominal share on GDP during the period 1992-1998. It includes spending on sales of hardware, software and related services by the final clients (households, corporations, government agencies). Sweden, UK and the USA showed the higher percentage of ICT spending, approximately by 8% of GDP.
ICT EXPORTS (Mio Euro) 96-2000
0
5
10
15
20
25
30
B DK FIN F D I NL E S UK USA
Average growth per year (%)
ALL TERTIARY EDUCATION 1999
0
500
1000
1500
2000
2500
B DK FIN F D I NL E S UK USA
Graduates per 100,000 persons 25-34 years
ICT SPENDING 1992-1999
0
2
4
6
8
10
B DK FIN F D I NL E S UK USA
Average nominal spending as a share of GDP
97
Some of the above indicators have been used in the context of two separate regression models, aiming respectively to find a correlation between: 1. the contribution of ICT capital deepening to economic growth and two possible of
2. the contribution of Total Factor Productivity to economic growth and three possible explanatory variables: presence of a robust ICT producing sector (measured with the proxy ICT export 1996-2000 – ICT EXP), R&D expenditure in ICT industries (ICT R&D) and quality of human capital (measured with the proxy “tertiary educational attainment – TER EDU).
The following paragraphs discuss in turn the models adopted and their results.
3.5.1. Capital deepening contribution to economic growth
The capital deepening represents the growth of the capital/labour ratio, which is one of the driving forces behind the labour productivity growth. According to several studies, the acceleration in capital deepening in the second half of the 90’s contributes to explain the gap in labour productivity growth and economic growth rate between EU countries and the USA73. Notwithstanding the variability of the estimates concerning the contribution of ICT capital to economic growth – mainly due to problems in measuring the size of the ICT capital itself, including the contribution of software investment - comparable order of magnitude can be observed between OECD and BLS data74. It ranges between 0.2 – 0.6 percentage points in EU countries and 0.9 in the USA during the 90’s. However, data relative to the second half of the 90’s (1996-1999), as estimated by the STAR Project, showed higher contributions, in particular for the USA (1.5 percentage points) and some EU countries, i.e. UK (1.2), Sweden (0.8) and Finland (0.7).
ICT CAPITAL CONTRIBUTION TO
GROWTH 1996-99
0
0.5
1
1.5
2
B DK FIN F D IRL I NL E S UK USA
Percentage points on GDP
As anticipated above, two variables can be considered as explanatory factors of the ICT capital contribution to growth:
• ICT investment (ICT INV)
• ICT price reduction (ICT Price)
73 In particular, see The EU Economy review 2000, chapter 3, page 102 74 See Federal Reserve Bulletin, Productivity Development Abroad, October 2000
98
Hence, taking the above ICT capital contribution to growth as dependent variable, the regression model75 includes the ICT investment and the ICT price reduction indicators as independent variables, so that:
ICT capital deepening = a + b*ICT INV (X1) + c*ICT Price (X2) The matrix of correlation coefficients shows a high correlation between ICT investment and ICT capital contribution to growth (0.94) and a weaker correlation with the ICT price reduction index.
Dependent
variable Var. 1 Var. 2
Dependent variable 1.00 0.94 0.39
Var. 1 0.94 1.00 0.48
Var. 2 0.39 0.48 1.00
• Variable. N° 1 ICT investment 1999
• Variable. N° 2 ICT Price reduction index (1990-97) The regression equation estimated with the standard least squares method, fitting the data observed for US and 10 EU countries76, is the following:
Y = -0.287 + 0.400X1 – 0.062X2 (1) The multiple regression coefficient R2 is equal to 0.90. The following graph shows the good adaptation between the observed value of ICT contribution to growth and the corresponding theoretical values obtained through the regression equation.
ICT CONTRIBUTION TO GROWTH 1996-99
0
0.2
0.4
0.6
0.8
1
1.2
1.4
1.6
USA UK S FIN NL DK B D F I E
Observed values
Theotetical values
Percentage points on GDP
It can be observed that with respect to the average ICT contribution to growth (0.6 percentage points) two groups of countries can be identified: a group of front-runners countries over the average (USA, UK, Sweden, Finland, the Netherlands and Denmark)
75 further details concerning the parameters of the regression model are given in Appendix 1. 76 only countries with data for all the variables are included in the regression models.
99
and the others, laggards, under the average (Spain, Italy, France, Germany and Belgium). Then, in order to differentiate the trend of growth, two regressions have been carried out with reference to the two groups of countries, taking as reference the same regression model of the above equation (1). The results, respectively for the front-runners and the laggard countries, are the following: Front-runners countries:
Y = -0.133 + 0.382X1 – 0.133X2 (2) The multiple regression coefficient R2 is equal to 0,839. Laggard countries:
Y = 0.073 + 0.117X1 + 0.073X2 (3) The multiple regression coefficient R2 is equal to 0,99.
3.5.2. Total Factor Productivity (TFP) contribution to economic growth
The total factor productivity accounts for more than 50% of the labour productivity growth, both in the USA and in the EU countries. The question here is to determine to what extent enablers exist which influence the TFP growth rates, and by this way the growth of GDP. Literature review based on cross-section data for OECD countries77 identifies at least three variables influencing TFP:
1. ICT production share 2. R&D investments 3. Quality of labour or human capital factors
The following proxy variables of have been considered here:
• the ICT export 1996-2000 (ICT EXP), indicating the presence of a consistent ICT sector in the national economic structure;
• the R&D expenditure in ICT industries 1995-1999 (ICT R&D), as for the R&D investments,
• the tertiary educational attainment at 1999 (TER EDU) with reference to the human capital factors. In this context, it should be also noted that the last European competitiveness Report 2002 indicates in the tertiary-level skill gaps, one of the main obstacles to be overcome in the near future78.
77 See, for instance, The EU Economy review 2000, chapter 3, page 104. 78 EC, European competitiveness Report 2002, page 8
100
The issue of the contribution of the ICT spending to the TFP growth is more controversial. On the one hand, some evidence supports the relationship between using ICT (PCs, Internet hosts, secure servers) and related increase in MFP79, on the other, the correlation between ICT spending and TFP does not provide clear signs in this direction80. However, a fourth proxy variable for ICT spending has been included. The matrix of correlation coefficients below, while confirming the high correlation between the first three independent variables above and TFP contribution to growth, shows also that there is no correlation between ICT spending and TFP contribution to growth, at least on the basis of the available data.
• Variable. N° 4 ICT spending as GDP share 1992-1998 (ICT SPE) The low correlation coefficient between ICT spending and TFP contribution to growth (0.15) has suggested to set up the regression analysis taking into account only the other variables, according to the following model81: TFP contribution to growth = a + b*ICTR&D (X1) + c*ICTEXP (X2)+d*TEREDU (X3) The regression equation estimated with the standard least squares method, fitting the data observed for US and 11 EU countries82, is the following:
The multiple regression coefficient R2 is equal to 0,91. The relationships between the observed TFP contributions to growth and the corresponding theoretical values are shown in the following graph.
79 See, for instance, D.Pilat and F.C.Lee. “Productivity growth in ICT-producing and ICT-using industries: a source of growth differentials in the OECD, 2000, page 13 80 See A.Stobbe, “New Economy in Europe – reality or mirage?” Deutsche Bank Research, 2001 81 further details concerning the parameters of the regression model are given in Appendix 1. 82 only countries with data for all the variables are included in the regression models.
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TFP CONTRIBUTION TO GROWTH 1996-99
-1.0
0.0
1.0
2.0
3.0
4.0
5.0
IRE FIN USA S F D UK NL E DK I B
Observed values
Theoretical values
Percentage points on GDP
The graph shows that six front-runner countries can be identified: Ireland, Finland, the USA, Sweden, France and Germany, with a contribution higher than 1.0 percentage point. The others (Belgium, Italy, Denmark, Spain, the Netherlands and UK) show contributions under 1.0 of percentage points. The two regressions carried out with reference to the above two groups of countries, taking as reference the same regression model of the above equation (4), provide the following results: Front-runners countries:
Y = -2.422 + 0.081X1 + 0.040X2 + 0.001X3 (5) The multiple regression coefficient R2 is equal to 0,89. Laggard countries:
Y = 0.461 - 0.042X1 + 0.067X2 + 0.000X3 (6) The multiple regression coefficient R2 is equal to 0,89. 3.5.2.1. The drivers of ICT contribution to economic growth: a comparison
The impacts of ICT production and investment on economic growth during the 90’s have been analysed in several studies, largely quoted in the present contribution. Some of them have tried to disentangle the ICT contribution to economic growth, i.e. the labour productivity growth, splitting up the increase in labour productivity in two components: capital deepening, with workers using more machines, and total productivity growth, in which existing resources of capital and labour are used more efficiently.
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Depending on the answer, a different interpretation of the potential spill-over effects of ICT can be envisaged, i.e. focussing on the capital deepening role means concentrating on the ICT producing sectors, according to the the traditional path of relative ICT prices decline and labour input-substitution processess. Stressing the TFP role, on the other hand, implies to focus on the ICT growing use in the overall economy that stimulates the related network-effects, as a general-purpose technology should do. Based on empirical observations, what of the two channels of economic growth, i.e. capital deepening or TFP, can be better stimulated by the ICT contribution, is still an opening issue. For instance, Stephen Oliner and Daniel Sichel, among the first to document the jump in the Americal productivity83, have recently updated their earlier work at 2001, reaching opposite conclusions84: more than the whole of the increase in productivity growth since 1995 now seems to be determined by capital deepening effects (mainly IT equipment and IT goods). Outside the computer industry, multifactor productivity fell slightly after 1995. Leaving a part the intrinsic difficulty in estimating productivity in the service using-ICT sector85, there is little evidence of significant spill-over effects from the ICT use86. The low correlation coefficient between ICT spending and TFP contribution to growth (0.15) shown in the present regression analysis supports such a point of view. This could partially explain why the capital deepening contribution to economic growth, via ICT investment and ICT price reduction, shows more robust results (multiple regression coefficient 0.99), compared to the factors affecting TFP contribution to economic growth (multiple regression coefficient 0.91). Moreover, it should be also considered that the ICT investment also explains, at least in part, the spillovers effects through their impacts on Total Factor Productivity. The presence of a strong ICT producing sector in fact involves at the same time high rates of R&D expenditures and ICT export, two variables correlated with high TFP contributions to growth (respectively 0.76 and 0.81), as confirmed by the Euroframe Group, which stressed that Finland, Ireland, Sweden and the USA, countries with a strong ICT producing sector, also showed significant increase in the TFP87. Moreover, a positive elasticity on TFP growth has been found for IT software provision (telecommunication software and equipment) in the MUTEIS project88. The elasticity coefficients amount respectively to 0.13 and 0.09, on the same order of magnitude of
83 Oliner S.D, Sichel, D.E (2000) 84 See “The Economist”, November 2 nd 2002, “Productivity promises” 85 See infra, chapter 3, paragraph 3.4.3 86 See, for instance, EC Economic Papers, W.Roeger, “The contribution of Information and Communication Technologies to Growth in Europe and the US: a macroeconomic analysis”, 2001 87 EUROFRAME, “The Economic Situation of the European Union and the Outlook for 2001 –2002”, page 53 88 MUTEIS – Macro-economic and Urban Trends in Europe's Information Society, “ ICT and network effects: a macro-economic approach”, by H.Meijers
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the elasticity (0.13) found for IT exports (a variable which can be assumed as a proxy of a strong manufacturing ICT sector), in the present regression analysys. However, it would not be correct to conclude that the presence of a large ICT producing sector is a necessary and sufficient condition to guarantee an effective ICT contribution to labour productivity and economic growth. As several OECD studies have stressed, there are countries, i.e. Australia, which showed high TFP rate without having large ICT producing sector and Japan, with strong ICT producing sector and weak TFP growth during the 90’s89. This implies that appropriate policies enforcing ICT diffusion, i.e. labour skill upgrade, regulative market deregulation favouring ICT price reductions, etc, should accompany the ICT investment, which nevertheless remains a key variable. 3.6. Contribution of Innovation and Learning to Growth In this section we will address more explicitly the role of innovation and learning as a crucial determinant of economic growth. We will focus on the links between ICT production and use by one side, and the innovation, learning and knowledge accumulation processes – including both individual and organisational learning – by the other side. ICT plays a crucial role, as potential enabler of many of wider and deeper innovation processes90:
• ICT has helped to break down the natural monopoly character of services such as telecommunication favouring the convergence of voice and data and new services through the digitisation.
• ICT is a key technology for speeding up the innovation process, resulting in a closer link between business strategies and performance.
• ICT has fostered greater networking in the economy, as it has facilitated outsourcing and co-operation beyond the firm, also in the absence of constant, geographically localised interaction.
• ICT makes possible faster diffusion of codified knowledge and ideas within and across borders of other technologies, i.e. the adoption of ICT appears to be fundamental for the development of new technologies, as for example nano-technology, biotechnology.
89 See D.Pilat and F.C.Lee. “Productivity growth in ICT-producing and ICT-using industries: a source of
growth differentials in the OECD, 2000, page 22 and A.Colecchia, P.Schreyer, “ICT investment and economic growth in the 90s: is the United States a unique case ?” OECD Working Papers, 2001, page 21 90 See also OECD, “A new economy ? The changing role of innovation and information technology in growth”, page 47
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Three measurable innovation enabling factors will be discusses in what follows: R&D expenditures and activities, the role of human capital, and that of removing cultural and administrative barriers to entrepreneurship.
3.6.1 Innovation enabling factors: R&D
Investment in R&D has been considered as a proxy of innovation, in the form of blueprints for new products or new processes, by the endogenous growth models approach. It is now widely recognised that R&D expenditures is a crucial determinant of innovating activities at firm level, although other activities, such as engineering, “learning-by-doing” processes, organisational measures (not formally included in the R&D statistics) make a significant contribution. Moreover, together with the business R&D, the basic governmental R&D plays a fundamental role in the process of creating innovation. For instance, the ability to understand and make use of the results of basic research performed in other countries requires strong domestic R&D capabilities, just evidenced by the Nordic countries which, despite their small size and use of foreign technology, have among the highest levels of investment in R&D91. An effective integration between public and business R&D is a prerequisite for the set up of an innovative environment, e.g. the concept of national innovative system of the evolutionary approach to innovation. In the context of ensuring an effective interaction between the two actors of innovative practices the following priorities have been carried out in a recent OECD report on the new economy92:
• Give greater priority to basic research; future innovation will be jeopardised without it.
• Improve the effectiveness of government funding for innovation, focusing on areas with high economic or social benefits, encouraging public-private partnerships
• Set up the legal framework for enhancing innovation, defining new schemes of intellectual property regimes. Key arguments in the field are: 1) increase predictability and reduce transaction costs, 2) increase incentives to commercialise, 3) decrease costs of protection and exploitation, 4) limit restrictions on publication and scientific enquiry.
• Remove barriers and regulations that limit effective interaction between universities, firms and public laboratories
Assuming the MFP growth rate as an indicator of innovation, empirical evidences prove the relationship between innovation and R&D expenditures. An econometric analysis was conducted on a panel of 16 OECD Member countries to determine the contribution of R&D performed by the business sector, the public sector (i.e. government laboratories and institutions of higher education), and foreign businesses to MFP growth between 1980-9893.
91 OECD, European Competitiveness Report, 2001, page 62 92 OECD, “The new economy beyond the hype”, 2000 page 52 93 See for detail OECD, “The new economy beyond the hype”, 2000 page 55
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The most significant results can be summarised as follows:
• Effects of business R&D on productivity. On average, a 1% increase in business R&D coincided with a 0.13% increase in MFP. The effect increased after 1980 and was larger in more R&D-intensive countries. It’s interesting to note that the effect of business R&D on MFP was lower where the share of government in funding was larger, probably due to the government expenditures on defence R&D which made a smaller contribution to MFP.
• Effect of foreign R&D on productivity. A 1% increase in foreign R&D is correlated with a 0.44% increase in MFP. This effect was essentially stable since 1980 and was larger in R&D-intensive countries, suggesting that the size of the domestic R&D base influences the rate of technology adoption from abroad. The impact was somewhat larger the smaller the size of an economy.
• Effect of public R&D on productivity. A 1% increase in public R&D coincided with a 0.17% increase in MFP. The effect decreased after 1980 and was larger in countries in which the share of universities (as opposed to government labs) was higher. The effect was also larger in countries with lower shares of defence R&D and higher levels of R&D intensity.
In conclusion, the analysis suggests that uneven impacts in innovation arising from R&D expenditures, especially among high-income countries, are influenced by differences in the way R&D expenditures are allocated and managed, but also by differences in the structure of national innovation systems and the linkages among innovating organisations.
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3.6.2 Innovation enabling factors: role of human capital
In recent years, the role of human capital has been clearly addressed through strategies and initiatives both at government and European level. For instance, the ESIS Report94, collecting the national and regional strategies for the development of the Information Society in the European Union, emphasised the priorities for a comprehensive strategy towards the full development of the education sector, “a primary target for the first Information Society public strategies”, associate with the emphasis increasingly placed on life-long learning and training processes. Furthermore, it has to be mentioned the Commission's Communication on "Strategies for Jobs in the Information Society"95 built on experience of Member States in order to identify the key areas of progress to seize the job opportunities and to enhance the living and working conditions for all citizens in the Information Society. Other initiatives, aiming at improving human capital endowment, have directly involved enterprises and business areas, i.e. the benchmarking projects and “Go Digital” initiatives96, which identified a number of quantitative targets to be achieved by national and/or European policies, e.g. in the areas of awareness and training and the participation of SMEs (Small and Medium-Size Enterprises) in e-marketplaces, including e-procurement. The role of human capital as enabling factor of economic development has been deeply analysed, both in relation to the economic growth, i.e. GDP growth rates, and with reference to its relationship with ICT use and innovation requirements, i.e. skilled workforce. Although our knowledge of the impacts of human capital on economic growth can rely on a considerably body of literature, in particular focusing on the role of education97, this remains an issue where empirical results are too weak to support uncontroversial statements. In this context, at least three families of studies can be identified: 1. A family of studies from labour economics, focusing on the link between education
and productivity, i.e. the “human capital earning functions”, where the explanatory
94 “Public Strategies for the Information Society in the Member States of the European Union”, ESIS Report, 2000 95 COM (2000) 48 final of 4 February 2000. These strategies have been carried out as a response to Lisbon; for instance, the European Employment Strategy, focusing on life-long learning and quality jobs in the knowledge-based economy, the eEurope Action Plan, the European Union's roadmap to the Information Society by 2002, with one of its three key objectives focusing on investing in people and skills; the "eLearning: Designing Tomorrow's Education" initiative in May 2000 in order to speed up changes in the education and training systems for Europe's move to a knowledge-based society. 96 “Summary of Results of Best Practice-related Activities in the field of Enterprise Policy” SEC 200, Benchmarking Report following-up the "Strategies for jobs in the Information Society", SEC 2001, and “Helping SMEs to Go Digital”, “the Go Digital Communication”, adopted in March 2001 97 For a useful review: J.Temple, “Growth effect of education and social capital in the Oecd countries”, OECD Working Paper, 2000
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variable is the year of schooling, suggests with robust econometric estimates a gaining ranging from 5 to 15% in earnings for one additional year of education, depending on time and country. The problem in such a family of studies arises in the omitted variables that are likely to be correlated with earning and schooling, e.g. family background or quality of school.
2. A group of studies with a macro-economic approach, the “growth accounting”
school, provide empirical support to the relationship between input growth, i.e. human capital, and output growth, i.e. value added. An example for a group of OECD countries shows that human capital has contributed to labour productivity growth by 0 to 1 percentage point. The studies found for the period 1948-1979 in US that labour quality, through better educational attainment98, is responsible for about a tenth of the growth of value added. Similar studies for G7 countries between 1960s and 1980s found that the growth of human capital accounted for about 10/20% of growth in total output. According to J. Temple, the common characteristics in such a group of studies is the hiding of other indirect effects, i.e. R&D, investments, so that “ a claim that X percentage points of growth in a given country is due to a change in the quality of the labour force does not imply that, in the absence of the change in labour force quality, the growth rate of output would have been precisely X percentage points99”.
Source. The EU Economy review , 2000
3. Another group of studies, i.e. the growth regression studies, provide results based on cross-country regression incorporating variables for physical capital, education, proxy variables for institutional factors, etc. According to a recent OECD review of a sample of these studies, the results implied on average that if human capital increases by a tenth, output per worker will rise by 6 per cent. But the findings strongly depend on the quality of data and basic assumptions: “the selection of countries, choice of time and specification of models could make a substantial
98 The assumption underlying the estimates is that the mean income associated with each schooling level is proportional to the marginal productivity 99 J.Temple, “Growth effect of education and social capital in the Oecd countries”, OECD Working Paper, 2000, page. 15
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difference in the results obtained”100. Recent works have assessed the long-run relationships between input and output factors over the period 1971-1998, based on improved time-series of human capital data and using new econometric techniques101.
Despite drawbacks and uncertainties, it can be concluded that the correlation between the measures of human capital and economic growth is able to capture effective contribution, notwithstanding its magnitude strictly depends on the basic assumptions and quality of data.
3.6.3 Innovation enabling factors: role of entrepreneurship
Entrepreneurship generally refers to enterprising individuals who display the “readiness to take risks with new or innovative ideas to generate new products and services”102. Empirical studies and correlation analysis suggest that the rates of entry and exit are positively correlated with economic growth. For instance, a survey based on 3,263 business executives in 47 countries, showed a generally positive relationship between higher level of per capita GDP and the level of entrepreneurship; in particular in countries such as United States, Ireland, Finland and Canada, with the exception of Japan103. Furthermore, there is some empirical evidence showing a link between changes in MFP (multi factor productivity) growth rates and administrative barriers to start-ups, as illustrated in the figure below.
Figure 6: Change in MFP growth rates and barriers to start-ups (1998)
Source: OECD “The new economy beyond the hype”
100 “The Well-Being of Nations. The role of Human and Social Capital”, OECD, 2001, page 29 101 A. Bassanini, S. Scarpetta “Does human capital matter for growth in Oecd countries? Evidence from pooled mean-group estimates, OECD Working Papers, 2001. The study found that on the long run one year of schooling would increase by 6% the GDP growth rate 102 OECD “Science, Technology and Industry Outlook”, 2001, Chapter 5 103 OECD “Science, Technology and Industry Outlook”, 2001, page 96
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The above graph shows the indirect stimulus to innovation caused by the entrepreneurship level, although the correlation appears rather weak (correlation coefficient –0.51). Given the importance of enterprise entry for economic performance, some reforms have been introduced in order to tackle a number of possible conditions that may impede a sufficient rate of entrepreneurship. The following factors can encourage the improvement of entrepreneurship104: i) removing regulatory barriers; ii) increasing access to venture capital; iii) implementing tax regimes that foster entrepreneurship; iv) facilitating use of stock options. In particular, we have to mention the importance of stimulating venture capital, and more in general, financial channels towards new innovative firms. The shaping of the European financial system in a way more “conducive” towards innovative firms and entrepreneurship has already been emphasized105. According to some analysts106, the financial issues can substantially explain the difference in the US growth path and innovative performances compared to the European patterns during the 90s.
3.6.4 Correlation and regression analysis: contribution of learning to economic performance
In order to support with further empirical evidence the findings on the contribution of innovation and learning to GDP growth, discussed in the previous paragraphs, a correlation and regression analysis has been executed, adopting the analytical approach recently presented in the OECD Report “Cities and Regions in the New Learning Economy” (OECD, 2001). The study has computed indicators of economic performance – in particular the GDP per capita – and found significant correlation of this with indicators of individual learning – i.e. educational attainment levels – and organisational learning – measured with two proxies of formal organisational learning such as per capita R&D expenditures and number of patents applications per million inhabitants – in 181 EU regions. We have replicated this kind of analysis on the basis of the data available for the USA and EU countries. The following list of individual and organisational learning related indicators from the SEAMATE database have been taken into account for the correlation and regression analysis:
104 OECD “,Science, Technology and Industry Outlook”, 2001, page 98 105 See, for instance, European Commission, “The EU Economy review 2000” European Economy, chapter 3 106 European Commission “The e-Economy in Europe: Its potential impact on EU enterprises and policies” e-Economy conference, page 11
110
• Educational attainment below secondary education 1999 (EDU LOWSEC). The educational attainment of the labour force captures the formal aspect of the human capital stock. Hence, this indicator has been included to represent the lack of the individual learning component. The graph shows the distribution of the lower educational level (below the secondary education) across a sample of OECD countries. An uneven distribution across countries it can be observed, i.e. from about 80% in Portugal to less than 10% in the USA.
• Educational attainment secondary education 1999 (EDU SEC). The distribution across the sample of OECD countries of the education attainment of the labour force with reference to the secondary education level is less unbalanced. About 50% of labour force in the USA, Denmark, and Sweden reach the secondary level of education. This percentage grows to 60% in UK, Norway and Germany, while for a group of countries ranges between 30% and 40% (Italy, Spain, France, Belgium, and Finland). Only for two countries, Greece and Portugal, the secondary level of education falls below 20%.
• Unemployment rate of young people (25-29 years) with tertiary education 1999 (UNEM TER 25-29). This indicator serves as a proxy of the capability of national labour markets to meet the supply of skilled workers. It measures in fact the unemployment rate of the young labour force (between 25 and 29 years) with a tertiary level of education. The tertiary level includes both the first stage of tertiary education, which
EDUCATIONAL ATTAINMENT '99
0
20
40
60
80
100
NOR US A DEN S G NL FIN B UK F I ES EL P
Up to secondary educ.-% labour force 25-64 -
EDUCATIONAL ATTAINMENT '99
0
10
20
30
40
50
60
70
NOR US A DEN S G NL FIN B UK F I ES EL P
Secondary educ.-% labour force 25-64 -
UNEMPLOYMENT RATES '99
0
5
10
15
20
EL I ES F FIN P G S W B US A NL DEN
Tertiary educ.-% labour force 25-29 -
111
provides the level of education required for entry in professions with high skills requirements, and the second stage of tertiary education, which prepares for advanced research posts in government and industry. Hence, it can be also interpreted as a measure of the “individual learning” component of the innovation process to the extent that indicates the proportion of high-skilled workers actually involved in the human capital stock. The graph clearly shows the different labour market characteristics across the OECD countries, i.e. lower young skill workers unemployment rates in the Nordic countries and the USA and higher unemployment rates in Greece, Italy and Spain.
• Unemployment rate of people aged 30-44 years with tertiary education 1999 (UNEM TER 30-44). This indicator represents the skilled workers’ unemployment rates, in the intermediate zone between the younger and the older range of labour force, i.e. 30-44 years. The USA, Norway, Denmark, UK, the Netherlands, show in fact lower level of unemployment, about 2%. On the other hand, in Greece, Italy and Spain the unemployment rates of skilled workers range between 6% and 8%.
• Participation rates for population 55-64 years with tertiary education 1999 (EDU TER). This indicator shows the labour force participation rates of adult population between 55 and 64 years (older workers) with a tertiary level of education. The distribution across the sample of OECD countries is quite homogeneous, with lower values in Belgium and Greece, i.e. about 45%, and the higher in the USA and a group of Nordic countries (Denmark, Sweden, Norway), with values ranging from 70% to 80%.
UNEMPLOYMENT RATES '99
0
2
4
6
8
10
NOR US A DEN S G NL FIN B UK F I ES EL P
Tertiary educ.-% labour force 30-44 -
EDUCATIONAL ATTAINMENT '99
0
20
40
60
80
100
NOR USA DEN S G NL FIN B UK F I ES EL P
Tertiary educ.-participation rates 55-64 -
112
• Triadic patents families (PAT) Patent-based indicators provide a measure of the output of a country’s innovation activity: its inventions. Hence, it can be considered a product of the organisational learning. Since the traditional patents indicators suffer of various sources of bias, in particular the weaknesses in international comparisons, the patent families indicators allow international comparability of patent filed in the European, American and Japanese area (from here the adjective “triadic”). The distribution of patents families across OECD countries shows higher values in Sweden (about 75 per mill. inhabitants), Germany, Finland and the USA (about 50). Italy and Spain stand at the bottom with less than 10.
• Gross domestic expenditure on R&D (GERD) The indicator represents the resources allocated at country level to R&D, without considering the origins of funding. It is an indicator of the financial input devolved to organisational learning processes fostering innovation. Possible biases in the international comparisons arise from the different national coverage of firms, particularly in the service sector. The graph shows the higher value for Sweden and Finland (both over 3% of domestic product) and the USA (2,5%). Germany, France and Denmark follow with value ranging approximately 2% and 2,5%. Italy and Spain stand on the bottom, with resources devoted to R&D corresponding to 1% of gross domestic product.
• Business enterprise expenditure on R&D (BERD) This indicator represents the expenses of the business sector for R&D activities, measured as percentage points relatively to the industry sector output. As for total R&D expenditures related to the gross domestic product, the Sweden and Finland lead the classification with about 5% of domestic product of industry
TRIADIC PATENTS FAMILIES
0
10
20
30
40
50
60
70
80
CAN USA B DEN FIN F G I ES S UK
Per million population 1995
DOMESTIC R&D EXPENDITURE
0
0.5
1
1.5
2
2.5
3
3.5
4
CAN USA B DEN FIN F G I ES S UK
as % of GDP 1999
BUSINESS R&D EXPENDITURE
0
1
2
3
4
5
CAN USA B DEN FIN F G I ES S UK
% of domestic product of industry 1999
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(Sweden) and about 3% (Finland). Some of the above indicators have been used in the context of two separate regression models, aiming respectively to find a correlation between: 1. GDP per capita in the year 1999 and five indicators of individual learning: shares of
population with and without a secondary level of education, unemployment rates for people with tertiary education (high-skilled workers) in three age groups – young workers (25-29), mature workers (30-44), older workers (55-64).
2. Labour productivity growth between 1996 and 1999 and three indicators of organisational learning: number of patent applications per million inhabitants, gross domestic expenditure on R&D (GERD), business enterprise expenditure on R&D (BERD).
The following paragraphs discuss in turn the models adopted and their results. 3.6.4.1 Contribution of individual learning to economic performance
There is a considerable body of literature concerning the relationships between individual learning, i.e. schooling, and economic performance both at individual level, i.e. involving the relationships between schooling and earning, and at aggregate level, i.e. measuring cross-country regression between education and economic performance. Moreover, with reference to the cross-country studies, although a robust finding of the literature found positive correlation between educational attainment and GDP levels, the same does not occur regarding the change in human capital and schooling and growth107. Recently, OECD researchers have carried out a contribution leading to the estimation of the evolution of human capital over time, i.e. the average years of education of the working age population between 1971-1998, based on more reliable data108. Thus, taking into account these uncertainties, the estimation of individual learning contribution to economic performance will assume here as dependent variable the GDP per capita in 1999, instead of GDP growth rates.
107 Zvi Griliches (2000) suggested a possible answer to this puzzle considering that much of the growth of human capital was absorbed in the public sector. The difficulties in measuring the productivity rates of workers employed in the public sector explain their absence in the growth output statistics. 108 A. Bassanini, S. Scarpetta “Does human capital matter for growth in OECD countries? Evidence from pooled mean-group estimates, OECD Working Papers, 2001.
GDP PER CAPITA 1999
0
5
10
15
20
25
30
35
40
k$ US
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Five variables have been considered as explanatory factors of the GDP per capita level:
• Unemployment rate of young people with tertiary education 1999 (UNEM TER 25-29)
• Unemployment rate of people aged 30-44 years with tertiary education 1999 (UNEM TER 30-44).
• Participation rates for population aged 55-64 years with tertiary education 1999 (EDU TER).
In such a framework, the GDP per capita level depends on the level of education attainment of the population, integrated with variables indicating the labour market capability to absorb the skilled workers with tertiary level of education. The latter variables have been introduced to investigate the effects of the different national labour markets on the performance of OECD economies. The growth pattern of the most developed OECD countries seems in fact strongly related to their capability to absorb skilled workers in high-tech economic sectors. For instance, the next table shows for a sample of OECD countries the unemployment rates of young labour force (25-29 years) in the year 1999, comparing those of the lower skilled workers, below the secondary level of education, with those experienced by the higher skilled ones, i.e. with tertiary level, and measuring the difference under the column “gap”.
Unemployment rate Unemployment rate Gap
below sec. edu. 25-29 tertiary level 25-29
A B (A-B)
France 21.1 7.5 13.60
Germany 13.8 2.4 11.40
Belgium 12.8 2.3 10.50
Sweden 11.8 2.3 9.50
Canada 13.1 4.2 8.90
Finland 13.2 5.9 7.30
Australia 9.4 2.1 7.30
Denmark 7.6 1.8 5.80
United States 6.5 1.9 4.60
Spain 17.3 13.4 3.90
Netherland 5.1 1.9 3.20
Portugal 4.2 3.2 1.00
Italy 12.5 16.7 -4.20
Greece 12.3 17.5 -5.20
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It is important to note that in the great majority of the countries surveyed in the table, the gap is positive as expected, meaning that unemployment is on average lower for the high-skilled young workers than for low-skilled one. A notable exception to this rule is provided by Italy (- 4,20) and Greece (- 5,20), whose labour markets de facto absorb more quickly unskilled workers. The regression model adopted is the following109: GDP = a + b*EDU LOWSEC (X1) + c*EDU SEC (X2) + d*UNEM TER 25-29 (X3) +
e*UNEM TER 30-44 (X4) + f*EDU TER 55-64 (X5) The matrix of correlation coefficients is as follows:
LOWSEC). Variable. N° 2 Educational attainment secondary education 1999 (EDU SEC). Variable. N° 3 Unemployment rate of young people with tertiary education 1999
(UNEM TER 25-29). Variable. N° 4 Unemployment rate of people aged 30-44 with tertiary education
1999 (UNEM TER 30-44). Variable. N° 5 Participation rates for population 55-64 years with tertiary education
1999 (EDU TER). As expected, an high negative correlation is observed between GDP per capita and the below secondary education level of attainment (-0.89), as well as an high positive correlation with the secondary education level of attainment (+0.83). The unemployment rate of young population with tertiary level of education is negatively correlated with GDP both with reference to the younger range between 25-29 years (-0.64) and to the older 30-44 (-0.54). The labour force participation rates for population between 55 and 64 years with tertiary attainment of education level show positive but more weak correlation with GDP (+ 0.50). The above results are broadly consistent with the above mentioned study carried out by OECD on cities and regions in the new economy context110. This study, based on
109 further details concerning the parameters of the regression model are given in Appendix 1.
116
correlation analysis between GDP per capita level and individual and organisational learning indicators for 181 EU regions, found a negative correlation (-0.60) between GDP and primary educational attainment and a positive one (0.58) between secondary educational attainment and GDP level. On the same track of the present outcomes, the OECD correlation analysis of GDP with tertiary educational attainment is weaker, but positive. The negative correlation found above between GDP and the unemployment rates of the population with tertiary education - both ranging from 25 to 29 years and from 30 to 44 years - confirms that GDP levels are positively correlated with higher employment rates for the skilled workers than for the unskilled ones. The regression equation estimated with the standard least squares method, fitting the data observed for US and 11 EU countries111, is the following: Y = 31.386 - 0.330X1 – 0.083 X2 - 0.0087 X3- 0.698 X4
+ 0.149 X5
The multiple regression coefficient R2 is equal to 0,89 The following graph shows the good adaptation between the observed value of GDP level and the corresponding theoretical values obtained through the regression equation. Generally, the gap is contained trough the range ± 10%, with the exception of Italy and Greece, where the gaps rise up respectively to +25 and -27% 3.6.4.2. Contribution of organisational learning to economic growth
As explained in this Deliverable’s Chapter 1, organisational learning refers to the process of formal and tacit knowledge created and diffused through the interaction
110 OECD, “Cities and Regions in the New Learning Economy”, Paris, 2001 111 Only countries with data for all the variables are included in the regression models.
GDP per capita 1999
0.0
5.0
10.0
15.0
20.0
25.0
30.0
35.0
40.0
USA DK S G NL FIN B F I ES EL P
Observed value
Theoretical values
Individual learning
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within and between institutions, i.e. firms, universities, R&D institutes, governmental agencies, etc. The following indicators have been considered as proxy variables of the aggregate organisational learning activities in the national economies:
• Triadic patents families (PAT), indicating the presence of relevant innovative activities – 1995 data, per million of inhabitant.
• Gross domestic expenditure on R&D (GERD), concerning the national expenditure, as share of GDP at 1999, in R&D.
• Business enterprise expenditure on R&D (BERD), representing the R&D expenditure from business enterprises in 1999.
The relationships of R&D expenditures with economic growth and productivity rates have been discussed in several studies and researches (see also infra, paragraph 3.3.2 for detail). In particular, the recent OECD report, Science, Technology and Industry Outlook (2001) has adequately stressed the linkages between R&D activities and productive growth, both at micro and macro level. Following this approach, the average labour productivity growth rate between 1996 and 1999 - a period where the effects of the “new economy” over economic growth rates have been remarkable - has been selected as dependent variable for the regression analysis. The matrix of correlation coefficients between the average labour productivity growth and the selected independent variables is shown below.
Dep.variable Var. 1 Var. 2 Var. 3
Dep.variable 1.00 0.71 0.77 0.65
Var. 1 0.72 1.00 0.95 0.94
Var. 2 0.77 0.95 1.00 0.98
Var. 3 0.65 0.94 0.98 1.00
• Variable. N° 1 Triadic patents families (PAT)
LABOUR PRODUCTIVITY
GROWTH 1996-99
0
0.5
1
1.5
2
2.5
3
3.5
FIN USA G S F UK B CAN DEN ES
Average growth rates
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• Variable. N° 2 Gross domestic expenditure on R&D (GERD)
• Variable. N° 3 Business enterprise expenditure on R&D (BERD) High positive correlation coefficients can be observed between the average growth rate of labour productivity and the number of patents per million of inhabitants (+0.72), on the one hand, and the overall expenditure in R&D (GERD), i.e. from private and public funds, on the other hand (+0.77). A positive correlation coefficient, although slightly lower (+0.65) is also observed in the case of the enterprise R&D expenditure (BERD). The regression model adopted is the following112:
Average productivity growth rate= a + b*PAT (X1) + c*GERD (X2) + d*BERD (X3) The regression equation estimated with the standard least squares method, fitting the data observed for US and 10 EU countries113, is as follows:
Y = -1.478 + 0.007X1 + 3.109X2 - 1.919 X3 (4)
The multiple regression coefficient R2 is equal to 0,85. The relationships between the observed average labour growth and the corresponding theoretical values are shown in the following graph. The graph shows an unfitting adaptation of the theoretical values with the observed ones, included in the range of ± 15%, with the notable exception of UK, Canada, Italy and Denmark, where the gaps rises to ± 30-50%. 3.6.4.3. Individual and organisational learning: a comparison
112 further details concerning the parameters of the regression model are given in Appendix 1. 113 The regression models take into account only countries with non-null data for all the variables.
Labour productivity growth rate 96-99
0
0.5
1
1.5
2
2.5
3
3.5
FIN USA G S F UK B CAN DK I ES
Observed value
Theoretical values
Organisational learning
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The correlation analysis indicates that the independent variables selected from the set of IST indicators (see infra Chapter 1) show a consistent behaviour with GDP and labour productivity growth rates, as suggested by literature. Indeed, concerning the ”individual learning”, i.e. the variables representing the human capital endowment, the higly negative correlation between between the educational attainment below the secondary education and GDP growth rates has already been pointed out in similar excercises114. On the other hand, considering the influence of “organisational learning”, the positive correlation between R&D business expenditures and labour productivity growth rates was signalled in the econometric analysis conducted on a panel of 16 OECD countries in 2001115. With regard to the regression analysis, the outcomes are less clear-cut. In the case of the variables representing the individual learning, the higher regression coefficient (0.89) ensures to the regression model a good predictive capability (narrow gaps between observed and theoretical values), in line with the findings from literature. According to the regression model, the yearly increase of 0.1% in the secondary educational attainment, and the tertiary-skilled occupied workers could determine an average GDP per capita growth by 1.1%, which accounts for approximately 20% of growth in total output along a period of twenty years. This outcome is similar to the one reported by Englander and Gurney116, which found a contribution due to the growth of human capital for the G7 economies from 10 to 20 per cent of total output (1960-1980). Diversely, in the case of “organisational learning” variables, the regression model provides a less satisfying regression coefficient (0.85), which can also be explained by several statistical problems in finding relationships between labour productivity and investment in technology and research. One of the main problems is related to the time needed for investment in technology and R&D to materialise in productivity increase.
114 See OECD, “Cities and Regions in the New Learning Economy”, Paris, 2001, page 37 115 See OECD “Science, Technology and Industry Outlook”, Paris, 2001, page 55 116 Quoted in J.Temple, “Growth effect of education and social capital in the Oecd countries”, OECD Working Paper, 2000, page. 15
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4 – IST first generation scenarios In this section we outline and analyse three IST scenarios conceived under assumptions about the future that make them recognisable and interesting: A. A first scenario, termed "Business as Usual to 2010", for the 12 variables listed in
Sect. 4.1 below takes as a starting point their 2001 actual values presented in Table 14. From these we generate the values of the same variables listed in Table 15 - Business as usual Scenario to 2010 extrapolating historical trends in the last decade.
B. A second scenario, termed "Positive to 2010", for the same 12 variables again starts
from the 2001 actual values. From these we generate the values listed in Table 16 - Positive Scenario to 2010 fanning up the historical trends previously used. The rationale of the more favourable growth rates is discussed case by case and linked to the corresponding factors or drivers, resulting from the contents of previous chapters.
C. A third scenario, termed "Negative to 2010", for the same variables again starts
from the 2001 actual values. From these we generate the values listed in Table 17 - Negative Scenario to 2010 fanning down the historical trends used to build Table 15. The rationale of the worse growth rates is discussed again case by case and linked to the corresponding factors or drivers.
The genesis of factors underlying the scenario, presumably with a cause-effect link, is not too relevant to the outcome (and would be too hard to identify). In a scenario (NOT a model) only the end results have to be interpreted and discussed. Indeed, the purpose of these alternative scenarios is to present common sense reasoned projections that:
1. illustrate plausible outcomes and supply upper and lower extremes just posited fanning out from the hypothesis of continuation of current trends (Business as Usual) to try and vaticinate the best and the worse that can be expected;
2. thereby provide a “rule of thumb” outcome to compare with second approximation scenarios and the more detailed modelling from WP5, and
3. provide some assumptions to the general context of modelling work of WP5. The methodology underlying this scenario exercise is discussed in Sect. 4.1 below. In Section 4.10 the scenarios are compared to those proposed by EITO: there is no identity, but the comparison shows our exercise is plausible.
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4.1. Methodology of Scenarios Building - intended as a Preview and an Integration of Modelling Proper The very decision of recurring to scenarios formulation stems from the consideration that no operational tools are available apt to compute future complex technological or socio-economic situations. It is, however, imperative to try and produce as good forecasts as possible based on trend analysis and on well known sophisticated projection tools. E3ME is one of these tools drawing its rationale and raison d'être from the econometric modelling approach. However, econometric modelling does not purport to define deterministic mechanisms enabling to formalise robust predictions. It embodies, though, refined procedures to interpret available empirical findings and time series and to project the corresponding trends. In this way are produced plausible, coherent, quantitative descriptions of future societal parameters. This is the content of the analysis and of the projections carried out in WP-5 using, as noted, the E3ME model. Future studies and forecasting exercises often rely on apparently naive definitions of trends fanning out from the past into a business-as-usual continuation from which sets of better and worse hypotheses are derived. It can be argued, in fact, that even sophisticated macroeconomic and System Dynamic models can hardly do better than analysing probabilities (subjective?) of more optimistic and more pessimistic outcomes. Collection and analysis of IST relevant variables and indicators, as carried out in the previous chapters of this Deliverable, were instrumental in building up a robust insight into:
• Future developments of ICT proper as conditioned by:
− Cultural and economic prerequisites
− Main cause-effect relationships in the web of socio-economic impacts
• “Digital divide between nations” being more relevant at the macroscopic level than the divide between the digitally literate on one hand and individuals who are old, disabled, living in remote areas or subjected to gender or racial discrimination
• Predictability of continued economic success of nations investing heavily in high level education and dissemination of culture.
The above considerations inspired the decision to consider only 12 indicators grouped in 3 classes: Prerequisites, IST variables and Socio-economic impacts:
Prerequisites
1. Investment in R&D as a proportion of GDP 2. Number of researchers as proportion of the total workforce 3. Proportion of population aged 25-64 having upper secondary schooling
IST variables
4. Share of ICT-producing and ICT-using sectors in overall value-added
5. Number of internet users 6. Proportion of companies engaging in purchasing via e-commerce
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7. Proportion of companies engaging in sales via e-commerce 8. Share of ICT manufacturing in total manufacturing employment 9. Value of ICT market [measured for EU15 aggregate only]
Socio-economic impacts
10. GDP 11. GDP per capita 12. Unemployment rate
Seven countries among the EU15 have been considered to be more representative or paradigmatic for the purpose of building IST scenarios: UK, France, Germany, Finland, Ireland, Italy, Portugal. The chosen set of 7 countries accounts for 2/3 of EU15 activity. The countries are divided in three paradigmatic groups: innovators (Finland, Ireland), advanced (UK, France, Germany) and laggards (Italy, Portugal).
4.1.1. Distinguishability of scenarios
Scenarios analysed must clearly set out assumptions about the future that make them recognisable and interesting. In general a scenario will be very distinctive, if it is based on the hypothesis of insurgence of a clearly recognisable trend which has marked consequences cascading from a given sector into a number of other sectors. The genesis of these upstream trends (possibly taking the form of step functions) may not be very relevant to the outcome (and in most cases would be too hard to reconstruct), while only the end results have to be interpreted and discussed. For example, if we describe a situation in which GNP is halved over a 5 years period, we are presenting a deep recession scenario. Discussing the causes and the consequences of this single event can be quite instructive. Instead a very precise description of a set of assumptions that differ slightly from situations or trends previously recorded, do not provide significant new insights. This consideration applied, for example, to GPAT, the Global Policy Analysis Tool, developed in 1975 by M. Mesarovic and E. Pestel to facilitate users' access to their global world model. In the case of analysis of the future of the energy sector, users were given triple choices of values to be attributed exogenously to 10 key variables: oil reserves estimates (2000, 2500, 3000 Gbarrels), oil demand reduction with price increase (.45, .225, .15), oil supply increase with price increase ((1, .75, ,5), monetary recycling (efficient, fair, poor), etc. The model would, then, compute hopefully plausible projections based on a single choice. A user had the impression of disposing of a very wide latitude of choice, since 310 = 59,049. Actually it was quite hard to distinguish between two choices based on a single different value assumed for one of the 10 parameters and hence between the two outcomes resulting from the model's operation. The choice of parameter values or trends for the different IST scenarios – business-as-usual, positive and negative - was made as shown in the following table. The consequences were attributed to corresponding countries and variables as described in the following sections.
Social unrest and/or trade conflicts stable Increas. Decreas.
Societal and economic stagnation due to terrorism stable Increas. Decreas.
4.1.2. Non gratuitousness
New scenario developments have to be chosen among the multitude of those which can be reasonably expected to take place. They must not be grabbed out of thin air. We should concentrate our efforts on analysing new events which reasonable and learned thinkers consider as likely and relevant. We should not spend valuable time to derive the ultimate consequences of a new - positive or negative - Weltanschauung being adopted by large masses of people, as this type of process would develop only over the long term. Strong socio-economic trends have already begun which will deeply affect the future everywhere. Among these: downsizing, outsourcing and chronic unemployment, privatisation and market dominance with adverse effects on service levels to less favoured strata of society, financial crises.
4.1.3. Adequate analysis of main scenario feature(s)
For a scenario to be useful, it needs to be covered by a text explaining the rationale for the imagined sequence of events and to include explicit specifications of assumptions made also concerning cause-effect relationships and explanations of the main consequences of assumed events. It is not enough to define it simply by means of a title. A full employment scenario should explain what decisions, interventions, implementations are posited and explain why these will result in full employment.
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4.1.4. Pedigree - or similarity to well known processes in the past
We will expect new processes of variation to be similar to those which took place in the past. This means that well established, previously successful explanations should be given more credit than those based on postulated mechanisms. A good case in point is represented by energy sources substitution patterns. These are well known to develop both in the growth and in the decline phase following logistic curves with fairly uniform time constants. The very constancy of these laws characterises a credible pedigree of the quantitative analysis in that it has been successful in a large number of cases over a period of time of about two centuries. Obviously we deal here with debatable issues and methods. It is easy to utter words of caution against ideological approaches. We must also remember that one man's tool of the trade may appear to another man as an idee fixe more than an ideology and a to a third man as sheer folly. This is a normal situation whenever highly complex and debatable questions are on the carpet. 4.2 - Scenario derivation from current trends Some trends are already well known. Positive ones are connected with the very fast penetration of hardware and network connections in all OECD countries. But the growth of ICT is uneven. There have been frequent births and demises of dotcoms, downsizing and chronic unemployment in the old economy sector, scarce supply of experts in high-tech and ICT (although, as already noted, this situation is now much less critical partly due to increased education/training actions, partly due to decreased demand) , privatisation and market dominance with adverse effects on service levels to less favoured strata of society, financial crises, balloon growth of stock markets followed by dramatic downfalls (Enron, Worldcom). Positive and negative trends are simultaneous: each inspires positive or negative features. The impacts of ICT on economic growth during the 90’s have been analysed in several studies, largely quoted in the present Deliverable. Some of them have tried to sketch possible scenarios in order to forecast the impacts on economic growth in general, or towards specific aspects, i.e. employment level, if the “new economy” features continue to operate across the European countries over the next ten or twenty years. A brief summary of recent scenarios, without the character of exhaustiveness, should include at least the following studies: 1. "Impact of Technological and Structural Change on Employment" is a study
published in March 2002 by ESTO, the European Science and Technology Observatory. It models the impacts of technological innovation on trade, economy, employment using the ASTRA (system dynamics) and GEM-E3 (General Equilibrium Model) models, which disaggregate the industrial and socio-economic processes and variables in considerable detail. The variables considered include: technological development (not exclusively ICT), trade policies, labour supply,
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skills (education and training), workplace organisation, productivity, consumer demand. The study generates projections of GDP and employment at the year 2020, according to three different scenarios: a Uniform scenario, where R&D spending was increased at uniform rate throughout the economic sectors; a Diversified scenario, where R&D spending was allocated to sectors which have showed strong performance (chemicals, manufacturing, transport equipment); and a Concentrated scenario, where the increases in R&D were concentrated on advanced technologies (electronics, telecommunications, genetic engineering, etc);
2. The STAR Project, “Socio-economic Trends Assessment for the digital
Revolution”, estimates the contribution of ICT capital investments in Europe from the point of view of their impacts on employment growth across European countries. According to the various assumptions concerning national labour markets and wage elasticity, three scenarios have been proposed: an Optimistic scenario where the patterns of the second half of the 90s are generalised in the future; a Conservative scenario where the patterns of the 90s are taken as reference for the impacts analysis, and a Full Convergence scenario, where all countries achieve the same ICT contribution to growth of the USA. STAR’s optimistic scenario foresees the creation in EU15 of 865,000 jobs/year due to ICT and their pessimistic scenario calls for 478,000 jobs/year due to ICT. Both expectations appear to be too rosy. STAR’s Reports appear to have been produced in the year 2001, and they have relied largely on data from WITSA (World IT Scientific Alliance). This may account for some preliminary conclusions reached in particular in STAR's A1 Report "Growth and employment effects of ICT" (prepared by Daveri of Parma University) to the effect that France and Germany lag in ICT behind Northern EU Nations to the same extent as Italy and Greece, whereas in SEAMATE our findings are more favourable to France and Germany. In any case the mentioned A1 Report proposes many empirical equations, and also supplies tables of GDP growth, ICT spending and investment, ICT induced growth, and elasticities relevant to the cognate SEAMATE objectives.
3. The EU Economy Review, 2001 by the EC, Directorate-General for Economic and
Financial Affairs, estimates the ICT investment contribution to output growth and Total Factor Productivity growth rates in the USA and EU member states according to explicit assumptions concerning ICT price decline and elasticity of substitution between ICT capital and other factors of production. The Optimistic scenario is based on the same ICT price decline between the USA and EU member countries and an elasticity of substitution equal to –1.5, the Caution scenario is based on an ICT price decline equal to half the USA level and a rigid elasticity of substitution (-1) and an Intermediate scenario adopts the same elasticity of the optimistic scenario and an ICT price decline in EU equal to half the USA level.
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4. Finally, the contribution by W.Roeger117 simulates the impacts on relevant macroeconomic variables (GDP, consumption, investment, employment and wages) arising from a rapid technological change in the production of ICT over a period of 50 years. Three scenarios are provided on the basis of the following assumptions: Large technological shock represented by an increase of 7% of TFP in the EU countries (11% in the USA); Small technological shock with 3.6% of TFP growth rate in the EU countries and a third scenario with No acceleration of TFP growth rate arising from ICT investment.
4.3 - "Follow the leader" situations From the review and analysis of EU15 data it is apparent that some (Northern) European countries have been more successful than others in terms of GDP growth as well as in growth of productivity, employment and effective recourse to ICT. One way to forecast a positive scenario is to assume that laggard countries will follow the example of more successful innovative ones. The positive scenarios for these (Southern) countries may, then, be imagined to develop along patterns and reaching milestones previously achieved by leader countries. Successful development of laggards may be a positive factor reinforcing the success of the leaders. The same logic, on a wider scale, is usually applied to compare overall EU performance with the US and Japan economies. 4.4 - Impact of exogenous factors It is hard to separate endogenous from exogenous factors in a situation where multiple feedback loops are at work. There may be factors which are totally external to the ICT sector, but which exert indirect influences. These will not be analysed individually as their inherent probability is hard to judge and as their socio-economic impacts would not be mediated through the influence on ICT. Analysis of cause-effect chains will not be belaboured since the corresponding mechanisms are too complex to be explained by means of scenarios. As illustrated below, IST shorthand scenarios are outlined by fanouts of recent historical trends extrapolated at the same rate or at a faster or slower rate. Among negative factors:
• terrorism inspired by non EU15 countries or immanent in Europe
• immigration of masses of uncultured people from Africa and/or Asia (see events of unchecked immigration (prompted by demand for labour, asylum to persecuted persons, etc.) from Commonwealth (Indian continent, West Indies) to UK which later led to drastic limitations of quotas)
• Near East conflicts expansion
• major international war
• major international economic depression
117 W.Roeger “The contribution of Information and Communication Technologies and Communication Technologies to Growth in Europe and the US: A Macroeconomic Analysis, EC, DG Economic and Financial Affairs, January, 2001
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• climate change due to global warming
• burst of financial bubbles connected to top management unethical behaviour and technological ill judgements, like overinvestment in wideband fiberoptics networks not followed by adequate demand
• ageing population Instead positive factors can inspire the scenario's structure more directly. Among these:
• innovative governmental industrial policy for new enterprises
• innovative Government and private education policies
• total quality management tuition introduced in all schools
• founding new excellent institutes for advanced studies and research
• establish mass media cultural programs (all levels, all targets)
• redesign careers (retraining and new professions after retirement)
• train high level scientists, professionals, experts and practitioners to communicate their knowledge directly and through the media
• integrate the above steps internationally - within Europe and especially outside: in Eastern Europe and in the so called Third World
• plan investments in all sectors (economy, industry, administration) to obtain results through education/knowledge diffusion rather than through direct short term action programs
• immigration of highly trained professional from Eastern new access countries or from Asia.
4.5 - Negative scenario easier to define A negative scenario, pessimistic enough to represent a marked difference to any optimistic projection and also to a business as usual base scenario, is less relevant than positive ones. This is due to the fact that negative expectations entail an involution and a return to the past, i.e. to situations where ICT was less present and does not affect other sectors nor society at large. Since these situations are well known, less effort should be exerted to analyse them. Consequently we devoted to the negative scenario about half as much time in the analysis work compared to the positive one. The latter contains more uncertainty - made of challenges and opportunities and also of risks (not exploiting adequately existing chances). 4.6 - The positive and negative EU15 overall vision Scenarios are outlined to 2010 – the year chosen in the e-Europe Action Plan, launched by the 2000 Lisbon European Council, to render Europe the most competitive knowledge based economy and society in the world - in a business-as-usual, a negative and a positive projection. As noted in Sect. 4.1 above, the variables considered are subdivided in 3 groups:
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Prerequisites
• Investment in R&D (% of GDP)
• Researchers/000 workforce
• % of the population aged 25-64 with upper 2ary education IST Variables
• ICT share in value added (Sum total of manufacturing and services both in ICT producing sectors and ICT using sectors) [aggregated value for EU15]
• No. of Internet users (M)
• % companies buying online
• % companies selling online
• ICT manufacturing share in total mfrg.employment
• ICT market value [aggregated for EU15] Socio-economic Impacts (3 variables also retro-acting on above variables)
• GDP (G€)
• GDP per capita (k€)
• Unemployment Other relevant variables are: literacy, education, internet hosts numbers, ICT Hardware penetration, revenues from ICT activity and from E-commerce, number of workers tele-working, E-learning, ICT Investment and Weight of Intangibles. At this initial stage in the work, however, it was deemed best to concentrate on the above list to present the analysis in a more agile form. The format of the scenarios is discursive since, as discussed above, available data and causal relationships are too vague to suggest formal statements. Available data and time series are taken as initial boundary conditions, but modified in order to satisfy common sense and to mesh with the vision of participants in the study. The latitude thus obtained aims to take into account factors and assumptions only available through the intuition of participants. We cannot hope to grasp counterintuitive situations (which System Dynamics contends it can identify and explain). But we can discuss and resolve contradictions inherent in current situations and their foreseeable developments. Note, for example, that skills shortage is per se a negative factor, but it entails that demand for skilled professional is high which denotes a positive scenario. No skills shortage may well be caused by a drop in demand for skilled professionals due to an ICT slump. The conclusions reached in the course of definition of the scenarios are in any event quantified for the sake of concreteness. From projections disaggregated by individual countries, global EU15 projections have been built. We started from the current situation of European innovation as depicted in the EC DG Report "Key Figures 2001 -Towards a European Research Area, Indicators
for benchmarking of National research policies" and, respectively, in the OECD Science, Technology and Industry Outlook and Scoreboard.
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From this and other sources we built the table below accounting for 2/3 of EU15 activity based on 7 countries: 2 innovators (Finland, Ireland), 3 advanced (UK, France, Germany) and 2 laggards (Italy, Portugal) and listing the 12 variables mentioned above.
Table 14: 12 Indicators Data for 2001 (*)
FIN IRL UK F D I P USA
Population (M) 5.1 3.6 58.9 58.4 82 57.4 9.9 286.5 Investment in R&D (% of GDP)
(*) ICT total market value aggregated for EU15: 537 G€ (2001). (**) Sum total of manufacturing and services both in ICT producing sectors and ICT using sectors
From this we have built a business-as-usual scenario, a negative and a positive one - all three projected to 2010 (the projection to 2005 is also interesting, but it is omitted at this stage as it would just add intermediate values with scarce substantive meaning). The scenarios presented here may be useful to support the choice of variables and assumptions to assess the relevance of adapting to Information Technology (e.g. using the E3ME model in WP5), and also to assess the relevance of mental models developed without using robust formal tools. 4.7 - Outline of a Business-as-usual Scenario to 2010 This is a business-roughly-as-usual vision. It consists of a continued growth at a slightly slower pace than in the past: no bumps, no breakthroughs except technical ones which however do not find wide acceptance or do not produce major socio-economic impacts. This extrapolation is not very interesting and can be produced almost mechanically without recourse to a deep conceptual analysis. The slowdown in the overall economy in 2001 appears to be partially offset by recent signals of an economic growth in the US corresponding to an annual rate of 5%. The signals, however, are mixed. Therefore in the business-as-usual scenario:
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the main assumption is that growth from 2002 to 2010 will be somewhat slower
than it was up to 2000, but livelier than in 2001. GDP and GDP p.c. are
assumed to increase over the period by 13% for Finland and Ireland, 10% for
UK, France and Germany, 8% for Italy and Portugal and 16% for US.
Upstream variables (Investment in R&D, number of researchers, education of
population) are postulated to hover around present values with modest
increases in laggard countries and more lively behaviour of innovator
countries. The gap between the 2 groups increases and markets don't show any
trend towards integration and effective widening. Growth of the number of
Internet users agrees with the forecast indicated in Annex I and E-commerce is
assumed to be strongly correlated with Internet use.
Table 15: Business as usual Scenario to 2010 (*)
FIN IRL UK F D I P USA Investment in R&D (% of GDP)
(*) ICT total market value aggregated for EU15: 1,000 G€ (2010) (**) Sum total of manufacturing and services both in ICT producing sectors and ICT using sectors
4.8 - Outline of a Positive Scenario to 2010 This positive scenario projects a future in which high-tech innovations are readily accepted by all advanced countries and also they seep to LDC's since international co-operation is assumed to get to centre stage entailing:
• establishment of many new private polytechnics and institutes of advanced studies to emulate
• consortia of high-tech industries committed to global cultural marketing
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• international subdivision of labour to avoid overlapping and duplication and foster integration
• open systems agreements to stave off commercial wars and attempts to corner the market on proprietary items and solutions
• financing of new R&D public and private efforts co-ordinated and controlled to blueprint significant highly efficient development. Government initiatives in this context obviously should not take the form of state planning (which has performed so poorly in Eastern former centrally planned economies). They should, instead, be integrated at the European level (in the direction in which the 6th Framework Programme appears to be headed) setting goals in agreement with the Lisbon declaration [EU to be N°1 in ICT!]. The importance of this factor has to be stressed and illustrated. The goal is certainly not to let Government (nor the EU) manage the ICT industry: it is to have EU and National Governments co-operate and lead to define ambitious goals and then stimulate and finance industry to implement state of the art innovation. This is exactly what happened (admittedly: especially for defence) in the USA in the second half of last century. The Federal Government (and often the Pentagon directly) blueprinted needed innovation and breakthroughs in technology (and notably in ICT) and financed huge programs which reached successfully the goals that had been set.
The above are then the unleashing factors of the positive scenario and from their assumption we deduce the contents and times as follows. As in the case of the negative scenario to be examined in the next paragraph, it does not appear that much can be learned by reasoning on the possibility that ICT growth rates increase simultaneously in all EU15 countries. This scenario attempts to deduce the consequences of a general factor or a set of general causes affecting all EU15 states. It appears reasonable to think that laggard less developed countries would be the first to benefit from a general improvement of the cultural and research climate. For them it is a lot easier to improve, exploiting the impact of the above initial positive factors which entails an upgrading of their low innovation rate, social efficiency, knowledge creation, influencing in turn productivity, GDP, demand for high-tech products (SW and HW). These positive events would then influence in turn the absorption of ICT and industrial output from leader countries which, in turn, will follow up the path to renovation, widening of markets (and scale economies), inter-fecundation and mutual enhancement of inventions and innovative practices. Sequences of the following types of events will ensue:
• Improvement in the skill of high-tech/ICT companies to integrate development, reach agreements to establish standardisation of HW and SW (thereby improving the efficiency of operators and of firms - especially SMEs), steer the re-conversion of old economy firms to new fields also transferring mature, well established technologies to LDCs (the economy of which improves so that international trade increases)
• Co-operation of public bodies (national and international) and private companies to define prices for natural resources, services in all countries in an improved way and also to allocate financial and human resources in an optimised way
• New forms of social contracts in industrialised nations old and new
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• dissemination of culture through schools, community colleges, media to create a wider basis from which skilled personnel may be trained and enlisted, eliminating skills bottlenecks
• Adoption of common languages (English, software codes) to facilitate multi-directional circulation of people among EU15 Countries and also to and from LDC's (prompted by demand for skilled labour, including teachers, tutors, professors).
"Follow the leader" situations can well be imagined in which laggard countries adopt prescriptions and policies which have proved successful in innovative countries. This will facilitate the identification of plausible trends and their quantification. At this regard, the positive scenario foresees sequences of events starting in 2003 and featuring at yearly intervals the outset of large signal innovative events. Indeed, in the positive scenario:
the main assumption is that growth from 2002 to 2010 will be definitely greater
than or equal to what it was up to 2000. GDP and GDP p.c. are assumed to
increase over the period by 40% for Finland (the same increase as from 1993
to 2000) and Ireland, 16% for UK, France and Germany, 15% for Italy and
Portugal and 22% for US. Growth of the number of Internet users exceeds the
forecast indicated in Annex I. We refrain here from getting involved in the
productivity debate and just accept a causal relationship between ICT
production and use and economic growth. The “pre-requisite” variables are
projected here to grow much faster for laggard countries than for innovator
countries, for which the returns of further innovation may be reasonably
expected to diminish.
Table 16: Positive Scenario to 2010 (*)
FIN IRL UK F D I P USA Investment in R&D (% of GDP) 4 3.8 3 3 3.2 1.8 2 3.5 Researchers/000 workforce 19 12 11 10 9.5 11 12 19 % Popul.25-64 w/upper 2ary education
(*) ICT total market value aggregated for EU15 : 1,200 G€ (2010) (**) Sum total of manufacturing and services both in ICT producing sectors and ICT using sectors
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4.9 - Outline of a Negative Scenario to 2010 This negative scenario of future ICT involution and bleak socio-economic situations throughout Europe will not consider major wholly exogenous events nor irresistible factors, such as an escalation of war or sudden large climate variations. The assumption of hypotheses like these would hardly lead to formulate significant counteracting policies particularly in the ICT sector. The same argument applies to the forecast of a deep depression. Past history shows that ICT innovation and its impacts on society have grown in different countries at various rates. It does not appear that much can be learned by reasoning on the possibility that ICT growth rates decrease simultaneously in all EU15 countries. This scenario attempts to deduce the consequences of a set of general causes affecting all EU15 states. It is reasonable to think that laggard countries would resent first the impact of the initial negative factors entailing a further downgrading of their low innovation rate, social efficiency, knowledge creation, influencing in turn productivity, GDP, demand for hitech products (SW and HW). These negative events would influence the absorption of ICT and industrial output from leader countries which, in turn, will follow on the downhill path to recession (possibly stagflation again?). The adverse factors (which, again, are reflected in the negative scenario below in a lump, undifferentiated way) are those listed in Section 4.4 above. We add to the list the following factors:
• trade conflicts with diminishing power of WTO - tariff and price wars, embittered by the unbalance of falling prices in certain sectors or regions (e.g.: steel production in Northern countries) vs. steady or increasing prices elsewhere (oil in OPEC countries)
• social unrest in industrialised nations old and new
• dissemination of mass irrationality: beliefs in magic or in fundamentalist or newfangled sects leading to low productivity, protest, abasement of culture
A number of factors may overlap the many conflict sequences which can be envisaged. A first negative factor may be identified in a coincidence of unfavourable business, social, industrial decisions. A second factor could be a sequence of negative financial events: mismanagement of large companies leading to their demise with consequent unemployment, downsizing, etc. Or else busting of speculative bubbles and failing of many companies on a pattern similar, but more severe, to the failures of dot.coms. A third negative factor could be decreasing efficiency of large technological systems. This may emerge as a consequence of proliferating complexity unchecked by inadequate skills and cultural level of operators as well as of the general population at large. The negative scenario foresees sequences of events starting in 2003 and featuring the outset of conflicts of the types outlined above. Superimposed on these the scenario considers efficiency downfalls or negative events affecting productive and associated life as indicated in the last three paragraphs above. No "follow the leader" situations would be relevant in this context. It may be useful to outline "follow-the-loser"
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situations in which more successful countries slip into acceptance of the worst trends presently at work in less successful European countries (laxism, downgrading of schools, relinquishing total quality management, etc.). Therefore, in the negative scenario:
the main assumption is that growth from 2002 to 2010 will be slower than it
was up to 2000. GDP and GDP p.c. are assumed to increase over the period by
9% for Finland and Ireland, 7% for UK, France and Germany, 4% for Italy
and Portugal and 10% for US. Growth of the number of Internet users stay
below the forecast indicated in Annex I.
Table 17: Negative Scenario to 2010 (*)
FIN IRL UK F D I P USA Investment in R&D (% of GDP) 3.4 2.9 1.9 2.2 2.6 .9 .8 2.7 Researchers/000 workforce 12 7 6 6 7 5 5 11 % Popul.25-64 w/upper 2ary education 74 55 83 63 83 44 25 84 ICT share in value added (1998) (**) 18 17 19 17 No. of Internet users (M) 1.2 .7 16 10 16 8 .8 130 % companies buying online 38 35 18 35 20 7 % companies selling online 20 28 20 36 16 9 ICT mfrg. share in tot.mfrg.employment
(*) ICT total market value aggregated for EU15 : 800 G€ (2010) (**) Sum total of manufacturing and services both in ICT producing sectors and ICT using sectors
4.10. Some comparisons The three intuitive first generation IST scenarios have been sketched by just fanning out current trends: no recourse is made to modelling proper. Consequently the present section means just to compare SEAMATE assumptions with scenarios produced by other projects, and in particular with the ESTO modelling outcomes. The latter is an analysis based on Input/Output approach, fairly more sophisticated and ambitious than the intuititive approach undertaken in SEAMATE WP1. However, we may anticipate, here, that in a late sense a certain convergence appears to exist - although ESTO has produced results which are more optimism than SEAMATE's. The following table shows the trends relative to projections to 2010 as regards GDP. SEAMATE has recorded in the table for "Situation at 2001" "Business as usual" "Positive" and "Negative" only the GDP's of Finland, Ireland, Uk, France, Germany, Italy, Portugal.
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% increase on 2001
SEAMATE 2001 GDP (*) 6.57 T€ -
SEAMATE 2010 GDP (*), Business as usual 7.2 T€ + 9.66
SEAMATE 2010 GDP (*), Positive scenario 7.67 T€ + 16.8
SEAMATE 2010 GDP (*), Negative scenario 6.97 T€ + 6.2
ESTO 2001 GDP 7.3 T€ -
ESTO 2010 Baseline scenario at 2010 9.1 T€ +24 (*) 7 selected countries
The ESTO study takes advantage both of system dynamics and of Input/Output approaches. The models are used to anticipate variations with respect to a baseline scenario. In 2010, under certain assumptions, the economy is expected to fare from .3 to 2% better than the baseline scenario indicates. Of course neither SEAMATE nor ESTO scenarios can be considered as predictions. The overall economic trends, especially in the telecommunications sector have become rather more bleak between March and November 2002. In particular strong negative trends have become apparent in France and Germany: in other countries similar or even worse situations may well have been developing, while governments have failed to face them realistically. The SEAMATE positive scenario optimistic GDP increase of 16.8% appears then more realistic than the hopeful 24% indicated by ESTO.
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5. The way forward: modelling of adapting to Information Technologies and issues for further research In this section we will develop in turn two main subjects:
• basic approaches for modelling technology adoption processes at the micro-economic level and Information Technology impacts at the macro-economic (Sect. 5.1). These approaches are exploited in full, with concrete modelling exercises, respectively in SEAMATE WP4 and WP5;
• an overlook of fundamental issues for further research, aiming to improve the understanding and predictability of Information Technology (Sect. 5.2)
5.1. Basic approaches to model IT impacts at micro and macro-economic level In the following we will introduce the kind of problems that models currently available at micro-economic and macro-economic level can handle. Indeed, specific micro and macro models have been developed in SEAMATE WP4 and WP5, to analyse processes of adapting to Information Technology in Europe.
5.1.1. Modelling network effects and technology adoption
Positive feedback effects underlie the existence of temporary monopolies that flourish in the markets of the network economy (for example Windows, VHS). These temporary monopolies are founded on the first mover advantages of increased network size for customers. Even so, the monopolies in a network economy only survive until they are threatened by new technologies with high expectations for the future pinned on them, at which point the competition for market success starts all over again. Some authors118 have proposed models to study technology adoption processes in markets where network effects are present. Katz and Shapiro present a static model of oligopolistic competition where consumers’ utilities for a given product are explicitly defined as a function of its price, categories of consumers differentiated according to their average willingness to pay, and the number of consumers who use the product. In this model, firms decide how much of their product to produce and whether to make it technologically compatible with other products. As might be expected, firms that are large and have a strong consumer base will not favour compatibility as much as firms with weaker consumer bases, regardless of social welfare considerations. Under certain conditions, widespread industry compatibility may enhance welfare over incompatibility, and industry coalitions may foster such compatibility. Although these mechanisms may have adverse effects – for instance in the form of competition-chilling
118 Katz and Shapiro (1985, 1986); Farrell and Saloner (1985, 1986)
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cartels – the authors argue for antitrust exemptions where industry cartels are likely to yield welfare-enhancing compatibility decisions for their products. In another study119, Katz and Shapiro assess a similar two-period model in which consumers must choose between two incompatible technologies, either of which may be sponsored. In this context, a technology is sponsored if a producer has proprietary rights over the technology, such as a patent, that might allow him to price the product at something other than competitive levels. When one technology is sponsored, the sponsoring firm might be able to create a solid base in the first period by engaging in below-cost penetration pricing that will allow its technology to become the dominant standard in the second period. This could eventually lead to the perverse result that the “wrong” technology can be adopted from a social welfare standpoint120. When both technologies are sponsored, the rational expectations of consumers can lead to a normatively desirable outcome: the technology that would be superior in future periods is made the standard, despite a cost differential that favours an inferior technology in the current period. The above illustrate the kind of technology adoption options which can be analysed with this class of micro-economic models of network industries. An important question is how likely are new standards or technologies (such as different formats for digitised music) to displace entrenched products in cases where there is an incompatible installed base121. Usually models’ results imply that the primary factors behind the decision to adopt the new technology are the size of the installed base that favours the old technology and the perceived benefits of the new network good or service. Though this is not a general property of products with network effects, cases can be found in which the installed base of the old technology can be viewed as a barrier to entry. Much of the research on network effects has implications for the strategies that firms might try to employ in bringing their products on the Internet market and establishing their new installed base. Many of these strategies turn out to be anti-competitive, so they usually require the attention of government and antitrust agencies in some way. One of the more likely venues for anti-competitive problems is the Internet infrastructure. According to Lawrence White, “even if competition is present in most of
the components of a network, monopoly in just a single component may be sufficient to
capture all the potential rents from the transactions that use that component”122. For a parallel situation in the Internet environment, it is sufficient to consider in some detail the current state of interconnection agreements between regional networks and backbone providers. While most backbones currently do not charge for network connection between one another, a fee is usually levied for each connection from backbone to regional networks, and the smaller networks appear to have limited bargaining power in these transactions. Indeed, as backbone owners begin to provide
119 Katz and Shapiro (1986) 120 this arises possibly because the sponsoring firm might price its technology so far below cost in the first period that all first-period consumers adopt it. If the size of the first period network is sufficiently large, second-period consumers will also adopt the sponsored technology even if, in this second period, it is priced higher than the unsponsored technology and less desirable. 121 Farrell and Saloner (1986) 122 White, 1999, quoted in A. E. Wiseman, 2000, pag. 78
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integrated services, such as acting as an ISP to end-users, competition may well dwindle because backbone providers could raise interconnection fees so high that they prevent potential competitors for ISP services to enter the market. Although such scenario may seems plausible, theoretical studies suggest that backbone providers are more likely to engage in some manner of price discrimination to squeeze as much value as possible from those firms – e. g. ISP services – that must rely on their technologies123. Price discrimination at the Internet infrastructure bottlenecks is not the only problem. Standardisation creates a number of potential problems as well. The inherent network externalities associated with the Internet, combined with the value of product interoperability and the presence of notable resource commitments on the part of investors and consumers, make some level of standardisation inevitable. This standardisation will likely give rise to natural monopolies, providing one group of widely adopted products with market durability that may significantly outlast the competitive superiority of the products. Thus, appropriate models of market evolution of the new Information Technologies are important because they can provide answers to problems as those illustrated above. Indeed, the rapid development of new technologies is posing a challenge to traditional concepts and to the very market regulation capability of governments and antitrust agencies. As far as market power is achieved due to underlying economies of scale (that might lead to a natural monopoly), the production of a superior product, the existence of a legal sanction (such as patents or licenses), or some form of anti-competitive practice, current regulatory culture is enough equipped to address the problems. But in the event that market power is acquired because of the presence of network effects, it is unclear whether the government can, or should, intervene to regulate market activities. Problems and questions at stake are not trivial, and they will likely engage regulators in the coming years as the Internet expands to touch more industries and channel of commerce. In order to provide possible answers to the kind of questions discussed above, and to achieve a better understanding of possible future outcomes in specific sectors, there is the need to refine and apply micro-economic models of network industries. These models pose specific challenges to modellers to predict future performances of new goods on the market124.
5.1.2 Input-Output models tracking ICT impacts at the macro-economic level
SEAMATE will not remain confined to the modelling of Information Technology adoption processes at the micro-level. It is the aim of WP5, instead, to model the
123 see for instance O. Shy, 2001 124 with reference to a typical network good as movies, whose success often depends by world of mouth recommendations, two economists, Art De Vany and David Walls, decided to plot first run movies over a 7 months period. They discovered that “the only reliable predictor of a film’s box office was its performance the previous week. Nothing else seemed to matter – not the genre of the film, not its cast, not its budget” (quoted in Kelly, 1998). SEAMATE WP4 focus on studying network effects in selected sectors and technology adoption processes, with appropriate models of the diffusion process.
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impacts of the ICT on the overall structure and productivity of the EU countries’ economy, using an Input-Output framework as a base (I-O relations are indeed at the core of the E3ME model structure). We will show below how the adoption of large-scale innovations – as the Information Technologies – could be modelled with a simplified Input-Output model of the national economy, according to what has been proposed in a seminal paper of A. P. Carter125. This is presented here only as a first introduction to the logic which governs Input-Output modelling, and the possible representation of innovation processes. The specific features, assumptions and usage of E3ME – which is a dynamic Input-Output model used in SEAMATE WP5 to produce scenarios of adapting to IT in Europe – are described in the relevant WP5 deliverables. In the input-output framework, an innovation involves a change in some column Aj of the input-output coefficient matrix or in the sectoral input coefficient for a primary
factor, such as labour, lj . Given input prices, pj , sectoral profit margins, πj , are the difference between the value of sectoral output, pj Xj , and input costs. Innovation will
be economically justified only if those costs, Σi pi aij + lj , are lower than the
corresponding sum for some initial values, Σi pi a°ij + l°j (Nordhaus, 1969).
Sectoral profits Pj are the product of a profit margin πj and a sectoral output level Xj:
Pj = πj Xj . A change in sectoral output, Xj, can result from a change in intermediate coefficients anywhere in the system. It will be given by:
∆Xj = Σj qij Yj - Σj q°ij Y°j Where q is an element of the Leontief inverse and Y represents final demand. Note that in this model the effect of an innovation anywhere in the system on Xi depends, first, on how that innovation affects intermediate requirements, represented by qij, for the output
of sector i. Secondly, ∆Xi also depends on how innovation affects the level and composition of final demand (e.g. by the way of diffusion of new products and services). Actually, this second effect is usually dealt with as an exogenous variable in the simpler and most popular versions of Input-Output models. How the resources released by a given innovation are actually used (e.g. workers released from a sector where a labour saving innovation was introduced are utilised to produce new services) affects whether the innovation leads to the expansion or contraction of any given sector.
The effects of innovation on sectoral profit margins, πj, depend on how sectoral prices are set. The analysis of upstream and downstream benefits of innovation proposed by A.P. Carter exploits a distinction which is possible in the input-output equations between: i) sectors where prices are set exogenously (“flex” prices independent from market pressures); ii) sectors where sellers set prices on the basis of input costs and a
125 see A. P. Carter, 1990
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fixed mark-up ratio (“fix” prices, in the sense that they are automatically determined applying a constant profit margin on the price of inputs fixed by the market). The first form of pricing is typical for a monopolistic operator, who can manoeuvre his profit margins, while the second is characteristic of highly competitive markets, where operators are forced to pass on savings due to innovation or to decreases in input prices to customer sectors in the form of lower prices. Most real-world pricing practice falls somewhere between these two extremes. Effects of innovation and the appropriation of benefits in terms of higher profit margins realised by suppliers or lower prices and, by consequence, increasing purchasing power of users sectors (including final demand) are modelled in this version of the Input-Output model distinguishing two main categories of sectors: fix and flex prices. A change in input coefficients for a flex-price sector leaves flex prices unchanged, affecting only the profit margins of the flex-price industries themselves. In turn, such a change leaves fix prices and profit margins of fix-price industries unchanged: the benefits of innovation remain confined within the flex-price sectors. On the other hand, a change in input coefficient for a fix-price sector leaves the profit margins of fix-price sectors again unaffected (as the very consequence of how the fix prices are set), but it can change any or all of their prices, and therefore, since fix prices enter also into the cost equations of the flex-price sectors, the profit margins of the latter. In this case benefits of the innovation are spread over the system. In sum, then, innovation anywhere in the economic system might increase the profits of a given sector by raising its output level, its profit margin or both. Changes in coefficients in any sector may raise output in that or in another sector. So may increases in final deliveries occasioned by the release of resources following innovation. Changes in profit margins can only occur in flex-price sectors. Such changes may be the result of coefficient changes in the flex-price sectors themselves or of changes in input coefficients of fix-price sectors that are passed on to the flex-price sectors in the form of lower input prices. These kind of relations have been used by A. P. Carter in her paper to present simulation of impacts of hypothetical innovations in a simplified economy consisting of four vertically staged sectors following Von Hippel’s classification (Von Hippel, 1987). According to this, an aggregate S(upplier) sector produces a input for an aggregate M(anufacturer) sector, which in turn provides and input into an aggregate U(ser) sector. O(ther) represents an aggregate of all remaining sectors of the economy. Each sector’s initial technology is represented by a column of intermediate and value-added coefficients (subdivided into labour coefficients and profit margins). In the mentioned hypothetical exercise several innovations are considered, each affecting input coefficients in a different way, as well as different combinations of fix- and flex- price strategies. Macro-economic assumptions have been made also, concerning the level of final demand and therefore aggregate employment impacts. However, the simulations did not include the wide range of cases where sectors appropriate a portion of the innovation related savings and pass on the rest in the form
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of reduced prices. Under some circumstances, innovating sectors might also increase their prices after innovation. In this sense, the computations made by A.P. Carter in her seminal paper provided only an initial step in exploring the range of plausible options. Moreover, Carter's work was only based on hypothetical data, to examine and present the logic of the economic system and impacts of innovation. The challenge obviously was – and still is – to implement the theoretical system with real data. 5.2 – Issues for further fundamental research The following sections aim to highlight the essentials of two issues which are quite relevant for deepening the analysis of ICT socio-economic impacts and also for reaching more significant insights in the processes involved. Section 5.2.1 concerns knowledge creation and flows - a sector which will attract heightened attention in 6th Research Framework Programme of the European Commission. Section 5.2.2 (and 5.2.2.1) concerns scale free networks. Their structure has begun to be really understood in the last few years. This understanding is vital for underpinning any forecasting attempt, as well as for devising adequate intervention strategies.
5.2.1 Evolution of Knowledge Assets - Conceptual Frameworks
The knowledge and intelligence applied to productive processes found expression both in the technologies used in production as well as in the way that production was organised. The more effectively knowledge and intelligence were used, the greater the economies achieved in the consumption of productive factors. Yet, knowledge and intelligence are elusive concepts; they are often idiosyncratic individual traits that do not interact in any direct mechanical way with the physical world. They do not yield easily to direct observation and analysis. Starting from these premises, a thought provoking, but unsatisfactory attempt to conceptualise the basic features of the information economy was made by M.H. Boisot (Knowledge Assets, Oxford University Press, 1998):
• introducing the concept of an “evolutionary” instead of the “neo-classical” production function;
• defining the value and analysing the future evolution of knowledge assets as the key “input” of the information economy.
Here we briefly present the above Boisot’s concepts and criticise the basic faults of his analysis (in section 5.2.1.1), and then proceed to outline (in section 5.2.1.2) essential traits of a conceptual framework of information-knowledge value and evolution 5.2.1.1. The evolution of information economy according to the Boisot’s perspective.
Typically, productions functions single out in a highly simplified form those factors that society considers critical to the creation of wealth. Nowadays, across virtually all industries, knowledge has become a critical determinant of the wealth of nations. Attempts have been made to incorporate knowledge into the existing neo-classical
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production function, e.g. embedding a measure of productive knowledge in human capital in the form of distinct categories of skilled workers. Boisot’s perspective is to consider these attempts untenable, and to adopt a radically different type of production function, one which at this stage of its development could only be used for a highly schematic type of analysis. This new production function will consider, instead of labour and capital, two other inputs: i) physical resources and ii) information resources. Albeit not easily measurable, physical attributes of energy, space and time can be grouped together into a single physical factor that is represented by one dimension of the new production function, while knowledge and information can be grouped together into a second factor and represented by a second dimension. However, this second input factor cannot be made up of knowledge and information themselves. Indeed, properly used, information economises on the consumption of data. Thus, data, not information, is considered as the second input factor into the production process, together with physical resources. Therefore, the Boisot’s production function operates at a high level of abstraction, the physical resources of energy, space and time making up one factor, data making up the other, and knowledge assets taking the role correspondent to the output of the production function. Another important feature of the Boisot’s perspective, is that in any system capable of evolving over time, the trade-off between physical and information inputs is asymmetrical – i.e. it has a preferred direction. Between any two time periods, a system and its successors will exhibit a bias towards increasing its consumption and processing of data, and thus towards reducing its consumption of physical resources per unit of output. It does this through a process of differentiation, integration, and the creation of memory stores. In effect, this new production function concept, in contrast to the more conventional ones used by economists, displays evolutionary tendencies. Systems that evolve do so by economising on their rate of consumption of physical resources. But is that proposed by Boisot also an useful perspective of the information economy for operational purposes? The problems come out again when he attempts to substantiate information as an “asset” in some way independent from the “service” which is ultimately supplied by human beings. Indeed, Boisot schematises the evolutions of information economy in the framework of what he terms Information Space (I-Space). This consists of 3 orthogonal dimensions: codification, abstraction and diffusion, moving in which he alleges to describe Social Learning Cycles, i.e. any progress or evolution of society, economic sectors, firms. Codification and abstraction often run closely together, but they are presented as quite different in this scheme. The first gives form to phenomena, the second gives them structure. The act of assigning phenomena to categories once these have been created is termed here as coding. The faster and the less problematically that coding can be performed, the more effective the codification process and the more extensively it will be used. If codification allows us to save on data-processing resources by allowing to group the data of experience into categories, abstraction allows us to realise further savings in data processing by minimising the number of categories that we need to draw on for a given task. Abstraction then works
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by teasing out the underlying structure of phenomena relevant to our purpose. It requires an appreciation of cause-and-effect relationships to an extent that simple act of codification do not. Diffusion of information is still another dimension of the I-space. It covers processes that vary widely in complexity, within the realms of physical, biological and social systems. Boisot’s theory suggests that the creation and diffusion of new knowledge effectively activate all three dimensions of the I-Space, but that they tend to do so in a particular sequence, named “Social Learning Cycle”. This is decomposed into six phases: i) scanning, i.e. identifying threats and opportunities in generally available but often fuzzy data; ii) problem-solving, i.e. giving structure and coherence to the insights of the scanning process; iii) abstraction, i.e. generalising the application of newly codified insights to a wider range of situations; iv) diffusion, i.e. sharing the newly created insights with a target population; v) absorption, i.e. applying the newly codified insights to different situations in a “learning-by-doing” context; vi) impacting, i.e. embedding of abstract knowledge in concrete practices, for instance behavioural patterns in which the new knowledge is taken for granted (common sense). Through a SLC, an information good evolves dynamically over time. The value of a knowledge asset is derived partly from the utility of the services that it yields over time, and partly from its positional status, which can confer a competitive advantage to those to whom the knowledge asset belong as far as others do not possess it. Thus, a proper exploitation of knowledge assets calls for optimising their residence time in value-generating regions of the I-Space. Indeed, through the dimensions of codification, abstraction and diffusion, both the scarcity and the utility of an information good can be expressed in the I-Space. The maximum value of an information good in the space is achieved when its diffusion is at a minimum but its degree of codification and abstraction are at a maximum (point B: proprietary knowledge). Conversely, the minimum value of such a good is reached when diffusion is at a maximum and codification and abstraction are at a minimum (point D: common sense). However, the information goods out of which knowledge assets are built are continually prey to the actions of an SLC. The SLC tends to move information goods both into the value-generating region of the I-Space as well as out of it.
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However, Boisot's too ambitious goal is unfulfilled because:
• no formal definitions of the 3 alleged dimensions are given;
• it is hard to believe that a single (discursive) model or paradigm is fit to describe significantly processes and events of different kinds (from R&D to management, to choices of technical, managerial and organisational solutions, to socio-economic or cultural trends involving entire nations);
• no metrics are suggested, so no check nor comparison to actual events/processes can be carried out. A tacit assumption that the entropy variable can be usefully employed and that it should be considered as inversely proportional to value, is not warranted;
• "codification" is presented as a standard step "giving form to phenomena" and replacing operational descriptions with set formal classification (this is only possible after facts and processes have been analysed and understood);
• "abstraction" is presented as a positive feature representing an advance with respect to consideration of concrete measurements (or observations or data). The concept is vague. Insight of cause-effect relationships and of process mechanisms would be, perhaps, a more apt concept;
• "diffusion" is described as the communication of knowledge relevant per se and immutable - as a secret formula, recipe or prescription which once acquired is equated to an appropriation of value, whereas knowledge has value as a source of solutions built on the supplier's competence/knowhow, as a continued service and not as a quasi-object;
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• excessive weight is given to property rights of knowledge producers, and too scarce attention to the accounting practices for keeping score of the value of knowledge
5.2.1.2. Knowledge value and evolution: outline of a conceptual framework
The following are statements that we recommend to consider to analyse properly knowledge value and evolution: 1. Encoding acquired knowledge is an essential tool for correct conceptualisation,
efficient use, rapid retrieval and effective communication. It cannot be carried out until adequate insight of processes, phenomena, facts has been reached. Recourse to pragmatic rules of thumb is on occasion unavoidable (usually when complexity is high) and should be documented for future re-processing.
2. Encoding knowledge of very complex realities or processes is hard. It is generally wrong to equate high complexity (above a certain threshold) with chaos. Chaos theory, as correctly used in physics, is concerned with formalised situations - in order to tell chaotic processes from noise, it is necessary to acquire many hundred thousand accurate measurements of well defined phenomena.
3. In order to transmit/disseminate knowledge, the format has to be tailored to the target's culture. This is not always easy and sometimes it is impossible. Acceptance (or adoption) of transmitted knowledge depends on many factors, often in unpredictable ways. The process is stochastic and solutions can only be sought by cut and try empirical strategies.
4. Information on quantities and prices of products or services even if available at a theoretical standard of perfection, hardly ever provide adequate knowledge of reality and of available choices. Apart from very standard and basic products (e.g. cigarettes), information on qualities, trends, probability of obsolescence is also necessary and often only available in rough form as the result of intuitive assessments.
5. Information should not be classed as "goods" and discussions on its scarcity value are idle. The notion that better defined and codified knowledge instead of gaining, loses intrinsic value in that it is easier to disseminate, to appropriate - is devoid of sense. Information/knowledge is a service and is not more indeterminate with respect to value than any other good. In a very peculiar sense it has intrinsic value: this can be assessed only by service suppliers and users interaction.126 Its value to users depends on a host of factors: mission and goals, market situation, incidental occasions. Consequently any attempt to capitalise (classify as assets) knowledge or other intangibles (either bought or produced in house) is to be avoided as too risky. A high quality design for a new machine or product may embody great hopes - which may never materialise due to non acceptance by the market or by the appearance of an even better and more innovative design produced by a competitor or by unrecognised inherent defects. Only after knowledge has driven production and profitable sales or a reduction of costs, its value can be assessed a posteriori - after the fact.
126 e.g. using in some cases auction systems to fix the price of goods and services whose value is unknown.
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6. To exemplify the service character of information/knowledge, consider a positive and a negative example. The former is the management system and software marketed by SAP. Its wide acceptance is not a sign of the intrinsic value of a product, but of the continued exploitation of advantages provided by the maintenance and current upgrading of systems initially acquired. The negative example is provided by Microsoft forcibly selling services (with too lucrative margins of 86%) to their captive market for Windows. Here the value of the service is debatable since each new version of the software provides only marginal improvements with respect to previous versions. Users are motivated to buy the new versions mainly due to the nuisance value of continuing to use previous ones after too large a section of the market has accepted the transition. We can imagine the end of the Microsoft monopoly as a consequence of a wide refusal to conform, either sticking to old versions of the software or migrating to competing open systems.
7. Knowledge has been equated by some to negentropy [or negative normalised entropy: a concept used in molecular biology and in the thermodynamics of living systems]. The metaphor is an apt one - for discursive purposes. Consideration of analogies with well defined physical variables (like entropy) hardly adds any operational insight unless it can be formalised and measured.
8. Technological processors and transmitters (including credit cards, cellular phones, e-mail, laptops, 3G s) are well known to enhance the efficiency of any operation involving knowledge. It is to be avoided to consider the performance, speed and quality of computers and telecommunication channels as a proxy for the quality of knowledge. Again: only after the fact the ease of information processing and transmission will be one of the factors to be considered in assessing value, efficiency or service level.
9. The substitution of information for physical resources may be actually a vital factor to increase efficiency, reduce costs, protect the environment. Information, though, has to be assessed in each individual instance: wrong information may produce untold damage and disaster.
To conclude, any mechanical relationship between the collection of data and the realisation of appropriate actions is not acceptable. This objective presupposes that the right kind of figures and data are collected in the first stance. But even with apparently simple measures, there is sometimes doubt as to what they mean. Take, for example, the problems that one has with data and measurements concerning the weather. The laymen observes the weather directly through his senses. The meteorologist can make direct observation through the senses as the layman, but instead of relying on his sense impressions he uses a battery of recording instruments: thermometers, barometers, wind vanes, hydrographs, rain gauges etc.. The above gives perhaps a concrete example of what Boisot defines in generic terms “abstraction”: one skilled man, with an updated knowledge of meteorological science and its instruments, can today forecast weather conditions over continents and relatively long periods of time, with an increasing degree of precision, and allows to save potentially a lot of resources127, something that the laymen with his less abstract knowledge cannot do. But the degree of relationships
127 for instance, the Mac Donald fast-foods in the US use weather forecasts to determine the “just-in-time” daily supply of bread, meat, etc., because according to their statistics, consumers afflux is strongly dependent from weather conditions.
147
between numbers and the real world is something for which we must always be on the alert. Even in simple cases data can require interpretation which is far from being mechanical, not to say of situations in which entire new categories and cause-effects relationships must be discovered to improve our capacity of understanding and mastering problems in the real world.
5.2.2. Scale-free Networks 128
Consideration of telematic networks showed that previous applications of graph theory to networks were ill-conceived. They considered networks growing in a random fashion and acquiring a uniform structures, with most nodes having the same average number of links so they present a Gaussian distribution. This is generally true of road networks with most cities (big and small) having very similar numbers of roads departing from them. In air transportation systems numbers of links per node (like income/person) are distributed according to a Pareto formula. This is also termed a power law and was originally applied by Pareto to the distribution of income in a country. The number N of citizens having an income equal to or greater than X is
N = a X-b with positive a and b). So: very few airports have very high numbers of air routes connecting them - very many airports have very few routes. An approximate mnemonic rule is: 20% of citizens earn 80% of total income or 20% of airports account for 80% of air routes. The same is true for the WorldWide Web. These networks are called scale free meaning that the distribution of links/node - not being Gaussian - does not possess a norm based on which a scale can be defined. The power law structure is due to the fact that the network is growing continuously with new nodes establishing links to existing nodes with a probability proportional to the number of links already connected to the existing nodes. So this preferential attachment is not a random process. Another factor influencing choice of links by new nodes is the fitness of the older nodes. Fitness is defined as the quality, efficiency, level of service, contents, effectiveness of the old nodes. Note here that Barabasi does not delve too deeply on fitness - this is due to the fact that fitness has largely to be defined subjectively. Different operators assess differently the fitness of a node. I surmise that fitness judgements don't have the transitive property. (Some work I did on mutual evaluation matrixes in professional groups may be applicable here). Again the choice of sites to which to connect depends on their previous connectivity and on their contents. Nodes with highest number of links are termed hubs and they dominate networks (examples: large airports and in the WWW, Google, AOL).The above mechanisms have the effect that large hubs tend to become larger and larger (richer-get-richer): often - but not always - they are the precursors, the innovators. In special conditions this process will lead to a winner-take-all situation (e.g.: Microsoft).
128 In very recent years a formal theory of the growth of certain networks has been developed (see: LINKED, by Albert-Laszlo Barabasi, Perseus Publishing, 2002). The following brief synopsis of the theory of scale-free networks is merely intended as a hint.
148
Often certain parts of the network form clusters containing hubs, but clusters may be (poorly) connected to each other by means of extremely low numbers of links -- termed weak links . To reach other clusters may be convenient in that this leads to the contents (or fitness) of new large hubs - this may be achieved then by following just weak links. These insights on networks cast new light on: network growth and decline processes, on success strategies (mergers are a necessity, not a choice), on reliability and resilience of networks (how to avoid, or to produce wilfully, cascading failures), on planning connectivity and navigation. This mathematical theory of networks appears to be an efficient tool for understanding and forecasting growth and decline processes not only of networks, but also of economic structures. 5.2.2.1. Small Worlds
Choose at random a man or a woman among all living human beings. How long is the chain of acquaintances linking this person to others and finally to one whom you know? On the average this chain has only 6 links. Since there are 6 million people on the world, this answer is surprising. It was imagined in 1929 by Frigyes Karinthy, a Hungarian novelist. Then in 1967 it had been formulated seriously and checked experimentally by the sociologist Stanley Milgram. Now it can be explained rationally using the Barabasi theory of networks. Intuitively: each of us knows on the average from a few dozen to many hundred people (just count the names in your own phone book). But some people have many tens of thousands acquaintances: they are the hubs and they cause the number of degrees of separation between any two individuals to decrease. At present there are some billions Web pages. Many of them contain links which connect them to other pages, just as human beings are tied with chains of mutual acquaintance. On Internet, however, the distance is somewhat larger: there are 19 degrees of separation. Nodes (persons, websites) are relatively close to each other which is the reason why these huge sets are termed small worlds. The fact that the Web is a small world does not entail that it is easy to carry out the 19 jumps (on the average) that will allow us to get to any site we may deem interesting. In fact with exactly the same ease we can reach any other site - and the majority of them has no interest whatsoever for us.
5.2.3 Knowledge dynamics and EU socio-economic development
The Boisot’s perspective of the information economy presented in para. 5.2.1 is still trapped into the need to define information as a “good” instead of a service, whose value depends on many circumstances. However, the focus on the possible trade-off between the usage of data and physical resources of energy, space and time, with knowledge producing new insights taking the role of resource saving factor (the equivalent of technology in the standard view) is stimulating, provided that it is not necessarily re-conducted to an overarching explanation of the impact of the information
149
economy in the way Boisot does, recurring to the abstract definition of the so named I-space and the too generic concept of SLC to represent the evolution of the new knowledge. Collecting data is an absorbing task which can all too easily become an end in itself. Yet, the aim of collecting and collating any figures is to be able to take appropriate actions on the basis of the information known. Thus, taking into account the caveats of para. 5.2.1.2 above, we can assume that a potential useful way of defining what “an appropriate action” is to use a wide concept of efficiency, i.e. to gather more with less –
more space because we save the use of land, more time because we avoid time
consuming tasks, more energy because we avoid waste of materials or exploit better the
energy transformation processes, and all this thanks to the new knowledge acquired on
the best way to do things in a given context. This is a concept which is perhaps much useful to use where the one overall measure that exists to assess the productivity of economic activities, that is added value, doesn’t work in practice, as it is for measuring the output of many services and information activities. Understanding the consequences of new knowledge in terms of saving of physical resources, in different socio-economic contexts, and devising new productivity measures is thus an important and challenging research task. As concerns the new approach studying scale-free networks (cfr. para. 5.2.2), this seems particularly promising to improve the modelling of network effects and achieve a better understanding of the dynamic of diffusion of new IT products and services. Different industrial structures and market regimes – e.g. e-commerce oligopolies versus monopolistic competition – should be studied to understand the underlying network dynamics. In particular, in some cases the evolution towards oligopolies or even monopoly situation could result from the operation of an underlying scale-free network dynamic, and the preferential attachment process. Modelling in such a way product market development, the success of a node (product) depends from its fitness (value for money) and the number of links already connected to it (the number of existing consumers).
150
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Useful links to Web sites
[1] eEurope benchmarking report Feb 2002 - da http://europa.eu.int/information_society/europe/benchmarking/index_en.htm [2] Internet economy indicators - da www.internetindic.com [3] C Commerce Industry statistics - da www.commerce.net [4] Mobile Commerce Epaynews.com - da www.epaynews.com [5] Is Europe ready for E-future by B Barnard - www.commeuro_file/europe.htm broadband.htm - article by G Livraghi that you find on www.gandalf.it [7] euinfoempl.pdf data on employment in ICT Europe from: http://europe.eu.int/comm/employment_social/soc-dial/info.soc/esdis/index.htm elearn01.pdf su e-learning europa da [8] http://europe.eu.int/eur.lex/eu/comm/cnc/2001/com2001_0172eu01.pdf [9] http://www.nua.com - Scope Communications Group, Dublin, Ireland [10] US Bureau of the Census - www.census.gov
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[11] Data on Internet Activity worldwide - www.gandalf.it [12] Data on Internet Activity in Europe - www.gandalf.it [13] Data on Internet Activity in Italy - www.gandalf.it [14] World: Miscellaneous: Literacy Info/ Stats by country, UNESCO, www.intuit.quickbase.com - liter2stat_file\5cxx2et9.htm [15] World: Miscellaneous: Education Info/ Stats by country, UNESCO, www.intuit.quickbase.com - literacunesco_file\5cxv8rye.htm
From www.oecd.org\statistics [16] A3.1 - Decomposition of changes in annual average growth rates of GDP per capita - oecdeconhum.xls [17] A2.1b - Educational attainment of the labour force (1999) - oecdedlevel.xls [18] B2.1b -Expenditure on educational institutions as a percentage of GDP - oecdedexp.xls [19] C4.1 - Graduation rates in tertiary education (1999) - oecdterteduc.xls [20] C4.4 - Science graduates in the youth labour force (1999) - oecdscigrad.xls [21] C6.1a - Participation in job related continuing education and training and educational attainment - oecdconteduc1.xls [22] C6.1b - Participation in all continuing education and training and educational attainment - oecdconteduc2.xls [23] C6.2a - Participation in job related continuing education and training and employment status - oecdconteduc3.xls [24] D6.2a - Nature and location of ICT training on hardware for teachers (1998-1999) - oecdICTsch.xls [25] D6.2b - Nature and location of ICT training on software for teachers (1998-1999) - oecdICTteach.xls [26] D6.2c - Nature and location of ICT training on Internet and multimedia for teachers (1998-1999) - oecdICTintnet.xls [27] D7.5 - Availability of software in schools (1998-1999) - oecdSWsch.xls [28] D7.3 - Use of the Internet in schools (1998-1999) - oecdinetsch.xls
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[29] D7.1 - Ratio of students to computers (1998-1999) - oecdcompstu.xls [30] D7.2 - Computers not in use in schools (1998-1999) - oecdcompno.xls [31] OECD, 1999 – The Economic and Social Impacts of Electronic Commerce – Paris [32] EC-EUROSTAT – Telecommunication indicators in the Eurostat area – Working Group Statistics on Communication and Information Services, February 2001 [33] European Commission Energy DG Report "Key Figures 2001 -Towards a
European Research Area, Indicators for benchmarking of National research policies". [34] OECD Science, Technology and Industry Outlook - Drivers of Growth: Information Technology, Innovation and Entrepreneurship, Special Edition 2001 – [35]http://oecdpublications.gfi-nb.com/cgi- [36]bin/OECDBookShop.storefront/EN/product/922001131P1 [37]OECD Science, Technology and Industry Scoreboard - Towards a Knowledge-based Economy, 2001 Edition - http://webnet1.oecd.org/EN/document/0,,EN-document-18-nodirectorate-no-1-17270-18---,00.html [38]"The EU Economy Review 2000", Chapter 3 - "Economic Growth in the EU: Is a New Pattern Emerging?" (available on: [39]http://europa.eu.int/comm/economy_finance/publications/european.economy/the_eu_economy_review2000_eu.htm/) [40]European Central Bank Working Paper N°122 "New Technologies and Productivity Growth in the Euro Area", by F. Vijselaar and R. Albers, February 2002 [41] OECD Education at a glance“, http://www.oecd.org/EN/home/0,,EN-home-4-nodirectorate-no-no--4,00.html [42] Deiss R., E-commerce in Europe, Statistics in focus, Eurostat Theme 4-12/2002
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Appendix 1 - Correlation and regression analysis This appendix shows detailed information on the regression and correlation analysis carried out in the chapter 3: 1) capital deepening contribution to economic growth, 2) Total Factor Productivity contribution to economic growth, 3) The contribution of individual learning to GDP, 4) The contribution of organisational leaning to productivity growth. The information released concern:
• Table indicating values of the analysed ICT indicators by country
• Descriptive statistics (mean and standard deviation)
• Matrix of correlation coefficients
• Model summary (multiple regression coefficient)
• Coefficients of the independent variables and confidence interval (95%)
• Residuals statistics (minimum and maximum values, mean, standard deviation, plot chart)
All the above-mentioned statistical analysis has been provided through the SPSS statistical tool version 7.5 for Window.
1) Capital deepening contributions to economic growth
Table indicating values of the analysed ICT indicators by country
Country Dependent variable Independent variables
Contribution of ICT ICT Investment ICT Price Level
Capital to Economic 1999 Variation 90-97
Growth '96-'99
-% Points on GDP - -Share on GDP - Standardised index
Predictors: (Constant), Part rate 55-64 ter, Unem ter30-44, Educ below sec 99, Unem ter 25-29, Educ attsec 99
a.
Dependent Variable: GDP pc 99b.
167
31,386 14,598 2,150 ,075 -4,333 67,106
-,330 ,160 -,895 -2,066 ,084 -,722 ,061
-8.87E-03 ,353 -,007 -,025 ,981 -,872 ,854
-,698 ,851 -,214 -,820 ,444 -2,781 1,385
-8.31E-02 ,217 -,162 -,382 ,715 -,615 ,449
,149 ,116 ,209 1,286 ,246 -,134 ,432
(Constant)
Educ
below sec99
Unem ter25-29
Unem ter
30-44
Educ attsec 99
Part rate55-64 ter
Model1
B Std. Error
Unstandardized
Coefficients
Beta
Standardi
zedCoefficien
ts
t Sig.LowerBound
UpperBound
95% Confidence
Interval for B
Coefficientsa
Dependent Variable: GDP pc 99a.
12,7573 32,9886 22,9833 6,8219 12
-4,5176 3,5847 -2.07E-15 2,3800 12
-1,499 1,467 ,000 1,000 12
-1,402 1,112 ,000 ,739 12
PredictedValue
Residual
Std.PredictedValue
Std.Residual
Minimum Maximum MeanStd.
Deviation N
Residuals Statisticsa
Dependent Variable: GDP pc 99a.
168
4) The influence of organisational learning to productivity growth
Table indicating values of the analysed ICT indicators by country
Country Dependent variable
Labour productivity Triadic patent Domestic R&D Business R&D
96-'99 families expenditure expenditure
-% increase- -Per million pop. 95 - - Share of GDP 1999 - - Share of GDP 1999 -
Sweden 1.7 73.6 3.8 4.7
Germany 2.1 52.3 2.4 2.2
Finland 3.1 49.6 3.2 3.2United States 2.6 42.4 2.6 2.4
Belgium 1.1 31.5 1.9 1.7
Denmark 0.9 30.7 2.0 2.0France 1.6 29.9 2.2 1.9
United Kingdom 1.5 22.2 1.9 1.8
Canada 0.9 11.8 1.7 1.3Italy 0.7 9.7 1.0 0.7
Spain 0.3 2.2 0.9 0.6
Independent variables
1.5000 .8450 11
2.0455 1.1484 11
2.1455 .8560 11
32.3545 21.1067 11
Labourproductivity
BusinessR&D
DomesticR&D
Triadicpatent
MeanStd.
Deviation N
Descriptive Statistics
169
1.000 .646 .766 .710
.646 1.000 .979 .943
.766 .979 1.000 .949
.710 .943 .949 1.000
. .016 .003 .007
.016 . .000 .000
.003 .000 . .000
.007 .000 .000 .
11 11 11 11
11 11 11 11
11 11 11 11
11 11 11 11
Labourproductivity
BusinessR&D
DomesticR&D
Triadicpatent
Labourproductivity
BusinessR&D
DomesticR&D
Triadicpatent
Labourproductivity
BusinessR&D
DomesticR&D
Triadicpatent
PearsonCorrelation
Sig.(1-tailed)
N
Labourproductivity
BusinessR&D
DomesticR&D
Triadicpatent
Correlations
.924a .855 .792 .3850
Model1
R R SquareAdjustedR Square
Std. Errorof the
Estimate
Model Summaryb
Predictors: (Constant), Triadic patent, Business R&D,Domestic R&D
a.
Dependent Variable: Labour productivityb.
170
-1.478 .577 -2.562 .037 -2.842 -.114
-1.919 .537 -2.608 -3.572 .009 -3.189 -.649
3.109 .762 3.150 4.082 .005 1.308 4.910
7.183E-03 .019 .179 .382 .714 -.037 .052
(Constant)
BusinessR&D
DomesticR&D
Triadicpatent
Model1
B Std. Error
Unstandardized
Coefficients
Beta
Standardized
Coefficien
ts
t Sig.
Lower
Bound
Upper
Bound
95% Confidence
Interval for B
Coefficientsa
Dependent Variable: Labour productivitya.
.1848 2.6871 1.5000 .7812 11
-.4978 .4129 -1.84E-15 .3221 11
-1.684 1.520 .000 1.000 11
-1.293 1.072 .000 .837 11
PredictedValue
Residual
Std.PredictedValue
Std.Residual
Minimum Maximum MeanStd.
Deviation N
Residuals Statisticsa
Dependent Variable: Labour productivitya.
Normal P-P Plot of Regression Standardized Residual
Dependent Variable: Labour productivity
Observed Cum Prob
1.00.75.50.250.00
Exp
ecte
d C
um
Pro
b
1.00
.75
.50
.25
0.00
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ANNEX 1: Screening of data and trends of ICT use and related variables In this Annex we examine a collection of data concerning prerequisites and use of ICT. Data were extracted from sources indicated in the references. Data were needed as a basis for scenario building. However figures reported from different (even authoritative) sources diverge markedly. As indicated in individual instances, we have recurred to common sense cross-footing to suggest usable quantitative assessments.
Internet users and hosts
Published data on Internet hosts and users (by EITO, OECD, Eurostat) differ markedly. Further collected data also diverge. The following table gives data for 2000 from Eurostat, Liikanen129.
Table 1: Internet users in 2000 per different sources (million)
Source ⇒⇒⇒⇒ Liikanen [5] Eurostat C-Commerce US Census NUA
USA + Canada 87 120 93.7 181
EU15 56 98 70 155
East.Europe 38
The very high variability indicates low reliability of data and probably large differences in classifications and definitions used. Of the 93.7 M users per US Census, 83.4 M are defined as E-mail users and 30.6 M as users for school courses - both activities have social but not immediate economic relevance. Commerce Net and NielsenMedia Research classify users as people who have accessed Internet at least once in the previous week. Consequently it appears that to mirror actual impact, a drastic reduction should be applied. The factor to be used should be at least equal to 2 on the excessive assessment of NUA. It appears reasonable to accept for Europe the Liikanen figure of 56 M in 2000, one third that in 1997 (as recorded by some credible sources) and next to zero in 1985. On this basis a logistic Volterra curve has been built giving the following values of European Internet users - with asymptote reached in 2020.
YEAR Internet users in Europe (M)
2000 55
2001 74
2002 94
2005 146
2010 176
2020 181
129 See the following: Is Europe ready for E-future by B Barnard - www.commeuro_file/europe.htm, C Commerce Industry statistics - da www.commerce.net, ] http://www.nua.com - Scope Communications Group, Dublin, Ireland, US Bureau of the Census - www.census.gov
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This can be the basis for a scenario of Internet diffusion. Further surveys or collection of experts opinions should be gathered. Data from130 and 131 indicate that the number of hosts in Europe and in the world is at present respectively 20.3 M and 126 M. A Volterra analysis indicates possible asymptotes of 90 M for Europe (20% more than the number of users is plausible) and 190 M for the world. According to OECD 2001 the numbers of ISDN subscribers from 1995 to 1999 based on 64 kbps equivalent, were132:
1995 1996 1997 1998 1999 1999 per capita (%)
Belgium 78 146 270 507 870 8.5
Denmark 42 90 176 346 662 12.4
Finland 13 54 116 329 467 9
France 0 1600 2128 2638 3600 6.1
Germany 2744 5203 7341 10093 13320 16.2
Italy 159 341 897 1735 3049 5.3
Netherlands 104 321 810 1570 2280 14.4
Norway 46 149 410 769 1262 28.3
Portugal 57 98 183 314 477 4.8
Spain 28 219 457 505 979 2.5
Sweden 49 100 187 319 645 7.3
UK 0 0 1100 1700 2400 4
Total above 12 3320 8321 14075 20825 30011 8.4
USA 0 0 451 757 999 3.3
Canada 0 0 0 1554 2016 .7
Extrapolating the time series for the above 12 European countries by means of a Volterra equation, we obtained an asymptote of 49.6 million ISDN subscribers to be reached in 2007. It is to be expected that the trend toward the broad band will block the growth of ISDN, which may not even reach the projected asymptote and in any case decline in following years.
130 Data on Internet Activity worldwide - www.gandalf.it 131 Data on Internet Activity in Europe - www.gandalf.it 132 cfr. Enabling the Information Society by Stimulating the Creation of a Broadband Environment in
Europe, Report of RAND Europe to DG Information Society of the European Commission
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According to the e-Europe Report 133 in 2001 there were in the USA 250 secure servers for million inhabitants (i.e. 71,000) and in Europe only 50 (i.e. 18,500). Surveys of Internet usage also reveal that some groups have more access to the Internet than others. This propensity for some groups to have greater Internet access than others has come to be known as a digital divide. Because there are a number of ways to categorise people, there are several possible digital divides that might conceivably exist. A wide and dramatic digital divide is apparent in the figure below (source OECD), which displays the distribution of the world’s online population.
133 eEurope benchmarking report Feb 2002 from: http://europa.eu.int/information_society/europe/benchmarking/index_en.htm
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Employment & Revenues from ICT
Data on total ICT revenues in the EU taken from EITO 2000 are reported in par. 2.4.8. below. These show a sharp increase of the market from 356 G€ in 1997 to 537 G€ in 2002 (estimated). The breakdown given for the year 2002 is: IT hardware: 106 G€ (20%) IT software and services: 145 G€ (27%) Telecom services: 286 G€ (53%) A significant disaggregation is suggested by Ecominfocenter for the US in 4 layers, for which revenues and employment are given for the 2nd quarter of 2000:
It is desirable that a similar disaggregation be defined and investigated for Europe too. From 134 below, info is available for Europe concerning employment connected to ICT in 2000:
Type of work ⇓⇓⇓⇓ Number of workers 2000
Number of workers estimated 2003
Direct empl. in SW (like Layer 2 for US?)
200,000 370,000
Upstream empl. (like Layer 1 for US?)
200,000 230,000
Downstream empl. (like Layers 3 and 4 for US?)
650,000 900,000
The growth rate for ICT jobs is estimated in 10%/year or about double the rate for general employment.
134 euinfoempl.pdf data on employment in ICT Europe from: http://europe.eu.int/comm/employment_social/soc-dial/info.soc/esdis/index.htm
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Type of worker ⇓⇓⇓⇓ % uses P.C. Nov.2000 % uses Internet Nov.2000
Self employed 41 31
Manager 80 61
White collar 70 46
Manual labourer 22 20
On the average 45% of European workers use computers (but only 16.7% have had informatics training by employers) - of these 12.5% telework. By comparison 70% of employees of government or public bodies have had informatics training. The same source presents the following estimates of skills shortage in Europe ICT sector:
Demand Supply Shortage
2000 10 M 9 M 1 M
2003 (est.) 13 M 11 M 2 M
Shortage of ICT experts is 2/3 for technicians and 1/3 for professionals. As a matter of fact, it is generally recognised that the skill shortage in Europe could represent a real handicap for the European economy. In some cases domestic market is not able to meet the demand for skilled work. For instance, the US experience shows that it has been possible to sustain the rapid growth in the ICT sector through the policy of attracting skilled immigrants135. However, a positive factor of flexibility for Europe could be the new possible inflow of migrants or outsourcing of ICT tasks to high skilled workers from East European Countries, facilitated by the policy of enlargement of European Union to candidate countries. Moreover, recent experience indicates that the skills bottleneck has been overestimated in the past - or else that decreased demand, together with increased training and education efforts for the moment has rendered this issue much less critical. Consequently the following table cannot be accepted acritically: it represents an interpretation which is probably obsolete. The issue is a relevant one and developments will be followed carefully. Currently available studies on skills shortage in Europe136 assess that in relative terms skill shortages are higher in those countries where ICT has the highest weigh in total employment, i.e. Netherlands, or, as Sweden and Denmark, “face relatively high skills shortages today largely because they have been ‘early adopters’ of new technology”137. The following table at 1999 indicates, on average, higher shortages in total IT skills in countries where computer workers as percentage of total employees are higher.
135 Nearly a third of Silicon Valley’s 1990 workforce was composed of immigrants. OECD, “A New Economy? The Changing Role of Innovation and Information Technology in Growth” 2000 page 46. Furthermore, foreign workers represented more than a quarter of qualified ICT-jobs during the 1996-1998. 136 “Europe’s Growing IT Skills Crisis”, IDC, 2000 137 “Europe’s Growing IT Skills Crisis”, IDC, 2000, page. 5
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Table 2: Total IT skills shortage and computers workers (1999)
1999Demand Supply % Shortage % of total employment
Sweden 408646 360610 11.8 2.4
Netherlands 662403 588267 11.2 2.7
Germany 1988464 1767571 11.1 1.3
United Kingdom 1761153 1605942 8.8 1.7
Belgium 392003 359458 8.3 1.6
Finland 123535 113310 8.3 2.2
Italy 894636 825898 7.7 0.8
Denmark 127555 117804 7.6 1.9
France 1612473 1494821 7.3 1.6
Spain 480228 457971 4.6 0.9
Greece 14976 14420 3.7 0.3
E-commerce
SEAMATE Deliverable 2.1 provides a large number of data and tables illustrating the % penetration of ICT in E-Commerce in general and in European enterprises, also compared to non- European situations. The Deliverable 2.1 selection of penetration and diffusion data is quite interesting as it reports the situation disaggregated by sector as well as comparisons with extra-European countries. The conclusions it reaches, however, do not differentiate between different EU15 countries so that they do not stress the insight reached in the Sections 2.2.14.3 – Enhancing cultural competence as
a pre-requisite to knowledge production and society and 2.2.15 – Conclusions from the
preliminary data and trends screening to the effect that a vital consideration is the remarkable lag between EU15 countries. This concerns not just ICT penetration or adoption, but the very prerequisites of innovation per se. Lacking these, the new tools and networks will hardly impact favourably societal processes and the economy. The conclusion is that energetic policies for higher education, R&D, innovation are critically needed in laggard countries (Spain, Italy, Portugal, Greece). The data and trends reported below are thus integrated permitting to get a wide overall picture and assessment and also to analyse in detail disaggregated situations. Looking at the situation in Europe, the following table gives forecasts for EU E-commerce total volume from 2 different sources. The marked divergence between them suggests scarce quality of the data. Information on collection methods is scarce and definition of e-commerce is doubtful. Table 3: EU E-commerce total volume diverging forecasts
The "eEurope benchmarking report Feb 2002" 138, estimates that in Europe 22% of companies are buying online and 22.9% are selling online. The latter are distributed as shown in the following tables:
Table 4: European companies selling online by sector
Sector % of companies in sector services 30 %
distribution 25 %
manufacturing 17 %
construction 18 %
Table 5: European companies selling online by size
Size of companies (employees) % of companies in size class
more than 250 30 %
more than 50 21 %
less than 50 21 %
From source139 below: euinfoempl.pdf data on employment in ICT Europe from: http://europe.eu.int/comm/employment_social/soc-dial/info.soc/esdis/ index.htm it appears that 45% of European SME's are connected to Internet, but only 21% use it for exchanging information and 7% use it for distribution. Relevant data are reported in: R. Deiss, E-commerce in Europe, Eurostat Theme 4-12/2002, from which the following table is derived.
Table 6: Share of enterprises using HW or functions indicated (Dec.2000)
EU DK D EL E I L NL A P FIN S UK
Computer 92 95 96 85 91 86 91 88 92 89 98 97 92
Web access 68 87 67 51 67 66 55 65 76 72 91 90 63
Web site 46 63 67 29 7 9 41 35 54 30 60 68 50
E-purchasing 26 37 37 5 9 10 19 25 15 12 35 31 33
E-ordering 18 34 30 5 9 8 18 25 14 10 35 54 ..
E-payment 7 17 8 1 3 5 8 14 5 4 10 48 ..
138 eEurope benchmarking report Feb 2002 – from http://europa.eu.int/information_society/europe/benchmarking/index_en.htm 139 euinfoempl.pdf data on employment in ICT Europe from: http://europe.eu.int/comm/employment_social/soc-dial/info.soc/esdis/index.htm
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E-delivery 6 47 6 1 4 4 6 .. 3 2 46 65 ..
E-sales 19 28 31 6 6 3 10 23 12 6 14 12 16
Product info 13 .. 26 6 5 2 8 .. 11 5 29 .. ..
Take orders 12 24 22 5 4 2 7 23 11 4 14 17 ..
E-delivery 1 7 2 1 1 0 2 .. 1 1 .. 4 ..
IT spending on E-commerce applications by 700 European companies is given by the following table (data from EITO 2000) - since the sample is small, no significant extrapolation may be made from it.
Table 7: IT spending in 1998 and 2003 (sample of 700 EU companies)
No time series is available, though, so that forecasts are not feasible. These estimates don't specify whether or not E-commerce simply displaces sales from traditional channels nor whether firms engaging in E-commerce make a profit (most B2C firms don't). However, sales/revenues are the only indicator of activity available, and they give an idea of market size.
E-Business Benchmarking for SME's
The data on E-commerce activity of European enterprises from Sect. 2.4.3 are supplemented by the following data on SME's (Source: "Benchmarking National and Regional E Business Policies, Stage 1 -Synthesis report 7 February 2002 European Commission, Enterprise DG). It will be noticed that in some cases SME's appear to be lagging with respect to larger outfits, while in other cases they appear to be engaged in E-business more than larger ones. This finding sounds paradoxical as larger companies are probably more active and apt to modernise more promptly. The report states that the observed variations may depend on "different policy challenges in different Member States". It is to be feared,
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though, that these apparent discrepancies stem instead from an inherent scarce reliability of the data. However, it could be also a sign of real phenomena, which contribute to differentiate the way that national markets’ structures are responding and adapting to the challenges posed by the new economy. It is the scalability of the Internet that offers small niche players many of the same advantages enjoyed by large diversified firms in term of expanding the range of e-commerce customers and transactions. Nonetheless, the high incidence of SME’s over the total e-market can be taken also as a sign of structural delay of large firms to migrate to e-commerce and consolidate the overall e-business in their countries. The report also notes other minor inconsistencies, as e.g. the fact that Swedish SMEs rank first in ICT use but lag with respect to Germany, Holland and Denmark in E-commerce sales. It is also to be remembered that definitions used may vary widely. ICT use may range from mere word processing, to bookkeeping, use of Access, Excel and more sophisticated tools. The following table shows the data from the quoted source.
Table 8: SME E-business adoption rates in 2001
% of SMEs A DK E FI GR S UK D LU NL I NO
Using ICT 92 95 91 98 84 96 92 96 90 87 86 93
Web access 83 86 66 91 54 90 62 82 54 62 71 73
Own website 53 62 6 58 28 67 49 65 39 31 9 47
Use 3rd party website
26 n/a 28 n/a 8 n/a 11 21 13 n/a 26 n/a
Buying online 14 36 9 34 5 31 32 35 18 23 10 43
Selling online 11 27 6 13 6 11 16 29 9 22 3 10
While the above data contribute to defining the overall European situation, it is to be doubted that they can be used as inputs to a formal model. As anticipated, it will be more appropriate to define plausible scenarios prudently quantified.
Mobile commerce
The basis to predict the impact of M-commerce, still in its infancy, are three-fold:
• projections concerning the fast growing diffusion of cellular phones, which is however differentiated in the various EU countries;
• technological forecasting concerning both network standards (e.g. UMTS) and mobile devices standards (cellular phones but also new portable media, as palm-top etc.)
• reasoning about economic convenience and social acceptance of the various technical systems which the industry is going to produce, in relation with the needs and life-style of the customers.
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This factors will be fully analysed within SEAMATE. Some well known evidence already exists about the diffusion of cellular phones in Europe, as that taken from 140 below: This has already been discussed in Section 2.3.4 Section 2.3.5 discusses expectations and implications of the announced transition to UMTS and Third Generation mobile communicators. This whole sector has been expected to be revolutionised again and again. The interaction of incessant technological innovation, regulatory frameworks and business initiatives (sometimes initiated with excessive haste) make it very hard to form sensible opinions and forecasts. Consequently evidence of diffusion of M-commerce systems and revenues originated by offers to mobile phones subscribers are still very fragmentary. Some of this evidence is reported in the tables below, taken from: Mobile Commerce Epaynews.com - from www.epaynews.com
Table 9: Handheld Market Share USA and Europe, 2000
Platform USA Europe Palm OS 78.8 % 62.4 %
Win CE/Pocket PC 13.1 % 19.6 %
Symbian/Epoc .6 % 17.8 %
Other 7.5 % 7.5 %
Table 10: % of Wireless Web Users, 2001 - Source Accenture
USA 6 %
UK 10 %
Germany 16 %
Finland 6 %
Japan 72 %
Table 11:Research firm, US Commerce revenues
Research Firm US mCommerce revenues 2004 (estimated)
Merril Lynch G$ 20
Ovum G$ 19.2
Myers Reports G$ 4.74
Jupiter Research G$ 1.7
Herschel Shosteck G$ 1.7
Average G$ 9.27
140 EC-EUROSTAT – Telecommunication indicators in the Eurostat area – Working Group Statistics on Communication and Information Services, February 2001
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Table 12: Users of Wireless Financial services (Source TowerGroup)
Region 2000 2005 (est.) North America 450 k 34,970 k
Western Europe 3,890 k 76,550 k
Asia-Pacific 4,810 k 83,740 k
Table 13: Mobile commerce Revenues 2000-2005 (est.) in M US$ (Source Jupiter Research)
Global .4 1.5 3.4 7.7 14.4 22.2 USA - .1 .2 .6 1.7 3.3
Japan .4 1.2 2.1 3.5 4.5 5.5
E-work
The European Commission Report eWORK 2002141 provides the updated information on the status of new ways of work in the knowledge economy reported below. The Commission has proposed a wide definition of telework as “method of organising and/or performing work in which a considerable proportion of an employee’s working time is: away from the firm’s premises or where the output is delivered, and when the work is done using information technology and technology for data transmission, in particular the Internet”. This covers telework at home, alternation between work in the firm’s office and at home, mobile telework, and work in local telework centres. The results of the EC IST EMERGENCE project, partially reported below, applying a broad definition of telework142, indicate that the dominant forms of e-work by employees within organisations have become the use of remote offices, many of them call centres, and the employment of multilocational workers, rather than fully home-based e-work. In addition, the largest and strongly growing proportion of e-work involves outsourcing driven by the search for technical expertise (software development and support, creative work including design, editorial work, multimedia content generation, etc.), cost and quality considerations.
141 EC, eWORK 2002 – Status Report on New Ways to Work in the Knowledge Economy, eds. Peter Johnston, John Nolan, September 2002 142 The definition of “e-work” applied by the EMERGENCE project encompasses any work which is carried out away from an establishment and managed from that establishment using IT and telecommunication link for receipt or delivery of work.
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The mentioned EMERGENCE study collected data from employers of 18 countries, and combined them with data from European labour force surveys to develop a model of e-work.143 Four distinct types of “individual” e-workers are identified in the study: 1. Telehomeworkers: these are employees who use a computer and
telecommunication link to conduct their work and who are based wholly or mainly in their homes.
2. Multilocational e-workers: this is a much more numerous group, including employees who alternate between a home and an office workstation, or who work nomadically from multiple locations.
3. e-Lancers: these are self-employed workers who supply business services to clients using a computer and a telecommunication link.
4. e-Enabled self employed: albeit not included in the EMERGENCE survey, which concentrated on remote supply of business services, this category can nevertheless be regarded as a form of e-work, and it has been estimated with an indirect method144. It is made up of self-employed people who work from their homes but who do not supply business services. These people may be doing anything from managing a farm or rural tourism activity to running an electrical repair business. They are included in this category only if they require computers and on-line links to their customers in order to be able to function effectively.
The table below shows the estimates of individual e-workers in 2000 for the EU 15 countries:
Year 2000
Telehomeworkers (person equivalent) 810.000
Multilocational e-workers 3.700.000
e-Lancers 1.450.000
e-Enabled self-employed 3.080.000
TOTAL 9.040.000 Source: EMERGENCE analysis, 2001
The estimated total of EU e-workers is about 9 millions, and this figure coincides with that provided by other sources as well145. The EMERGENCE study produced also a business-as-usual projection of about 10 millions of new e-workers by the year 2010, and a positive scenario entailing widespread technological and organisational change, with about a triple number of new e-workers (27 millions). The study concludes that the willingness of employees and workers to embrace technological and organisational
143 EMERGENCE, Modelling e-Work in Europe: estimates, models and forecasts from the EMERGENCE Project, available at www.emergence.nu 144 this portion has been estimated using the UK labour force survey to determine what proportion of self-employed people in each sector were e-Enabled, and applying this proportion to the data on self-employment from the European Community Labour Force Survey (CLFS). 145 the EC IST ECATT project estimated that in 1999 teleworkers in Europe stood at 9.009.000 (see ECATT Project, Telework Data Report, Bonn, 2000). Another source, i.e. the SIBIS project (2003), provides a wider estimation of teleworkers, up to 13% of employed population in EU 15, based on surveys carried out on 2002/2003.
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change will be a decisive factor in shaping future working patterns in the EU. Moreover, new e-work facilities, via advanced mobile and handheld devices, are expected to spread across the workforce in the years to come. This could strongly extend the potential benefits of e-work, but will also create new challenges for safeguarding health and safety and the quality of working life.
E-training
According to the 2001 ASTD (American Society for Training and Development) State of the Industry Report between 1.8% and 3.5% of a company's payroll was spent on training expenditures in the last three (3) years. Payments to Outside Companies was 19.9% of training expenditures, while training expenditures have been distributed by course types as follows: 5% Basic Skills 4% Executive Development 7% Quality, Competition, and Business Practices 9% Interpersonal Communication 6% Sales and Dealer 7% Customer Relations 9% New Employee Orientation 6% Product Knowledge 7% Occupational Safety 11% Professional Skills 6% Managerial / Supervisor Skills 9% Information technology Skills 13% Technical Processes and Procedures Companies that currently have, or are in the process of developing, an E-learning regimen are: 3 Com ; Hewlett-Packard ; ABA (American Bankers Association) ; IBM ; Adobe ; Kraft/General Foods ; Black & Decker ; Microsoft ; Children's Hospital of Philadelphia ; Motorola ; Circuit City ; Cisco ; Texas Instrument ; Compaq ; U.S. Army ; Domino's Pizza ; Wells Fargo ; General Electric ; Westinghouse. The following table gives the breakdown for various training methodologies in the year 1999 and projections for the year 2002:
TRAINING METHODS 1999 2002
Instructor-Led classroom 79,9% 67,5%
Learning technologies 8,4% 18,2%
Other Self-paced sources 8,0% 9,7%
Other Methods 3,7% 4,6%
Literacy, Education, E-learning
The following data extracted from Sources indicated in the references (essentially UNESCO and OECD) are intended as a basis for scenario building together with data
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and considerations on E-commerce, E-economy, E-learning146. Here a first attempt is made to draw prima facie conclusions - some of which, however, appear to be plausible. Data used concern only Spain, France, Italy, UK, Germany, Greece and Portugal: the idea being to consider the larger and richer nations and those at the lower levels. This should be enough to serve as a basis for a preliminary conceptual discussion. The table below shows a group of indicators denoting the scale and quality of human resources in OECD countries147.
Table 14:Human resources indicators in OECD countries
The table clearly indicates a group of countries located in the north of Europe, i.e. Finland, Denmark, Sweden, United Kingdom, with two or more human resources indicators over the EU average. In these countries the outstanding level of these indicators is a clear sign of a good potential supply of skilled human resources148 The findings from the SIBIS Project149 also confirm such a trend. Based on surveys on 2002/2003, SIBIS data show that Finland, Sweden, the Netherlands, Denmark and UK lead the rank in the participation of labour force in lifelong learning training processes. The percentage of population with tertiary education is a more comprehensive indicator of the supply of human resources suitable to be employed in the information-based activities, because it covers the overall service sectors, other than the science and
146 for a good overview of existing education indicators of OECD, see OECD, Education at a glance, mentioned also in the Annex to this report 147 The European Innovation Scoreboard 2001. EC Innovations/SMEs Programme, 2001 148 It should be considered that the migration phenomenon (in particular in the US) could undermine the ability of this indicator to represent the supply of human resources. 149 SIBIS Project (2003)
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technical areas150. Furthermore, it is related to the entire population, taking into account in this way the trends towards the growing working age of the new economy workforce151. On the same track, the indicator of lifelong learning tries to capture, despite the difficulty152, a basic requirement of the knowledge economy: preparing the people to “learning to learn”153. Some of the indicators recorded, like minimum number of years of schooling in various countries, are hardly significant: the quality of tuition should be measured - a controversial and hard task. Reliability appears to be scarce. Illiteracy hovering around 1.5% is hardly credible. Portugal seems to be more honest at 7%. Data should be gathered on operational literacy (i.e. actual use of literacy to read/write) and also on average culture and knowledge of physical world and science (the latter based on US NSF survey, is now being used in EU). As regards telematic literacy CEPIS, the Council of European Professional Informatics Societies is providing a vast drive to upgrade both the public at large (mostly students and workers in various fields) and also advanced professionals. Many thousand training centres have been accredited (mainly in schools but also at private companies) to provide tuition, testing and certification for the ECDL (European Computer Driving Licence) level. At this level individuals should master: how to use a PC, word processing, EXCEL, PowerPoint, Access (database management), Outlook (E-mail). One shortcoming is that all of these procedures are standardised on Microsoft products. Another one is that the level of certification of training and test centres is very uneven so that ECDL graduation is not a very significant indicator. At the professional level CEPIS has initiated EUCIP (European Certification of Informatics Professionals) - a certification and competence development scheme. This is operational in UK, Germany and Italy: Ireland, Finland, Norway and Greece are planning to participate within 2002. In 2002 there are 1,000 training centres and many thousand test centres in the above nations. The EUCIP syllabus entails 400 study hours at the core level (planning, building, operating IT functions), 800 hours at the elective level (including vendor courses) and a vocational structure based on the Industry Structure Model of the British Computer Society. The following table elaborated from154 gives an overview of EU school attainment (caveat: actual syllabi and levels reached may differ markedly).
150 For a correct interpretation of results, international discrepancies in the “tertiary degree” requirements should be taken into account 151 P. Drucker has stressed the combined phenomenon of the progressive ageing of population and the increasing longevity of new knowledge workers. “The next society” A survey of the near future” The economist, November 3rd, 2001 152 The indicator has been calculated as the participation in any type of training course of education activity for the population between 24 and 65 years during the four weeks prior to the survey 153 As seen in the previous chapter, education policies and framework for lifelong learning schemes appear to be among the top priorities of European policymakers 154 OECD Education at a glance“, http://www.oecd.org/EN/home/0,,EN-home-4-nodirectorate-no-no--4,00.html
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Table 15: % of population having attained various school levels
A DK E FI GR S UK D IR I F B P
Less than 2ary 26 20 64 28 50 23 38 18 48 58 28 33 79
Upper 2ary 56 52 15 40 27 48 36 55 32 29 50 41 11
Tertiary 10 20 4 18 10 16 9 10 8 3 10 14 8
8 8 17 14 13 13 17 13 12 10 12 12 2
In Europe 92% of secondary and 70% of primary schools were connected to Internet in 2000. On the average there was one PC for every 18 students. 55% of teachers said they were computer literate. European graduates in S&T in 2000 were 3.1% of the population 20-24 years old. The corresponding % for the USA was 4.1%. Some of the OECD statistics are of dubious interpretation as, e.g., the GDP per capita annual growth rate due to human capital (1981-97) (see Table A3.1 -155), which is reported as computed as result of multivariate regressions. In order to assess and measure the average level of culture of different countries it is necessary to analyse the penetration or diffusion of abilities in:
• reading/writing
• using mathematical tools
• using science facts and methods
• performing job related tasks
• interpreting concepts, notions and names from past and present human endeavours. There have been recent attempts to build indicators of the first 3 types of skills listed above (reading and writing, mathematics, science) for the knowledge society, but they need to be further developed and, above all, included into the circuit of official statistical processes, e.g. promoting a Community Literacy Survey. In particular reference is made here to the PISA (Programme for International Student Assessment) experience. PISA is an internationally standardised assessment administered in 32 countries (of which 28 are members of OECD) to samples between 4.500 and 10.000 of 15 years old students. Although the assessment of cross-curriculum competencies is an integral part of PISA, its aim is to define knowledge and skills not merely in terms of mastery of the schools curriculum but in terms of abilities in adult life. These will assess the ability to read and write, but also mathematical, scientific and technological literacy. Standard literacy is disaggregated on 5 levels from sheer literal understanding to ability to retrieve relevant information, to interpretation of text and its implications, to reflection and evaluation of consistency. Mathematical performance is assessed beyond the knowledge of standard formulas and problems, to encompass logical analysis of processes and situations to be schematised by means of formal tools. Scientific
155 A3.1 - Decomposition of changes in annual average growth rates of GDP per capita - oecdeconhum.xls, from www.oecd.org\statistics
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competence is evaluated not just on notions, but on the ability to detect causal relationships in situations involving: life/health or earth environment or technological processes. In the 3 fields considered, ratings were constructed in such a way that 500 is taken as the assessment for the median - with 2/3 of the sample being rated between 400 and 600. PISA is a long-term programme of the OECD that will be developed in three year cycles. The 2000 assessment is the result of the first cycle in which two-thirds of testing time were devoted to reading literacy and only a summary of skills was provided for the other knowledge and skills domains. The second cycle ending in 2003 will be devoted mainly to mathematical literacy and the third one (2006) to scientific and technological literacy (Frey, 2002). It is evident that, with this timing, PISA results will be not immediately useful for the analysis of new economy trends. Moreover, PISA is limited to assess the literacy skills of young students, while there is the need to extend investigation of literacy skills also to adult population. In this regard, also the International Adult Literacy Survey (IALS), whose first report was released in 1995 (IALS, 1995), must be mentioned. This survey compares the literacy skills of people of different age from different countries, by conducting a sample survey of representative households. But IALS has two flaws: it considers only people between 16 and 65 years, thus excluding people older than 65 who represent a growing percentage of the European population, and it doesn’t include explicitly mathematical, scientific and technological literacy, as PISA does. Therefore, there is really the need to innovate on current literacy data, extending the PISA methodology to wider samples of population and rendering the survey more frequent, in order to get timely data. We think it would be appropriate to define and administer widely a Community Literacy Survey.
GDP, employment, productivity, ICT investment and market value
Additional data useful to feed the IST scenario building process are included in: "The Impact of the E-Economy on European Enterprises: Economic Analysis and Policy Implications", COM(2001) 711 final of 29.11.2001. This report is discursive and adds little information to the general picture. It is worthwhile, though, to record some relevant data which help to suggest causal links between socio-economic success policies and other factors to be analysed. The following table shows annual growth in GDP, employment and productivity for the period 1996-2000.
The following incomplete data are relevant and have to be complemented with additional inputs:
Table 17: ICT Investment as % of GDP
1992 1999
USA 2.6 4.5
EU15 1.81 2.42
E 1.58
UK 3.76
Data on IT and ICT market value are supplied in "The EU Economy Review 2000", Chapter 3 - "Economic Growth in the EU: Is a New Pattern Emerging?" (available on: http://europa.eu.int/comm/economy_finance/publications/european.economy/the_eu_economy_review2000_eu.htm/) The following table gives data on the ICT market value in the EU. The source is EITO: as previously noted in the section about PC penetration, EITO supplies scanty indications of sources and methodology.
Table 18: ICT market value in the EU (G€), source EITO 2000
The point being made about this caveat and about the additional one that Volterra Lotka equations should be used with caution when dealing with money values, an attempt was made to fit logistic curves to the time series for total IT market and total TLC market. The analysis provided a value of the asymptotes of 1567 G€ for the IT market and of 517 G€ for the TLC market, to be reached between 2030 and 2050. Although standard errors were quite low (respectively 8E-04 and 4E-03) - these projections are scarcely reliable. The 2 diagrams are represented below. The values computed for 2010 are 543 G€ for the IT market and 454 G€ for the TLC market: their sum (1,000 G€) will be used as a projection in the outline of the business as usual scenario presented in a subsequent section.
189
Data on innovation from European Commission DG Research “Science, Technology and Innovation Key Figures (2001 and 2003-2004 issues), “European Innovation Scoreboard 2003” and the “OECD Science, Technology and Industry Outlook and Scoreboard 2001”
These documents respond to a request of the Lisbon European Council meant to strengthen social cohesion and becoming the most competitive and dynamic knowledge-based economy in the world within the next decade. They analyse statistical data on 17 indicators in 4 areas: human resources; knowledge creation; transmission and
190
application of new knowledge; innovation finance, output and markets. They depict achievements and trends, performances and European convergence in innovation. Care should be taken to interpret the data in the documents since they refer to different years for different countries; yearly growth data are deduces from 3 years periods which vary from case to case. Also time series are not given: most data correspond to a single year; trends are identified by comparing some years' data with the average of other years since the years considered are not always the same, trend variations cannot be assessed - or false conclusions may be drawn. However, the detailed data provided in the mentioned documents (see www.cordis.lu/innovation-smes/src/policy htm) are useful to make comparisons between EU15, USA and Japan, and also to follow the trends of the relevant indicators. These results may well be used in conjunction with others with the scope in mind of building scenarios. It would be too ambitious to try and use these data together with others to attempt building formal models. The "OECD Science, Technology and Industry Outlook and and Scoreboard " (2001 and 2003 Issues) discusses the mechanisms driving growth: information technology, innovation and entrepreneurship. It provides a host of internationally comparable data to analyse trends in knowledge based economy, subdivided in 4 sections:
• Creation and diffusion of knowledge (public and private R&D, human capital, patents)
• Information economy (ICT, investment in and product of; influence on trade)
• Global integration of economic activity (international cooperation and alliances) It illustrates the contributions of ICT, software and TLC to the increase of GDP and GDP per capita. Investments in ICT account for an increasing share of total investments and in 1996 investments in TLC infrastructures surpassed in the US investments in highway infrastructures. An important factor is cost of access: in USA on the average .6 US$/hour, whereas in Europe it is 1.6US$/hour with peaks in Eastern Europe at 2.5US$/hour. E-commerce has been prospering more in countries where access to Internet is unmetered (USA, Australia, Canada, Switzerland). Other relevant factors are: educational attainment, innovations and inventions leading to patents awards. It appears that the European innovation performance continues to lag behind that of the USA. The following diagram (European Innovation Scoreboard 2003 Source) depicts the situation in 2002 and shows that the gap is wider for items like R&D and ICT expenditures as well as S&E graduates. These are the prerequisites for future upsurges of activity and improvement of the situation. Consequently any comparison of scenarios assumptions will have to take into account that a more pessimistic stance should be adopted for the future of Europe. The ambitious ultimate goals of the Lisbon European Council run the risk of not being attained unless strong and better integrated policies are adopted and implemented.
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Acceding and Accession Countries (AAC13) ICT Situation and Impacts
A survey and analysis of the ICT sector in AAC13 was carried out in the framework of the Enlargement Futures Project at IPTS (Institute for Prospective Technological Studies, Joint Research Centre - www.jrc.es ): E. Gourova, J.C. Burgelman, M. Bogdanowicz, C. Herrmann - Information and Communication Technologies, Final Report - March 2002. (Report EUR 20247). In the present section some highlights and comparisons to the EU15 situation are presented, integrated with data from other sources as indicated. Positive developments of ICT and hence positive socio-economic impacts in AAC13 are peculiarly conditioned by the evolution of telecommunications, In the last decade this sector underwent a radical transition from centrally planned state monopoly to market conditions, having to cope with a serious lack of financial resources and outdated telecommunications infrastructures (except in Malta and Cyprus, already up to EU15 standards). In 2001 the transition to digital switching and the construction of digital backbones had progressed very considerably. The following table shows some key data on demography, economics, PC and Internet penetration.
Table 19 Population, GDP, PC and Internet Use in 2000 Country Popu-
lation M
GDP G€ (1)
GDP k€/ inhab
GDP % Growth/ Year (2) '95-2000
PC's in use K
PC's in use/ 100 inhab
Internet users k
Int'net users/ 100 inhab.
Bulgaria 9 12.2 1.365 - 1.2 396 4.4 386 4.3
Cyprus .5 2.2 4.4 4.8 140 28 120 24
Czech Rep. 10.4 54.6 5.25 .2 1362 13.1 1000 9.6
Estonia 1.6 4.5 2.8 5.2 216 13.5 * 366 23
Hungary 10.5 54.5 5.2 4.05 777 7.4 * 715 6.8
Latvia 2.5 5.6 2.25 4.8 205 8.2 * 150 6
Lithuania 3.8 7.1 1.87 3.2 22.4 5.9 * 103 2.7
Malta .35 4 11.4 4.3 73.5 21 40 11.4
Poland 38.4 164 4.26 5.2 5952 15.5 2800 7.3
Romania 23.2 32.8 1.41 - 1.9 742 3.2 800 3.4
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Country Popu-lation M
GDP G€ (1)
GDP k€/ inhab
GDP % Growth/ Year (2) '95-2000
PC's in use K
PC's in use/ 100 inhab
Internet users k
Int'net users/ 100 inhab.
Slovakia 5.3 22.5 4.25 4.1 392 7.4 * 650 12.2
Slovenia 1.9 23.2 12.2 4.5 519 27.3 250 13.1
Turkey 66.5 206 3.1 n.a. 3059 4.6 2000 3
Total CC13 175.8 593.2 3.37 **
3,2 ***
13856 7.88 ** 9380 5.3
* figure for 1999 ** average for CC13 *** average excluding Turkey (1) 2001 data from www.eia.doe.gov/emeu/iea ; (2) Data From www.ebsummit.org/pdf/McKinsey_report.pdf The data collected here appear not to be very reliable, as different sources report other values often with large discrepancies. The previous Table shows that AAC13 have a population equal to 47% that of EU15 and a GDP equal to 8% that of EU15 (which was about 7,500 G€ in 2001). According to OECD data for the 7 AAC13 countries admitted to NATO (published in the International Herald Tribune of November 22, 2002) are those listed in the following table: consistently higher than the ones in the previous table except for Slovakia and Slovenia.
Country GDP 2001 (G€)
Bulgaria 15.3
Estonia 6.2
Latvia 7.9
Lithuania 13.9
Romania 34.4
Slovakia 19.9
Slovenia 19.9
A marked heterogeneity between different AAC13s is noticeable. E.g. only in Slovenia, Malta and Cyprus penetration of PC's exceeds 20% - but these 3 countries account for a minute percentage of the total AAC13 population. In the last years GDP growth in AAC13 has been considerably higher than in EU15, with the exceptions of Bulgaria and Romania. EU enlargement is expected by some to raise AAC13 GDP growth by 1 percent annually or more. However at the end of 2002 there are serious doubts on the short term growth of GDP for many EU15 countries, notably France and Germany. Consequently it would be very hard to anticipate the timing of some of the CC13s possibly reaching the level of lower income EU15 countries. Even for the better equipped and lively AAC13's that moment is probably more than a decade and a half away. It is apparent that under many respects Turkey represents an "odd man out" both culturally and economically in the set of the 13 countries. However the probability of EU enlargement including Turkey over the short term appears low enough that the quoted peculiarities may not be attributed excessive importance.
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Other indicators of ICT level published by UNCTAD156 are shown in the following Table.
Table 20 Phones, cellulars, TV sets, investment in TLC in 2000
Country Phone lines/-100 inhab.
Mobile phones/100 inhab.
TV sets/ 100 inhab
5-year investment in TLC - M$
Bulgaria 35 4.2 40.8 320
Cyprus 54 19 15.2 370
Czech Rep.
37.1 19 46.7 5251
Estonia 35.7 27.4 50.4 258
Hungary 37.1 16,2 44.5 3039
Latvia 30 11.5 64 458
Lithuania 31 9 42 388
Malta 51 9.7 53.6 87
Poland 26.3 10.2 41.3 4522
Romania 16.7 6 24 1330
Slovakia 30.7 17 41.2 1173
Slovenia 37.8 30.9 35.6 514
Turkey 26.5 12.4 32.6 2611.
Data for 2001 were unavailable, but a Reuters report of June 2002 indicated, that, e.g., mobile telephone penetration for AAC13 had grown from the previous year to 31% - still less than half the EU15, where in 2001 penetration has reached 72% - a marked increase from the level reported in Sect.2.3.4. The average level of culture, proficiency and school accomplishments is quite variable among the AAC13, with Turkey and Malta reaching estimated adult illiteracy rates of about 10%. Hungary, Poland and Czech Republic possess good schools (also advanced) and a higher cultural level. This situation is partially reflected in the unemployment which hovers around 6% for Hungary, Czech, Cyprus, Malta, Romania, Slovenia, Turkey and around 16% for Bulgaria, Estonia, Latvia, Lithuania, Poland and Slovakia. The following table from EITO 1998 compares IT hardware sales in EU15 and in AAC13.
Table 21: IT hardware sales in 1998 (units)
Western Europe
Eastern Europe
Unix servers 129,316 7,641
NT servers 272,100 19,812
Other servers 369,251 67,431
Workstations 210,077 6,040
PCs 19,824,095 2,414,300
LAN Cards 15,388,400 1,130,112
156 see http://stats.unctad.org/public/eng/TableViewer
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Drawing preliminary conclusions from the above analysis, the overall situation concerning EU enlargement to include AAC13 can be very roughly summarised as follows:
• ICT, innovation and economic indicators all point to AAC13 being one order of magnitude down with respect to EU15
• The need to upgrade infrastructures and human capital entails that investment needs are going to be in the next few years more weighty than trade volumes increases
• A modest positive influence on EU15 GDP may be expected as a consequence of increased trade - but it is debatable whether this effect could also exist without enlargement becoming a reality (note here that EU trade with AAC13 represents in 2001 11% of extra EU trade, corresponding to 4% of overall EU trade. Only for Germany AAC13 trade represents 10% of total foreign trade).
• It is to be expected that techno-economic development of AAC13 will take place at a faster pace for upper tier countries (Hungary, Czech Republic, Poland, Slovenia, Cyprus). This heterogeneity may detract from positive impacts.
• Policies aiming at higher level and mass cultural and training investments may fail to produce local fast ICT growth, if improved economic and ICT growth conditions in EU15 attract migration of highly skilled workers from AAC13. This process, though, may not materialise if slow growth, or recession prevail in EU countries.
• Controversies are likely to be produced to influence decisions on investments vs. subsidies
195
Annex 2: List of state-of-the-art IST indicators
INDICATORS TIME
COVERAGE
EXPLANATION MEASUREMENT
ISSUES
SOURCE
I
ICT Sector Indicators
1
MAIN
TELEPHONE
LINES IN
OPERATION
1980- 1999 Measured as the number (thousands) of main lines in a country. A main line is a telephone line connecting the subscribers’ terminal equipment (e.g., telephone set, facsimile machine) to the public switched network and which has a dedicated port in the telephone exchange. The term is synonymous with “main station” or “Direct Exchange Line (DEL)”, commonly used in telecommunication documents. In 1999, diffusion of main telephone lines in EUROSTAT countries edged up 210,354.19 thousands units, most of which located in Germany (48,300 thousands), France (34,100 thousands) and Italy (26,506 thousands).
Some telecommunication operators report access lines rather than main lines. The former include extensions on private Automatic Branch Exchanges (PABXs), that are billed separately or that have their own telephone number. Furthermore, subscribers may share the same line or use extensions from a private extension. Thus, one main line could serve several subscribers. Some countries’ data (e.g., Belgium, the Netherlands, Norway, Portugal and Switzerland) include ISDN channels or digital lines from 1994 .
Telecommunication Indicators in the EUROSTAT Area, ITU (International Telecommunication Union), 2001.
2
INTERNATION
AL
OUTGOING
TELEPHONE
TRAFFIC
1980-1985- 1990 1995/1999
Measured as the total completed telephone traffic measured in million of minutes that originated in a specified country with a destination outside the country itself. As for 1999, Germany holds the highest figure for international telephone traffic (7,000 million of minutes), followed by UK (6,066) and France (4,386).
The treatment of paid vs. free traffic and collect and country can differ. For some countries (Sweden), data since 1993 are ITU estimates, whereas for the Netherlands data from 1992 are not comparable with earlier years due to changed accounting.
Telecommunication Indicators in the EUROSTAT Area, ITU (International Telecommunication Union), 2001.
196
INDICATORS TIME
COVERAGE
EXPLANATION MEASUREMENT
ISSUES
SOURCE
3 MOBILE
TELEPHONE
SUBSCRIBERS
1980-1985- 1990 1995/1999
Number of subscribers (thousands) to an automatic public mobile telephone service, which provides access to the Public Switched Telephone Network (PSTN) using cellular technology. In the 1980s merely Nordic countries could boast a certain diffusion of mobile phones. Remarkable increases in the number of subscribers can be highlighted from 1995 to 1998. Some countries doubled substantially their figures in time (e.g. Italy with 6,422 thousands subscribers in 1996 and 11,737 in 1997 up to some 30,296 thousands in 1999 as well as Spain The Netherlands and Portugal). Italy ranks first, followed by Germany (23,470 subscribers) and France (21,433 thousands).
Data do not include the number of subscribers to public mobile data services, private trunked mobile radio, telepoint, non-cellular mobile, fixed cellular, or radio paging services.
Telecommunication Indicators in the EUROSTAT Area, ITU (International Telecommunication Union), 2001.
4
FULL-TIME
TELECOMMUN
ICATION
STAFF
1980-1985- 1990 1995/1999
Measured as the number (thousands) of full-time staff employed by telecommunication network operators in the country for the provision of public telecommunication services. While for some countries a steadfast increase in the number of employed people in telecommunication operators was reported all over the two decades (e.g., France with 156.40 in 1980 up to 170.50 in 1999 and the Netherlands with 27.90 in 1980 and 35.59 in 1999), for other countries like Italy (104 in 1980 up to 79.03 in 1999) a progressive fall or a swinging trend like in UK (246.70 in 1980 down to 142 in 1996 and up to 202.35 in 1999) was reported.
As far as possible, staff not working principally for the provision of telecommunication services are excluded
Telecommunication Indicators in the EUROSTAT Area, ITU (International Telecommunication Union), 2001.
5 TELECOMMUN
ICATION
INVESTMENT
1980-1985- 1990 1995/1999
Measured as the annual expenditure (in million US$) associated with the acquiring ownership of property and plant used for telecommunication services. Investments have more than doubled over two decades in UK (2,906 million US$ in 1980 up to 13,007 in 1998 down to 9,191 in 1999) and Germany (5,494 in 1980 edging up to 11,915 in 1990 down to
Data also includes investments in land and buildings.
Telecommunication Indicators in the EUROSTAT Area, ITU (International Telecommunication Union), 2001.
197
INDICATORS TIME
COVERAGE
EXPLANATION MEASUREMENT
ISSUES
SOURCE
10,896 in 1999), whereas France kept a steadfast pace and the Netherlands raised year after year related investments allocation.
6 TELECOMMUN
ICATION
REVENUES
1980-1985- 1990 1995/1999
Measured as the revenues (turnover) in million US$ received from providing telecommunication services in the country earned during the financial year under review. US$ values are obtained by the applying the average annual exchange rate.
Data may not be comparable because of a series of factors. First, it is assumed that the data relate to revenues of all PTOs providing service in the country. Furthermore, data do not often include revenues from cellular mobile phones, radio paging and or data services if these services are not provided by the main fixed-link operator. Moreover, operators may have subsidiaries with financial activities unrelated to telecommunication services that may be included. Finally, differences in both definition and accounting rules may affect the data.
Telecommunication Indicators in the EUROSTAT Area, ITU (International Telecommunication Union), 2001.
7 PERSONAL COMPUTERS
1990, 1995/1999
Measured as the number of computers (millions) for personal use. In early nineties, merely Germany (6.50) and UK (6,.0) pointed out a substantial diffusion of PC’s amongst people. They also rank first in 1999 (24,40 and 18,00), although other major countries such as Italy (11,00) and Spain (4,80) are still far from reaching such a widespread use of the PC.
Data do not include computers that are accessed via a terminal such as super, main frame or mini computers.
Telecommunication Indicators in the EUROSTAT Area, ITU (International Telecommunication Union), 2001.
8 INTERNET
HOSTS
July 1997-Oct. 2000 1980-1985- 1990 1995/1999
Measured per 1,000 inhabitants. It takes into account the gTLDs (global Top-Level Domains) distributed to country of location. The indicator includes any computer system connected to the Internet (via full-time or part-time, direct or dial-up connections), so
Surveys of Internet hosts are undertaken by several entities, including Network Wizards, RIPE (which produces monthly surveys of Internet hosts for
OECD Science, Technology and Industry Scoreboard, OECD, 2001.
198
INDICATORS TIME
COVERAGE
EXPLANATION MEASUREMENT
ISSUES
SOURCE
that hosts can be thought as an indicator of the minimum size of the public Internet. A host is a domain name that has an IP (Internet Protocol) address “record” associated with it. In October 2000 the OECD average was 81.5 hosts per 1,000 inhabitants, whilst the EU average being 34.7 and the USA far ahead with 234 hosts. Although only Sweden (106 hosts per 1,000 inhabitants in October 2000) matched the growth rate in the USA between July 1999 and Oct. 2000, recent growth rates have been uneven and large gaps between countries remain.
countries in their region) and Telcordia Technologies, providing a daily update of the number of Internet hosts and top-level/second-level domains by country.
9 ISDN
SUBSCRIBERS
1980-1985- 1990; 1995/99 1995/1999
The indicator show the number of subscribers to the ISDN (Integrated Services Digital Network), a system of digital phone connections that allows data to be transmitted simultaneously across the world using end-to-end digital connectivity. For instance, a basic ISDN connection can provide 2 channels whereas a primary connection can provide 30 channels. Data indicate that ISDN usage is beginning to accelerate, because of a high bandwidth demand for applications such as Internet access and video conferences
Some operators count the number of circuits available rather than subscribers. Then the former are converted to equivalent subscribers numbers. ISDN channels taken into account are 64 kbit/s voice equivalent.
OECD Science, Technology and Industry Scoreboard, OECD, 2001.
10 INTERNET
ACCESS
PRICES
1999-September 2000 Measured in PPP US$, including VAT. Another barrier to ICT diffusion is the cost of Internet access for consumers. Prices continue to differ widely and the differences are among the largest for any communication service. Price differences for consumer access reflect the fixed and variable telephone charges set by telecommunications firms, but also the fees charged by the leading Internet service providers (ISPs). For 40 hours of Internet access, at peak and off-peak times, differences in Internet access cost for consumers are even more
The OECD basket includes the line rental, public switched telephony network (PSTN) usage charges and the ISP fee. The line rental charge is used to balance the fact that countries that traditionally did not charge for local calls had higher fixed charges, whereas those that did had lower ones. The use of a fixed charge does not imply that
OECD Science, Technology and Industry Scoreboard, OECD, 2001.
199
INDICATORS TIME
COVERAGE
EXPLANATION MEASUREMENT
ISSUES
SOURCE
noticeable. At peak times, countries which traditionally have had unmetered local calls – Australia, Canada, Mexico, New Zealand, the United States – are among the least expensive. Turkey, where a call allowance is included in the line rental, is also inexpensive.
customers would need an additional line, as most residential customers use their PSTN line to access Internet services.
11 USE OF
INTERNET IN
SCHOOLS
1998/1999
Measured as the Percentage of schools which have access or intend to have access to the Internet for instructional purposes, by level of education, expressed as a percentage of students. In order to assess national policies with regard to developing the use of the Internet in schools, the IT specialists in the sampled school were asked whether the school was on-line and, if not, whether the school planned to provide its computers with Internet connections by 2001 At the time of the survey, over 75 per cent of primary schools were connected to the Internet in Canada, Finland, Iceland and New Zealand. With the exception of Italy, where 28 per cent of primary schools were connected, in all other countries participating in the survey more than half of primary schools were connected to the Internet.
Education at a Glance , OECD Report 2001.
12 TV CHANNELS
PER 100
INHABITANTS
1990 1995/1999
Measured as the number of TV channel per 100 inhabitants in the OECD area.
Telecommunication access paths include the total of fixed access lines and cellular mobile subscribers
OECD Science, Technology and Industry Scoreboard, OECD, 2001.
13 CABLE TV
SUBSCRIBERS
1980-1985- 1990 1995/1999
Measured as the number of subscribers (thousands) to the cable television. For Belgium and the Netherlands data are available from 1980, highlighting a substantial number of cable television subscribers in the 1980s in these two EU countries. Presently, Germany (18,550 thousands) and the Netherlands (6,120 thousands) shows the highest
Some countries’ data include Microvawe Multi-point Distribution systems (MMDS) or Satellite Master Antenna Television (SMATV) connections.
Telecommunication Indicators in the EUROSTAT Area, ITU (International Telecommunication Union), 2001.
200
INDICATORS TIME
COVERAGE
EXPLANATION MEASUREMENT
ISSUES
SOURCE
figure for this indicator, whereas Spain (523.69 thousands) and Italy (160 thousands) rank last
14
NUMBER OF ENTERPRISES IN THE ICT SECTOR
1995/1998
In 1998, 88% of EU enterprises engaged in the ICT sector were operating in services and 12% operated in manufacturing. Whilst the number of ICT manufacturing enterprises is stagnating, the number of ICT service enterprises has increased strongly in the recent past. The United Kingdom is the EU country with the largest number of ICT firms followed, at a distance, by Italy, Germany and France. The United Kingdom is also the country with the largest number of ICT service enterprises, representing about one third of the EU total. The USA’s proportion of services to manufacturing firms is similar to that of the EU-15, whereas Japan is the country with the highest share of ICT manufacturing enterprises.
Information Society Statistics, Statistics in Focus, EUROSTAT , Theme 4 – 34/2001
15 EMPLOYMENT IN THE ICT SECTOR
1995/1998
Four countries (Ireland, Sweden, the United Kingdom and Finland) have a share of ICT employment in total employment above both the EU-15 average and the USA. Portugal has the lowest share of ICT employment in the EU. In 1998, the share of employment in the ICT sector in the EU was 2.8% below both the USA and Japan. The service sector represents 63% of the total ICT workforce in the Union. Amongst these, 38% (24% of the total of ICT employees) are working in telecommunication services. The UK was the largest employer of staff in ICT with well over one million staff in 1997.
Information Society Statistics, Statistics in Focus, EUROSTAT , Theme 4 – 34/2001
16 VALUE ADDED OF THE ICT SECTOR
1995/1998 Finland ranks first in terms of value added per person employed in the ICT sector (83 000 Euro in 1998) followed by Ireland, Belgium, Austria and the United Kingdom (no data available for Germany, Greece and Luxembourg). Services act as the main
Information Society Statistics, Statistics in Focus, EUROSTAT , Theme 4 – 34/2001
201
INDICATORS TIME
COVERAGE
EXPLANATION MEASUREMENT
ISSUES
SOURCE
activity producing value added, out of which telecommunication ones played a significant part, weighing around 40% of the total EU-15 value added in 1998. In Ireland and Finland, however, the manufacturing sector produces more than 50% of the ICT value added.
17 TURNOVER OF THE ICT SECTOR
1995/1998 Turnover comprises the totals invoiced by the observation to market sales of goods or services supplied to third parties. Six countries, Ireland, Denmark, Finland, Portugal, the Netherlands and Austria had a turnover per enterprise substantially above the EU average in 1998. Ireland, Finland and Sweden led in terms of turnover per person employed if Germany is not considered (results for Germany relate to enterprises with 20 persons employed and more and are thus overstated compared with the other countries). In 1998, the European Union’s turnover for the ICT sector was composed around 37% by manufacturing, 22% by telecommunication services and just over 40% by other ICT services.
Information Society Statistics, Statistics in Focus, EUROSTAT , Theme 4 – 34/2001
18
ICT IMPORT, EXPORTS AND TRADE BALANCE
1996/2000 On average, the EU’s ICT exports grew more than imports between 1996 and 2000 with Ireland leading the way with an average export growth of 31% over the period. However, in absolute terms Germany and the UK were the greatest exporters of ICT products. Only the Netherlands saw a reduction in its ICT exports between 1999 and 2000. A very interesting element is that in 2000 only Finland, Sweden and Ireland succeeded in selling more ICT goods, than they bought from abroad. The Netherlands and Portugal actually witnessed a fall in ICT imports between 1999 and 2000.
Information Society Statistics, Statistics in Focus, EUROSTAT , Theme 4 – 34/2001
202
INDICATORS TIME
COVERAGE
EXPLANATION MEASUREMENT
ISSUES
SOURCE
Between 1996 and 2000, the EU trade deficit for ICT goods narrowed on average by 4.3% per year. While the trade deficit increased between 1996 and 1998 it fell sharply in 2000. While 12 EU Member States showed trade deficits in ICT goods (the UK, Italy and Spain with the highest absolute values), Finland, Sweden and Ireland showed a considerable export surplus as regards ICT goods, amounting to 9% of GDP in Ireland.
19 SHARE OF ENTERPRISES USING ICT
December 2000
Measured as the share of enterprises using selected types of Internet access, ranked by xDSL. The main findings of the survey are that 92% of enterprises (of 10 employed persons or more) used computers at the time of the survey, 75% had web access and 38% had their own web site at the end of 2000; IT has made its way into practically every large enterprise in the EU and only 8% of the SMEs were not equipped with computers at the time of the survey. When it comes to web access, or web presence, the gap between larger enterprises and SMEs widens The main barriers to Internet use indicate that technical ones (security, hardware and know-how) were felt to be more important than economic ones (notably cost). Analogue connection (dial-up access) is the traditional way of access. ISDN access is somewhat faster (up to 64 kbits/sec. per channel) and is currently the most popular digital method of access. DSL also relies on a standard telephone line, but uses a technology that allows broadband connections.
Data drawn from the results of the survey for the 2000/2001 reference year.
E-Commerce in Europe, Industry Trade and Services, Statistics in Focus, EUROSTAT , Theme 4 – 12/2002
20
USE OF E-COMMERCE FOR PURCHASES
December 2000
Measured as the share of enterprises using e-commerce for purchases (%) . Enterprises turn to e-commerce to purchase at least some of the goods and services needed for their activity purchasing (including all networks, IP or not) still represented a
All is the weighted average for the Member States appearing in each line of the table. Figures concern e-commerce made via all kinds of computer networks, not
E-Commerce in Europe, Industry Trade and Services, Statistics in Focus, EUROSTAT , Theme 4 – 12/2002
203
INDICATORS TIME
COVERAGE
EXPLANATION MEASUREMENT
ISSUES
SOURCE
very small share of the purchases made by enterprises, although it reached 1% or more of the total in more than one-quarter of Finnish, German and Swedish enterprises – B2B market places have emerged to facilitate transactions between enterprises. These consist of specialised sites that allow buyers and suppliers to meet each other virtually and to trade. Enterprises of business services were the most frequent users of these marketplaces for purchases.
just the more talked about Internet Protocol (IP) based ones.
21 USE OF E-COMMERCE FOR SALES
December 2000
Measured as the share of enterprises using e-commerce for sales (%). In 2000/2001, enterprises were less active selling by electronic means than purchasing. Indeed, only 19% of surveyed enterprises made use of e-sales (see table 4) and only 6% of enterprises used e-sales for more than 1% of their sales. Contrary to e-purchasing, sales via electronic commerce addresses both the business-to-business (B2B) and the business-to-consumer (B2C) markets; the latter relies mostly on the Internet rather than other networks and this was virtually non-existent as a distribution channel before 1998. enterprises in the sector of hotels and restaurants were the most active suppliers (3.1%), whilst they were at the same time the least active buyers. Manufacturing enterprises were clearly the least prone to sell on-line (1.2%) via B2B market places.
All is the weighted average for the Member States appearing in each line of the table.
E-Commerce in Europe, Industry Trade and Services, Statistics in Focus, EUROSTAT , Theme 4 – 12/2002
204
INDICATORS TIME
COVERAGE
EXPLANATION MEASUREMENT
ISSUES
SOURCE
II
Innovation & Structural Business Indicators
22
GROSS
DOMESTIC
EXPENDITURE
ON R&D
(GERD)
1981-1985 1990/1999 Measured as: 1) a % of GDP; 2) in millions of 1995 PPP US$ . It is the domestic R&D-related expenditure of a country for a given year and thus the main aggregate used for international comparisons for R&D expenditure. Increase in the R&D expenditure between 1994 and 1999 was reported in the USA: this widened the gap in volume of spending between the latter and EU and Japan. In 1999 the R&D expenditure in the USA accounted for 44% of the OECD total, whereas EU edged up to 28% and Japan 17%. The low average growth in R&D expenditure in the EU is due to declining growth in the major European economies. Indeed, this expenditure grew by 1.4% in Germany and 1.2% in the UK. R&D expenditure declined in Italy only. On the other side, R&D expenditure relative to GDP increased continuously in the USA and Japan, while remaining stable in the EU. Sweden, Finland and Japan allocated more than 3% of their GDP to R&D expenditure, while in Ireland the growth in R&D expenditure reached 13% annually.
The magnitude of estimated resources allocated to R&D is affected by some national characteristics, such as improvements in national surveys on R&D (coverage of firms especially in the service sectors – for the USA , Norway, the Netherlands and Japan - improved estimates of resources allocated to R&D by the higher education sector), improved national comparability, breaks in the time series (for Germany and the USA) and probable underestimation of R&D data (the USA and Sweden)..
OECD Science, Technology and Industry Scoreboard, OECD, 2001.
23
R&D BY
BUSINESS,
GOVERNMEN
T, HIGHER
EDUCATION
1981-1989- 1991-1993- 1995-1997-1999
Measured as a % of GDP for the three main sectors of performance: a)business enterprise; b) government; c) higher education. In EU countries, R&D performed by the higher education sector represent about 0.38% of GDP in 1999, while in the USA the figure is slightly lower and in Japan it accounts for 0.4%. On the other hand, in 1999 R&D performed by business sector in the EU jumped up to 1.20% from 1.14% of the previous year, while in the USA it accounted for
Measurement of R&D performance in the higher education sector is affected by a significant estimation of figures carried out by national authorities, although evaluation methods are periodically revised. Moreover, peculiar national characteristics may substantially
OECD Science, Technology and Industry Scoreboard, OECD, 2001.
205
INDICATORS TIME
COVERAGE
EXPLANATION MEASUREMENT
ISSUES
SOURCE
some 2% of GDP. Government R&D performance remains under 0.3% in each of the three countries, highlighting a decline over the last decade mainly in the UK, France, Italy and the USA, where it was mainly due to a decrease in defence spending and transfer of public agencies to the private sector
influence R&D performance by government and higher education. Some data may be also over- or underestimated as well as drawn from series which have breaks from previous year for which data are available.
24 FINANCING
OF R&D
1981-1989- 1991-1995- 1997/1999
Measured as a % of GDP and as a share in national total sources of financing, i.e. business enterprises, government, higher education, private non-profit plus foreign funds (from abroad). About 72% of R&D in Japan and 67% in the USA is funded by the business sector, whereas only 55% in the EU. During the 1990s the relative share of funding from the business sector kept steady in Japan, while it highly increased in the USA and slightly in the EU. In most countries the government funding decreased over the 1990s, although it is still the major source of R&D funding. The business sector, however, both plays a major role in financing R&D and perform most R&D. Its contribution to the total R&D performance has increased after 1995, thus representing more than 2/3 of total R&D expenditure.
Flows of funds are measured using performance-based reporting of the funds received by one unit, organisation or sector from another unit for the performance of intramural R&D. Only direct transfers (from a unit/organisation/sector to another) of resources used to carry out R&D are measured.
OECD Science, Technology and Industry Scoreboard, OECD, 2001.
25
BUSINESS
EXPENDITURE
ON R&D
(BERD)
1981-1989- 1991-1995 1997/1999
Measured as millions of 1995 PPP US$. This indicator covers R6D activities carried out in the business sector by performing firms and institutes. Industrial R&D is most closely linked to the creation of new products and production techniques as well as to a country’s innovation efforts. Moreover, the business enterprise sector includes all those firms whose primary activity is the production of goods and services to be marketed, as well as private and non-profit institutes. Business R&D expenditure increased at a fast pace in the USA over the 1990s
Changes in R&D in time must be evaluated by taking into account series breaks or survey methods improvement (extension of the survey coverage), but also the privatisation of publicly owned firms.
OECD Science, Technology and Industry Scoreboard, OECD, 2001.
206
INDICATORS TIME
COVERAGE
EXPLANATION MEASUREMENT
ISSUES
SOURCE
(3.7% annually), whilst the EU growth was much less (2.2%).
26 BUSINESS R&D
INTENSITY
1981-1989- 1991-1993- 1995/1999
Measured as a % of domestic product of industry. This indicator can be also defined as the business R&D intensity, namely the business enterprise sector R&D expenditure as a % of domestic product of industry. Relative figure for Japan and the USA (around 2.4% each) overcome those to the EU (only 1.6%), of which Finland and Sweden are significantly above the average to the former. Indeed, this indicator performed well over the 1990s in the Nordic countries and Ireland, but declined in Germany, the UK and Italy.
OECD Science, Technology and Industry Scoreboard, OECD, 2001.
27
R&D IN
SELECTED
SERVICES
AND
MANUFACTUR
ING
INDUSTRIES
1) 1991-1999 2) different time periods
Measured as: 1) the share of services in business R&D (total services and manufacturing industries); 2) the average annual growth rate in R&D in selected services and manufacturing industries (namely services, communications, computers and related activities and manufacturing). Most countries are moving their economic structure towards services, which now have an equal share in R&D and GDP. Norway, for instance, has carried 48% of total business R&D in the service sector, as well as the USA (31%) and Denmark (37%) whereas Japan, Germany and Italy have the lowest share of services R&D (less than 10%). On the other hand, manufacturing industries performed a lower average annual growth rate for R&D over the 1990s. A remarkable gap was highlighted in the Netherlands, where between 1991 and 1998 R&D in services increased by 18.5% a year whereas R&D in manufacturing only by 1.2%
The measurement of expenditure in R&D in this sector underwent a certain improvement by national statistics authorities, although some peculiar issues are still to be worked out. Most of all, the practises concerning the allocation of activities formerly included in manufacturing but reclassified in services need to be standardised.
OECD Science, Technology and Industry Scoreboard, OECD, 2001.
28 R&D IN HIGH-1991/1999 Measured as a % share in total manufacturing.
Manufacturing industries are grouped according to See previous indicator OECD Science, Technology and
Industry Scoreboard, OECD,
207
INDICATORS TIME
COVERAGE
EXPLANATION MEASUREMENT
ISSUES
SOURCE
MEDIUM-LOW
TECHNOLOGY
INDUSTRIES
their R&D intensity (or level of technology) in 4 categories: 1) high; 2) medium-high; 3) medium-low; 4) low. The category 1) accounts for more than 50% of total manufacturing R&D in most countries. The share of R&D in high-technology industries varies between the USA, the EU and Japan. In the USA they accounted for 60% of total manufacturing R&D in 1999, whereas the EU for 46% and Japan for 43%. In Ireland and Finland most manufacturing R&D expenditure was allotted to high-technology industries, while in Germany it was devoted to medium-high-technology industries (60% or more).
2001.
29
R&D IN
SELECTED ICT-
RELATED
SECTORS
1991-1995- 1999 Measured as a % of GDP and as a % of business enterprise sector R&D expenditure for both ICT-related R&D expenditure in manufacturing industries and ICT-related R&D expenditure in services industries. In countries with data for both categories of industries, ICT-related R&D expenditure generally expanded more rapidly in the services industries over the 1990s. The ratio of R&D expenditure by ICT industries to GDP or to the total business enterprise can indicate the R&D specialisation of the former. Small countries such as Finland and Sweden are much more specialised than large ones in both ICT manufacturing and services. Moreover, only Finland allocated more than 1% of GDP to ICT-related manufacturing R&D expenditure in 1998. On the other side, United States and Japan’s ICT-related intensities are well above those of large EU countries, except for the UK which ICT-related R&D expenditure increased by 1% a year in manufacturing industries and by £% in the services ones. In manufacturing, ICT-related R&D expenditure, Germany performed a decrease by 1%,
ICT industries selected for the calculation of this indicator include for the manufacturing industries: office, accounting and computing machinery; manufacture of radio, TV and communication equipment apparatus; manufacture of medical, precision and optical instruments, watches and clocks; for the services industries: post and communications; computer and related activities.
OECD Science, Technology and Industry Scoreboard, OECD, 2001.
208
INDICATORS TIME
COVERAGE
EXPLANATION MEASUREMENT
ISSUES
SOURCE
France by 2% and Italy by 0.5%
30
GROSS
DOMESTIC
PRODUCT
(GDP)
1980, 1985, 1990, 1995/99
The GDP (Gross Domestic Product) measures the total output of goods and services for final use occurring within the domestic territory of a given country.
The indicator does not take into account allocation to domestic and foreign claims.
OECD Science, Technology and Industry Scoreboard, OECD, 2001.
31
GDP PER
CAPITA &
GDP PER
HOUR
WORKED
(time series)
1950-1960-1973-1987-1992-1999
Measured as: 1) GDP per capita (USA=100) ; 2) GDP per hour worked. Over the 1950s and 1960s, income levels of countries except the United Kingdom were catching up with those of the United States. Japan had the highest rate of catch-up over the 1950-99 period, with GDP per capita growing more rapidly, by 2.7% than in the United States. Most of Western Europe had much lower rates of catch-up, typically below 1% a year. The UK was already at relatively high income levels in 1950 and have since done little catching up with the United States. Changes in levels of GDP per hour worked show a slightly different pattern. Several European countries now stand even with the United States in terms of average labour productivity and some have even surpassed it.
OECD Science, Technology and Industry Scoreboard, OECD, 2001.
32
BREAKDOWN
OF GDP PER
CAPITA:
§ GDP/H: Hourly productivity;
§ H/L: Average working time;
1999 Measured as: 1) GDP per capita (USA=100) and its effect (%) of working age population (15-64 years) to total population, labour force to working-age population, unemployment, working hours; 2) GDP per hour worked; 3) GDP per person employed. In 1999, the United States had the highest level of GDP per capita, followed by Switzerland and Norway. Most G7 countries had income levels ranging between 65% and 80% of that of the United States. Next come a number of lower-income economies, including Greece, Portugal and Spain,
GDP is converted to common currency by 1999 OECD purchasing power parities (PPP). Comparisons of income and productivity levels (see also next indicator) need to address several measurement problems. First, they require comparable data on output. The measurement and definition of
OECD Science, Technology and Industry Scoreboard, OECD, 2001.
209
INDICATORS TIME
COVERAGE
EXPLANATION MEASUREMENT
ISSUES
SOURCE
§ L/LF: Employment rate;
§ LF/WAP: Labour force participation rate;
§ WAP/POP: Percentage of working age population:
some of which have recently experienced high growth. Differences in GDP per capita among countries can be attributed to differences in labour productivity, or GDP per hour worked, and differences in labour utilization, or the average number of hours worked by the population. Differences in GDP per capita are clearly not the same as differences in GDP per hour worked. Demographic factors – differences in the ratio of the working-age population to the total population – have only a small impact on cross-country differences in GDP per capita.
GDP are treated systematically across countries in the 1993 System of National Accounts (SNA). Most countries have now implemented this system, therefore output in these countries is likely to be understated relative to other OECD countries. The second issue is the measurement of labour input. Some countries integrate the measurement of labour input in the national accounts. In most countries, however, employment data are derived from labour force surveys that are not necessarily consistent with the national accounts. Third, international comparisons require price ratios to convert output expressed in a national currency into a common unit. Exchange rates are of limited use for this purpose because they are volatile and reflect many influences, including capital movements and trade flows. The alternative is to use purchasing power parities (PPPs), which measure the relative prices of the same basket of consumption goods in different countries.
210
INDICATORS TIME
COVERAGE
EXPLANATION MEASUREMENT
ISSUES
SOURCE
33
BREAKDOWN
OF VALUE
ADDED BY 9
AGGREGATE
INDUSTRY
AND SERVICE
SECTORS
1998 Measured at current prices and broken down into 9 aggregate sectors (%).Sectoral value-added shares provide a good perspective on the structure of economies. Some are heavily oriented towards services (e.g. the United States), while others have a significant manufacturing sector (e.g. Ireland). Countries that have industrialized very rapidly in recent years or that are still at relatively early stages of economic development typically have the largest manufacturing sectors (e.g. Ireland,). Large services sectors in countries such as Denmark, France, and the United States are primarily due to a high proportion of value added in finance, insurance, real estate and business services, and a large community, social and personal services sector. Economic development in most economies has long been characterized by a gradual process of structural change. In recent years, many of them have also experienced a decline in the share of manufacturing in overall economic activity. This is partly due to saturated demand for many manufactured goods, but also to the differential in productivity growth between the manufacturing and the services sectors.
Measurements at basic prices except for the USA and Japan measured at factor costs. Since manufacturing typically experiences more rapid productivity growth, relative prices decline and the sector’s share in value added may drop over time. In contrast, some services sectors may have little scope for productivity growth and will therefore experience an increase in relative prices. This typically implies that their share in value added will increase
OECD Science, Technology and Industry Scoreboard, OECD, 2001.
34
VALUE
ADDED OF
HIGH-
MEDIUM-LOW
TECHNOLOGY
INDUSTRIES
AND
KNOWLEDGE
1990/1999 Measured as: 1) the real value added; 2) implicit deflators in high- and medium-high-technology manufactures and knowledge-intensive “market” services. All industries generate and/or exploit new technology and knowledge to some extent, but some are more technology- and/or knowledge-intensive than others. In Ireland, high- and medium-high-technology manufacturing has been a driving force behind the recent economic expansion and now accounts for more than 16% of total value added,
Base year is 1995=100 OECD Science, Technology and Industry Scoreboard, OECD, 2001.
211
INDICATORS TIME
COVERAGE
EXPLANATION MEASUREMENT
ISSUES
SOURCE
INTENSIVE
SERVICES
significantly higher than the OECD average. In most other countries, business services account for largest proportion of knowledge-intensive services. In the United States, growth in real value added of high- and medium-high-technology manufacturing outpaced that of services in the 1990s. In Europe and Japan, services have generally grown more rapidly.
35
IMPORT
PENETRATION
OF HIGH-
MEDIUM-LOW
TECHNOLOGY
INDUSTRY
1990-1998 Import as a % of domestic demand (estimated as production minus export plus imports) by: by 1) high technology industries; 2) medium-high technology industries; 3) medium-low-technology industries; 4) low-technology industries. The import penetration rate shows to what degree domestic demand is satisfied by imports. For some industries, import penetration rates are high, like in the USA for the textiles and motor vehicles, computers in the EU and wood, food and drink and tobacco in Japan. Furthermore, strongly export-oriented industries can also have a high import penetration rate, like computers and electrical machinery in the USA and scientific instruments in Japan and the EU.
Values greater than 100 can occur when exports exceed production because of the inclusion of re-exports-products that are imported and then re-exported without any further transformation
OECD Science, Technology and Industry Scoreboard, OECD, 2001.
36
EXPORT
RATIO OF
HIGH-
MEDIUM-LOW
TECHNOLOGY
INDUSTRY
1990-1998 Export as % a percentage of production by 1) high technology industries; 2) medium-high technology industries; 3) medium-low-technology industries; 4) low-technology industries. The export ratio indicates the share of output which is exported by a given country. The export ratios and the import penetration rates (see next indicator) for the USA, the EU and Japan show similar patterns of internationalisation across manufacturing industries. For instance, the exposure of computers, aircraft, radio and TV equipment to international trade is high, whereas that of paper, printing and tobacco, food and drink is limited. Moreover, a strong
Values greater than 100 can occur when exports exceed production because of the inclusion of re-exports-products that are imported and then re-exported without any further transformation
OECD Science, Technology and Industry Scoreboard, OECD, 2001.
212
INDICATORS TIME
COVERAGE
EXPLANATION MEASUREMENT
ISSUES
SOURCE
difference between the two above-stated indicators could indicate patterns of national specialisation (the UK has a strong export orientation in aircraft, Japan and the EU in shipbuilding, motor vehicles, machinery and equipment)
37
CONTRIBUTIO
N TO TRADE
BALANCE OF
HIGH-
MEDIUM-LOW
TECHNOLOGY
INDUSTRIES
1990/1999 Measured as % a percentage of contribution to the manufacturing trade balance by: 1) high technology industries; 2) medium-high technology industries; 3) medium-low-technology industries; 4) low-technology industries. The "contribution to the trade balance"* makes it possible to identify an economy’s structural strengths and weaknesses via the composition of international trade flows. It takes into account not only exports, but also imports, and tries to eliminate business cycle variations by comparing an industry’s trade balance with the overall trade balance. It can be interpreted as an indicator of "revealed comparative advantage", as it indicates whether an industry performs relatively better or worse than the manufacturing total, no matter whether the manufacturing total itself is in deficit or surplus. Few countries are specialized in high- and medium-high-technology industries. In 1999, the structural surplus in these industries represented more than 15% of total manufacturing trade for Japan, about 5% for Germany and the United States. For most countries, these specialization patterns have changed only little over the past decade. There are exceptions, however. Japan and Ireland’s comparative advantage in high-technology industries declined considerably over the 1990s,
Measurement was carried out by taking into account the observed trade balance of industry minus theoretical trade balance, expressed in hundreds of manufacturing trade
OECD Science, Technology and Industry Scoreboard, OECD, 2001.
38 GROSS FIXED
CAPITAL
1998 Measured as a % of GDP. It covers investment in structures, machinery and equipment, thus
EU Average annual growth rate excludes Belgium., whilst
OECD Science, Technology and Industry Scoreboard, OECD, 2001.
213
INDICATORS TIME
COVERAGE
EXPLANATION MEASUREMENT
ISSUES
SOURCE
FORMATION highlighting diffusion of new technology especially to manufacturing industries. It represents around 21% of OECD-wide GDP, although for most countries this ratio decreased during the 1990s. In the USA gross fixed capital formation grew more ( by 6.2% from 1991 to 1998) than investment in knowledge: this could be due to the inclusion of some component of investment knowledge (e.g., software expenditure) in the former.
average annual growth rate of OECD countries 1991-1998 is expressed in 1995 US$ using purchasing power parities (PPP).
39
FOREIGN
DIRECT
INVESTMENT
FLOWS
1990/1998 Measured in billion of US$. Foreign investments takes the form of direct investments, portfolio investments, reserve assets or other investments. A foreign investment is classified as a direct investment if the foreign investor holds at least 10% of the ordinary shares or voting rights in an enterprise. Any other investment amounting to less than 10% is a portfolio investment. The magnitude of FDI flows varies among countries and regions and over time. Several factors could have an effect on the direction and magnitude of such flows: infrastructure quality, level of taxation, technology, labour skills and the macroeconomic stability of the recipient country. FDI as a percentage of GDP is high for Belgium-Luxembourg, Sweden, the Netherlands, Switzerland and the United Kingdom. It is still small in Turkey, Korea, Japan, and Italy. In some countries, outward investment greatly exceeds inward investment. Like in Germany, Japan and the United Kingdom. The Netherlands and Sweden also rank high as net outward investors. These countries differ from the others in that they are home to several multinational corporations that invest extensively abroad
By definition, direct investment flows do not include investment via the host country’s capital market or via other financial sources that do not pass through the investor country, although in some cases this may represent over half of the total investment. For this reason, data on the activity of foreign affiliates provide more complete information on the importance of foreign investment in each country
OECD Science, Technology and Industry Scoreboard, OECD, 2001.
40 TECHNOLOGY
BALANCE OF
1990-1999 Measured as the amounts of receipts and payments (and the consequent balance) in both millions of US$
Although the balance reflects a country’s ability to sell its
OECD Science, Technology and Industry Scoreboard, OECD,
214
INDICATORS TIME
COVERAGE
EXPLANATION MEASUREMENT
ISSUES
SOURCE
PAYMENTS and as a % of GDP. The technology balance of payments measures international technology transfers: licenses, patents, know-how, research and technical assistance. Technology receipts and payments constitute the main form of disembodied technology diffusion. Trade in technology comprises four main categories: a) transfer of techniques (through patents and licenses, disclosure of know-how); b) transfer (sale, licensing, franchising) of designs, trademarks and patterns; c) services with a technical content, including technical and engineering studies, as well as technical assistance; d) industrial R&D. The main technology exporters as a percentage of GDP are Switzerland, Belgium, Denmark, the United States, the United Kingdom and Japan. Ireland and Portugal are among those that imported the most technology in 1999.
technology abroad and its use of foreign technologies, a deficit position does not necessarily indicate low competitiveness. In some cases, it results from increased imports of foreign technology; in others, it is due to declining receipts. Furthermore, if the balance is in surplus, this could be the result of a high degree of technological autonomy, a low level of technology imports or a lack of capacity to assimilate foreign technologies. Thus, trade in services may be underestimated when a significant portion does not give rise to any financial payments or when payments are not in the form of technology payments.
2001.
41
NUMBER OF
PATENTS
(Triadic Patent
Families)
1989-1993- 1995. Measured as: 1) the total of triadic patents (namely those issued by the European Patent Office (EPO), the US Patent and Trademark Office (USTPO) and the Japanese Patent Office (JPO); 2) a share in total triadic patent families and 3) the number of patents in triadic patent families per million population. Patent-based indicators provide a measure of the output of a country’s R&D, notably its inventions. Patent indicators are generally based on patent applications and/or patent granted by national or regional patent offices. In 1995 the USA accounted for about 35% of all patents filed in the three patent
Methodologies used to measure patents number filed in a country can affect final results: patents filed at one of the three patent office, for instance, possess either weakness in international comparability (home advantage for patent applications) or high heterogeneity of patent values within a single office. This hurdle can be overcome by building an indicator based on “patent
OECD Science, Technology and Industry Scoreboard, OECD, 2001.
215
INDICATORS TIME
COVERAGE
EXPLANATION MEASUREMENT
ISSUES
SOURCE
offices taken into account. The EU came second with 32% and Japan edged up to 27%. When population size is taken into account, Switzerland is the country that filed the most of patents (100 patent families per million population) in 1995. more than, for instance, Sweden (74) and Japan (69). Also Northern European countries filed a substantial number of patents in 1995, whereas Greece has the lowest ratio (close to nought) in the EU. On the other hand, Japan has the highest patent intensity (i.e. patent application as a share of business R&D expenditure), well above the EU and the USA.
families”, i.e. sets of patents taken in various countries to protect a single invention, when a first application in a country is then extended to other offices. Patent families thus improve international comparability of patent-based indicators, since they concern only patents taken in the same set of countries. To create a “family”, a patent must be filed in several countries, thereby patents that are members of families will be of higher value than those filed only in one country.
216
INDICATORS TIME
COVERAGE
EXPLANATION MEASUREMENT
ISSUES
SOURCE
III
Human & Social Capital Indicators
42 POPULATION BY AGE AND GENDER
1975-1985- 1995-2005 (forecast)
Distribution of population in three main age groups: Youth: 0-14 years Active population: 15-65 years Elderly: over 65 years
EUROSTAT Working Papers. Population and Social Conditions. National and Regional Population Trends in the European Union, EUROSTAT, 1999.
43 URBAN POPULATION
1975-1998-2015 Measured as a % of total population for each country. Forecasts are given for year 2015
Human Development Indicators, United Nations, 2000
44
INCOME DISPARITY (ratio of richest 20% to poorest 20%)
1987-1998 Measured as the ration “richest 20% to poorest 20%” in the time period from 1987 to 1998.
Human Development Indicators, United Nations, 2000
45
POPULATION AGED 25-64 BY LEVEL OF EDUCATIONAL ATTAINMENT
1999 Measured as a % population by level of educational degree (below upper secondary school, upper secondary school, non-university tertiary education, university level education). The share in the USA of population aged 25-64 who has completed upper secondary schooling is more than 20% higher than in Europe. This value exceeds 80% in the USA, Norway, the UK, Germany and Japan, whereas it is below 50% in Portugal (21%), Spain (35%) and Italy (44%). On the other hand, population aged 25-64 having university-level education has the highest value in the USA again, together with Norway and the Netherlands (more than 20%). In Italy, Austria and Denmark this value is below 13%.
Measures of educational attainment are the most commonly used proxies for human capital, despite they sometimes do not take into account quality of schooling and formal or on-the-job training. Human capital is also heterogeneous: the level of individuals’ skills, knowledge and competencies can be taken to represent the “stock” of human capital at any one time, although these various attributes cannot b-e easily quantified.
OECD Science, Technology and Industry Scoreboard, OECD, 2001.
46 LABOUR 1999 Measured by level of educational attainment and The labour force participation Education at a Glance , OECD Report 2001.
217
INDICATORS TIME
COVERAGE
EXPLANATION MEASUREMENT
ISSUES
SOURCE
FORCE PARTICIPATION RATE BY EDUCATIONAL LEVEL AND GENDER
gender for populations 25 to 64 and 55 to 64 years of age. Although the gender gap in labour force participation remains among those with the highest educational attainment, the gap is much narrower than among those with lower qualifications. On average across OECD countries, with each additional level attained, the difference between the participation of men and women decreases by 10 percentage points: from about 30 percentage points at below upper secondary level, to 20 percentage points at upper secondary and 10 at tertiary level. Much of the overall gap between the labour force participation rates of men with differing educational attainment is explained by larger differences in the older populations, particularly among men between the ages of 55 and 64. More than 70 per cent of 55 to 64-year-olds with a tertiary-level qualification are active in the labour force in 20 out of 29 countries. Only Greece, Korea, Mexico and Turkey have participation rates as high among those who have not completed upper secondary education. By contrast, the education gap in female labour force participation is relatively wide in all age groups.
rate for a particular age group is equal to the percentage of individuals in the population of the same age group who are either employed or unemployed, these terms being defined according to the guidelines of the International Labour Office (ILO).
47
FEMALE ECONOMIC ACTIVITY RATE
1998 Measured as: 1) the % rate of female workers aged 15 and above; 2)as an index, whose base year is 1985 = 100; 3) as a % of male rate.
Human Development Indicators, United Nations, 2000
48
UNEMPLOYMENT RATE BY EDUCATIONAL LEVEL AND GENDER
1999 Measured by level of educational attainment and gender for population 25 to 64 and 30 to 44 years of age. The wide variation between countries in unemployment rates observed among those with low educational attainment is attributable to a number of factors. In some countries (especially Finland and Spain), the high unemployment rates of the poorly educated reflect
The unemployment rate is the number of unemployed persons divided by the number of labour force participants (expressed as a percentage).
Education at a Glance , OECD Report 2001
218
INDICATORS TIME
COVERAGE
EXPLANATION MEASUREMENT
ISSUES
SOURCE
generally difficult labour market conditions, which affect these individuals in particular. Unemployment rates among those without an upper secondary qualification are also relatively high in some countries where labour markets are less regulated (Canada, the United Kingdom and the United States), although not in others (Australia and New Zealand). On the other hand, in countries where agriculture is still an important sector of employment (Greece, Portugal and Turkey), unemployment rates of persons without upper secondary education tend to be low. Finally, where overall labour market conditions are particularly favourable (Austria, Iceland, Luxembourg and Norway), jobs appear to be available for workers with low as well as high educational attainment
49 LONG-TERM UNEMPLOYMENT BY GENDER
1998 Measured as a % of total unemployment, by gender (male and female)
Data refer to unemployment lasting 12 months or longer
Human Development Indicators, United Nations, 2000
50 PART-TIME EMPLOYMENT BY GENDER
1998 Measured as a % of total employment, by gender (male and female)
Human Development Indicators, United Nations, 2000
51
RELATIVE EARNINGS BY EDUCATIONAL LEVEL AND GENDER
Measured by level of educational attainment and gender for population 25 to 64. Upper secondary education is = 100. Relative earnings from employment are defined as the mean earnings (income from work before taxes) of persons at a given level of educational attainment divided by the mean earnings of persons with upper secondary education. This ratio is then multiplied by 100. The estimates are restricted to individuals with income from employment during the reference period. Since lower educational attainment is associated with fewer hours of work (in particular with part-time work)
Earnings data are annual for most countries; for France ,Spain and Switzerland they are monthly. In the case of France, data cover the earnings of employees only. The Spanish data exclude people who work fewer than fifteen hours a week.
Education at a Glance , OECD Report 2001.
219
INDICATORS TIME
COVERAGE
EXPLANATION MEASUREMENT
ISSUES
SOURCE
and with less stable employment (more likelihood of temporary employment or more susceptibility to unemployment over the course of a year), the relative earnings figures shown for higher educational attainment in the tables and charts will be greater than what would be evident from an examination of relative rates of pay. The observed differences in relative earnings of men and women within a country can likewise be affected by some of these factors.
52
FULL-TIME AND PART TIME EMPLOYMENT OF YOUTH POPULATION BY EDUCATIONAL LEVEL AND GENDER
1999 Measured by gender, age group and education status.Entry to the job market often involves a phase of unemployment. The proportion of young men in this age group who are neither in education nor in work is around 13 per cent, over 5 percentage points higher than that of 15 to 19-year-olds. In countries where young people spend less time in education and enter the labour market earlier, the figure rises very little. Unemployment among first-time labour-market entrants makes its full effect felt in Finland, France and Italy, where the proportion of young men neither in education nor in work is much higher among 20 to 24-year-olds than among 15 to 19-year-olds. Among young women aged 20 to 24 years, the increase is even more spectacular since the average rate for all countries is 22 per cent, which is more than twice that of the younger group. In addition to the general phenomenon of unemployment among first-time labour-market entrants, there is still a significant withdrawal of women from the labour market in some countries.
The statistics are calculated from labour force survey data on age-specific proportions of young people in each of the specified categories. The definitions of the various labour force statuses of those not in education (and not enrolled in work-study programs) are based on the ILO guidelines. The data for this indicator were calculated from the special data collection on transition from education to work
Education at a Glance , OECD Report 2001.
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ISSUES
SOURCE
53
PARTICIPATION TO TRAINING ACTIVITIES BY EMPLOYMENT STATUS AND GENDER
Different years for each country
Measured as the mean number of hours per adult for the population 25 to 64 years of age, by employment status and gender. Participation rates among the unemployed population, on average, are 50 per cent lower than corresponding rates among the employed population. In particular, very low participation rates were reported for the unemployed in job-related continuing education and training in Poland and Finland By contrast, in Denmark, the Netherlands and Switzerland, the difference in participation rates between the employed and unemployed is not as pronounced. While participation rates in continuing education and training are comparatively low among the unemployed, the mean number of hours of training of unemployed participants in job-related continuing education and training programmes is up to five times higher than that of employed participants. This is largely the result of active labour market policies that provide full-time programmes and training activities for the unemployed.
The mean number of hours per adult is equal to the participation rate divided by 100, multiplied by the mean number of hours per participant. Comparable data on continuing education and training were compiled from national surveys in seven countries. With the exception of Sweden, these national surveys have the same reference period of 12 months. In Sweden, a reference period of six months is used. The sample sizes in these surveys ranged from 5 000 to 40 000 respondents. The data collection was based on face-to-face interviews or telephone interviews.
Education at a Glance , OECD Report 2001.
54
RESEARCHERS PER 10,000 LABOUR FORCE BY SECTOR OF EMPLOYMENT
1981-1989-1991-1995- 1997- 1999
Measured as a the number of employees per 10,000 labour force by sector of employment (business enterprise, government, higher education). Researchers are defined as professionals engaged in the conception and creation of new knowledge, products, processes, methods and systems and are directly involved in the management of projects. Researchers can also be university graduates. The business enterprise sector covers scientists and engineers carrying out R&D in firms and business enterprise sector institutes. While the government and the higher education sectors also carry out R&D, industrial R&D is much more linked to the creation of new products and production techniques, as well as to a country’s innovation efforts. Amongst all countries, Japan has the highest number of researchers
For countries compiling data by qualification only, data in university graduates are used as a proxy. The number of researchers is expressed in full-time equivalent (FTE) and includes staff engaged in R&D during the course of one year.
OECD Science, Technology and Industry Scoreboard, OECD, 2001.
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relative to the labour force, followed by the USA. Moreover, in Japan and the EU the share of researchers is similar to their share in R&D expenditure, whereas the USA’s share of researchers is 7% below its share of R&D expenditure. The bulk of R&D is funded and carried out by the business enterprise sector. In the USA four out of five researchers work in the business sector, whereas only one out of two in the EU. Moreover, in the USA, Japan and Sweden, business researchers exceed 50 per 10,000 of the economy-wide labour force, whereas in other EU large countries this figure slips down to 30.
55 PUBLIC EXPENDITURE ON EDUCATION
1998 Measured as direct public expenditure on educational institutions plus public subsidies to the private sector as a percentage of GDP and as a percentage of total public expenditure, by level of education and year. On average, OECD countries devote 12.9 per cent of total government expenditure to education, the values for individual countries ranging between 7 and 22 per cent. Korea, Iceland, Mexico and Norway allocate between 16 and 22 per cent of total public spending to education. Conversely, in the Czech Republic, Germany and Greece, the proportion of public expenditure spent on education is less than 10 per cent.
Total public expenditure, also referred to as total government spending, corresponds to the non-repayable current and capital expenditure of all levels of government, central, regional and local.
Education at a Glance , OECD Report 2001.
56
RATIO OF STUDENTS TO TEACHING STAFF
1999 Measured for public and private institutions. The ratio of students to teaching staff in primary and secondary education varies widely between OECD countries. In primary education, the ratio of students to teaching staff, expressed in full-time equivalents, ranges from 32 students per teacher in Korea to 11 in Denmark and Hungary. The mean OECD ratio of students to teaching staff in secondary education is 14.6, which is close to the ratios in the Czech Republic (14.7), Germany (15.2), Ireland (14.6), Japan (15.4), Sweden (14.5), the United Kingdom (14.7) and the United States (15.6). As the
“Teaching staff” refers to professional personnel directly involved in teaching students. It does not include non-professional personnel who support teachers in providing instruction to students, such as teachers’ aides and other paraprofessional personnel.
Education at a Glance , OECD Report 2001.
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difference in the mean ratio of students to teaching staff between primary and secondary education indicates, there are fewer students per teacher as the level of education rises. With the exception of Canada, Denmark, Mexico, the Netherlands and Sweden, the ratio of students to teaching staff decreases in every OECD country between the primary and the secondary level.
57
TRAINING OUTSIDE FORMAL EDUCATION
Measured as expected hours of training outside formal education, net participation rates, and mean number of hours of participation per year, by age group. More than one third of all people aged 25 to 44 participate in some continuing education and training (not leading to a formal educational qualification) in 10 out of 18 countries for which comparable data are available. The number of hours of training in which people aged 20 can expect to participate over their lifetime is substantial. It ranges from around 1 000 hours of continuing education and training in the Flemish Community of Belgium, Italy and Poland, to over 3 000 hours in Denmark and Finland.
Education at a Glance , OECD Report 2001.
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SCIENCE GRADUATES IN THE YOUTH LABOUR FORCE
1999 Measured as Number of science graduates per 100 000 persons in the labour force 25 to 34 years of age, by gender. Science fields include life sciences; physical sciences, mathematics and statistics; computing; engineering and engineering trades, manufacturing and processing, architecture and building. Comparing the number of science graduates with the number of 25 to 34-year-olds in the labour force provides another way of gauging recent output of high-level skills by different education systems. The number of science graduates per 100 000 people in the labour force ranges from below 700 in the Czech Republic, Mexico and the Netherlands, to above 1 600 in Finland, France, Ireland, Japan and the
Labour force data used in Table C4.4 are taken from the OECD Labour Force database, compiled from National Labour Force Surveys and European Labour Force Surveys.
Education at a Glance , OECD Report 2001.
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United Kingdom.
59 GRADUATES BY FIELD OF STUDY
Measured as the distribution of tertiary graduates in public and private institutions, by field of study and level of education. In 19 of the 26 countries providing data, the largest concentration of tertiary-type A qualifications awarded is in the field of social sciences, law and business (Table C4.3). The percentage of tertiary-type A qualifications awarded in the social sciences, law and business ranges from 25 per cent or below in Korea, Norway and Sweden, to over 46 per cent in Mexico and Poland. Typically, one out of every three or four students graduates from the fields of humanities, arts or education. There is less variation between countries in graduation from science-related fields than in overall graduation rates. The percentage of students in science-related fields (engineering, manufacturing and construction, life sciences, physical sciences and agriculture, mathematics and computing, but not including health and welfare) ranges from less than 19 per cent in Norway, Iceland and the United States, to over 33 per cent in Finland, Germany and Korea.
Education at a Glance , OECD Report 2001.
Notes on the TIME COVERAGE: 1997-1999: the slash separates a year from another.; 1997/1999: the backslash indicates a time-series
224
Annex 3: IST research projects related with SEAMATE
PROJECT
SHORT DESCRIPTION RELATION
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SEAMATE
WPs
CONTACT DETAILS
STAR Socio-economics Trends Assessment for the Digital Evolution
The main goal of this project is to examine the socio-economic impacts of new technologies and services on the nature of work and business enterprise in the next decade, with a specific focus on the identification of new opportunities for economic and employment growth and their drivers and barriers. The project will: 1) analyse emerging patterns in the development of the digital economy in Europe and the application of the new technologies to advanced ("second-generation") services; 2) assess their contribution to the competitiveness of European industry and service providers; 3) study the conditions leading to sustainable social and economic growth patterns.
EMERGENCE Estimation and Mapping of Employment Relocation in a Global Economy in the New Communications Environment
The EMERGENCE project aims to provide reliable information both qualitative and quantitative, on delocalised telemediated work. An interdisciplinary team (plus associates in North America and Australasia) will carry out a statistical overview, develop analytical models, conduct an international survey and carry out a comparative case study to map, quantify and forecast the new international division of labour in information processing. It will make recommendations to official statistical bodies. It will dissemination information interactively, for use as a resource for research, benchmarking against global comparators, regional development, employment creation, equal opportunities and other policies.
Surveys confirm that e-work is taking place on a significant scale in Europe (e-Work Report, 2001), starting to induce a direct impact on employment practices and an indirect effect on the economy in a number of regions. Meanwhile, people observe discrepancies about penetration of e-work between companies according to their size. The results are significantly lower among SME (ECATT Report, 2000). Another criterion is the political support in the countries. With the strong will to contribute to a better use of e-work at the levels of work people and policies frames, the E-GAP Projects wants to identify, understand and highlight the hidden inhibitors to e-works and give arguments and tools to bring flexibility into the Community legislation taking into account regional contexts. So, the aim is to contribute to better conditions conducive to sustainable development (Göteborg, 2001)
WP1 Contact Person: Name: DE BEER, Anne Tel: +33-2-54808903 Fax: +33-2-54808924 Email: [email protected]
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NEWTIME New E-Work Techniques in Micro-Enterprises
NEWTIME's aim is to provide a factual basis for the specific modalities chosen for migration of micro-business IST networks from first generation low bandwidth, telework-enabled, networks towards networks with broadband IST at their core. Objectives include: - identifying the tools and techniques most valuable in new generation networks; -identifying the individual technical and social skills needs emerging from first encounters between micro-businesses and high bandwidth access (ISDN, ADSL, SDSL, UMTS); -reviewing the place of facilitation/mentoring; -and linking to economic development and SME facilitation activities.
MUTEIS Macro-Economic and Urban Trends in Europe's Information Society
The overall objective of the MUTEIS project is to explain and understand functional and spatial diversity in Europe's digital economy both from a macro and local/urban perspective. We want to improve knowledge of the macro economic impact of the digital economy, but also on the origins and causes of local diversities in the development of the digital economy, as we believe that the urban stories help to understand the macro-overall pattern. The analysis should improve the design and implementation of policy action on European, national and urban levels that efficiently and effectively help Europe's transition into the digital economy in a sustainable way.
WP1 Project URL: http://muteis.infonomics.nl Contact Person: Name: VAN ROSSUM, Martin (CEO) Tel: +31-10-2850940 Fax: +31-10-2850968 Email: [email protected]
TERRA2000
The overarching objective is to seize the moment before the opportunities offered by the New Economy slip away and the issues are resolved in ways that undercut European values, institutions and interests. The target audiences are policy makers, economic and social actors in the unfolding of the New Economy, "final users" and research communities. The primary objective is to produce a rich library of scenarios that combine informed and consistent assumptions about the New Economy; a coherent set of key issues relevant to European policy; assumptions about key actors; closely integrated state-of-the-art projections; and an assessment of the implications. The second objective is creation of integrated tools for supporting scenario and policy development and analysis: specific models for networked economy, social fabric and resource utilization; sensitivity analysis, scenario screening and development and gaming tools; and a database of inputs, New Economy indicators and system outputs. The third ojective is an active societal discourse to engage the wider world in project activities and support preservation and enhancement of European values, institutions and interests in the context of the globalising
NESKEY NEw partnerships for Sustainable development in the Knowledge EconomY
NESKEY etablishes the agenda for research on Sustainable Development in the Knowledge Economy. (1) Measurement and reporting project addresses disclosure of information on corporate environmental, social, and economic performance for stakeholders’ decision-making. It develops global guidelines for companies in the ICT sector. (2) Intangible assets project defines how to measure intangibles at micro and macro levels. It develops reporting standards facilitating evaluation the soft assets of a company, including the risk and opportunity elements. (3) Sustainable cities project develops socio-economic and environmental indicators and creates communities between companies, projects, individuals, NGOs, experts and cities using ICT’S contribution to Intelligent Houses as a test case. The final report publing the results together facilitates the development of EU models and scenarios for sustainable development and the knowledge economy.
DEESD Digital Europe: E-commerce and Sustainable Development
DEESD aims to identify the crucial role that e-commerce and e-work can play in creating an information society that is more user friendly, socially inclusive and environmentally sustainable. The project will build a convincing "business case" for the contribution that can be made by e-commerce and e-work to sustainable development, including a policy framework for "sustainable electronic markets" and make further recommendations to the EC, EU member states, local authorities, businesses and NGOs.
FLEXWORK Demonstrating and promoting the take-up of new ways of FLEXIBLE WORKING among outlying regions and SMEs.
The project will develop Service Deployment Templates, using SME's in developing regions in Ireland, Portugal and Eastern Europe as usage case studies. It will channel and demonstrate these Service Deployment Templates and the underlying flexible working technology directly to the users by participating in their own conferences, workshops, publications and websites. It will support all levels of flexible working technology, from application software (e.g for collaborative working and virtual meetings) to the underlying communications infrastructure, with emphasis on the use of open standards.
ECATT Benchmarking Progress on Electronic Commerce and New
European policy is increasingly focussed on promoting the business techniques and new ways of working which will provide the economic and social foundation of the Information Society. It will be essential to monitor the effectiveness of this policy, some indication of progress and of
Methods of Work areas requiring more or more concerted action. At the same time, many areas of European business urgently need of information about the speed of these developments in European markets, which they expect to have a strong impact on their global competitiveness. Despite the increasing number of studies on electronic commerce and telework, no single source of reliable empirical information exists on the extent, scope, nature of and factors affecting the speed of these developments in Europe. The ECaTT project will generate representative information on the prevalence and spread of electronic commerce and new forms of work in Europe. It will also
give an up-to-date picture of major practices, projects and schemes across Europe. ECaTT will conduct three major data gathering activities.100 case studies in most Member States, with half each focussing on new ways of working and on electronic commerce. An Interview survey of 7,500 EU citizens in at least 10 EU Member States covering attitudes to and practice of new ways of working and electronic commerce An Interview survey of at least 4,000 EU businesses in at least 10 EU Member States, covering current practice and plans to introduce the various forms of new ways of working and electronic commerce.
Name: Simon ROBINSON E-Mail: [email protected] Name: Werner B.KORTE E-Mail: [email protected] Company: EMPIRICA - Society for Communication and Technology Research ltd. Oxfordstr. 2 D - 53111 Bonn Tel: ++49 (0)2 28-9 85 30-0 Fax: ++49 (0)2 28-9 85 30-12
INDIC@TOR A cross-cultural study on the measurement and enhancement of employability in small and medium sized ICT companies
In an ever changing, global, technologically demanding business environment, sourcing and retaining talent becomes the competitive battleground. One way to adapt the activities of firms to the exigencies of the fast changing demands in their environment, is to increase the employability of personnel. This involves (both at the level of the individual as well as the organisation) the enhancement of job-related expertise and professional growth. In this project, seven European countries will provide psychometrally sound survey and interview data on software engineers working in SMEs in the ICT sector. Recommendations and a selection of the practical results to enhance employability will be communicated to SMEs, IST projects, policy makers and other related stakeholders. Moreover, best employability practices will be identified and disseminated widely across Europe.
The intention of the study is to research how the new technologies may transform lives in the broadest sense. Postal Operators will face dramatic changes in their core business. The working place of postal workers and the quality of their workplace and tasks will change. But also for the citizens that are in contact with the posts, there will be many changes such as new services and possibilities. Postal operators play a crucial role in the economic cycle of today in both businesses and households. Postal Operators are on a daily basis in contact with an enormous number of European citizens. The interaction between these two parties, through new digital services, helps to bring new technologies closer to all European businesses and citizens and will accelerate its introduction and general acceptation.
WP2 Project URL: http://www.posteurop.org Contact Person: Name: POUW, Johannes Martin Tel: +32-2-7247280 Fax: +32-2-7263008 Email: [email protected]
FAMILIES Families, Work and IST: A study of the interactions between family trends and new work methods in the Information Society
Families are central to the adoption of new ICT-based work methods and, conversely, the new work methods can impact on families for better or worse. The FAMILIES study will provide the first comprehensive and focused investigation of this area. It will analyse the key interactions between families and the new ICT-based work methods, empirically investigate these interactions as they arise for real families, define the policy and RTD implications, and disseminate the results inside and outside the programme. The results will help the RTD programme and projects to address the requirements for "family-friendly" systems and services, and contribute to the achievement of EC policy objectives in employment, equal opportunities, information society and other fields.
The BEEP project is concerned with analysing and exploiting socio-economic best practice in four main domains of the e-Europe initiative: A) employment and skills, B) digital SME, social inclusion and regional cohesion, C) and in the important cross themes between them. Extant data sources from both Commission-supported and other high quality initiatives will be used, most of which are not widely used and few are interlinked, though there is a great need for understanding and exploiting available knowledge at a European level. BEEP will also update this best practice knowledge in line with on-going developments, especially by closely supporting RTD projects and taking up their results. Data will be analysed qualitatively and quantitatively to draw out socio-economic best practice and provide benchmarking standards. Results will be widely disseminated in the programme and produce three fully developed services: 1) socio-economic best practice, 2) benchmarking, 3) Land linked knowledge (data) bases. These services will comprise a comprehensive set of tools available interactively on a user-friendly web-site which
organisations and individuals will be able to easily exploit.
E-LIVING e-Living: Life in a Digital Europe
This project will create a co-ordinated set of pan-European longitudinal household panel studies to generate quantitative data on time-use, uptake of IST's, IST competencies, environmental impact and perceived quality of life. It will conduct analysis of this data to describe, explain and model relationships between the uptake and usage of ISTs and changes in citizen's lives and to understand how these patterns contribute to changes in lifestyles and/or quality of life. The results will be made available as a resource for future analysis or for use in subsequent projects via a website, publications and a managed programme of workshops to engage public and commercial policy makers. Finally the consortium will work towards an on-going pan-European household panel study aimed at measuring and testing the hypothesised benefits of IST's.
KISEIS Key Interventions for Sustainable Employment in the Information Society for Disadvantaged Groups
The study will analyse solutions for the socio-economic dimensions of the transition to sustainable employment in the information society for disadvantaged groups. The research will develop a framework of interventions, building on lessons from the EU EMPLOYMENT Initiative projects with sustainable IS employment and mainstreaming outcomes. The research will study indicators of success in interventions in four EU countries. Research will include interviews with former EMPLOYMENT participants currently in sustainable employment, and with employers, and case studies of mainstreaming initiatives. The project will develop guidelines and models of best practice for interventions addressing socio-economic aspects of sustainable IS employment. It will also identify and analyse ways to strengthen future EU policy and IST Programme research on an inclusive information society.
SIBIS Statistical Indicators for Benchmarking the Information Society
SIBIS is a project for the definition and piloting of statistical indicators to be used for measuring and benchmarking important domains and issues of the Information Society. These will be based on real life, rich in information and can be easily used for informing policy and practice. SIBIS will produce an indicator system which unfolds and compares the state of development of European countries towards the Information Society, carry out an initial benchmarking based on this indicator system, and strongly support the development of policy in this field. As another key result, the survey results provide an unrivalled, unique and representative single source of reliable data on current and medium term aspects in the Information Society domains across the EU member states, Switzerland, the USA and 10 candidate countries ready for use by the project's target audience.
NEWKIND New Indicators For The Knowledge Based Economy
The objective of this project is developing indicators for assessing the significance of changes in the knowledge-base underlying economic, industrial and firm performance. We aim to provide means to connect knowledge-based indicators to indicators of performance in order to draw policy relevant conclusions about the nature and extent of knowledge-based developments on economic performance. This project will develop new knowledge-related indicators of economic activity to assess: the accumulation of intangible capital across European economies; the emergence of the new "information infrastructure" of electronic commerce; the changing structure of the knowledge-base of firms.
ERMIS Electronic commeRce Measurements through Intelligent Agents
ERMIS project aims at designing, developing and validating an integrated system for the efficient statistical measurement and monitoring of electronic commerce. This integrated system will comprise closely interweaved technical (software) and methodological tools in order to identify and monitor qualitatively and quantitatively the emerging new economy. Facing the challenges of the new economy, the project will define a new business and economic model, as well as a system of new indicators for e-commerce. The development of an integrated system of data collection, evaluation and dissemination will contribute to the critical objective of reduction of the time between data collection and dissemination. Major objectives are also the information accessibility and the quality of both collected data and new indicators produced. The project aims to tackle the problem in a holistic way, by considering all aspects of the information life-cycle and combining advanced methodology and tools of areas such as statistics IT and Business Modelling.
EICSTES The primary objective is to offer statistics and to derive indicators about the European Science- WP6 Project URL:
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CONTACT DETAILS
European Indicators, Cyberspace And The Science-Technology-Economy System
Technology-Economy System in Internet. This objective will be achieved with the development of new technologies (agents) to recover data from the net in an automatic way and the application of new models and concepts to uncover relationships between the actors of the New Economy, using advanced tools as graph theory, complexity and chaos theories and social network analysis. In order to test some of the models proposed, a series of case studies involving different and complementary aspects specially relevant to the European scenario will be analysed. As an ultimate aim, we stress the measurement and evaluation of the impact of the information technologies in the Society as a whole and on the citizens and their quality of living. The indicators will be disseminated in an open user-friendly graphical environment using new web visualisation techniques.
STILE Statistics and indicators on the labour market in the e-economy
STILE aims to support the statistical requirements of the IST Programme by providing innovative methodologies and content on the statistical monitoring of the labour market in the e-economy. This includes the finetuning of statistics to match the e-economy and the monitoring of ICT-related work patterns. The project involves users systematically, and involves nine expert partners. The existing activities aimed at the extension of the coding on e-work used in national Labour Force Survey (LFS) will be analysed, in order to provide a proposal for the fine tuning of NACE and ISCO classification; an internationally harmonised module on telework for LFS; a module to cover ICT in business panel surveys; the analysis of sectoral mobility in ICT; the construction of ICT occupational profiles and the benchmark of the profiling methodologies. The project's activities will be disseminated through several tools and a concluding European conference on these issues.
STING Evaluation of Scientific & Technological Innovation and Progress in Europe, through Patents
Measurement and assessment of technological innovation is a very specific scientific subject, which is extremely important for many actors, like for example policy-makers, organisations and individuals. Therefore, it is required to extend the used methodologies and tools and to develop the required abilities and means to measure, assess and understand the on-going changes and their effects. The main objective of this project is to develop efficient, innovative methodologies and tools for the analysis of information related to the technological innovation in a pan-European level, based on patents data. In this way, new indicators will be produced and calculated on a regular basis, providing reliable information on the scientific and technological progress in Europe.
The New Economy Statistical Information System (NESIS) is a three-year accompanying measure, involving 7 partners and designed to contribute to the continuing elaboration and evaluation of European benchmarking indicators, as successive phases of the Lisbon strategy unfold and are implemented. This contribution of NESIS will be both through conceptualisation and re-conceptualisation of new information economy indicators centred on best practice, with its focus on eEurope, and through their statistical measurement on an ongoing basis via integration within the European Statistical System (ESS), with its high quality standards. The awareness-building, dissemination and networking activities through NESIS's websites and help-desks are aimed at promoting the take-up of best practice indicator methodologies and at inculcating a greater sense of urgency within the ESS to respond to the challenges posed by the dynamics of the new information economy.
B2B METRICS Statistical indicators for the information society
The project will allow for a better understanding of the B2B e-commerce development via the use of innovative frameworks and indicators. It will help to estimate forms, content, strategies and impacts of B2B e-commerce use on competitiveness employment and potential barriers to development. It will contribute to the development of toolkits for knowledge economy measurement in a co-operative way with all stakeholders. The indicators will be designed to cover the subject in a systematic and exhaustive way through the identified domains and types of indicators. Statistical problems of the indicators and data collection techniques will be discussed. An advisory committee and contacts to the relevant institutions will give support to the important dissemination aspect of the project. The project will in various ways contribute to the programmes and key actions of the FP.
LAW Labour Market Changes and welfare perspectives in Europe
Labour market trends and welfare systems are currently among the most important issues debated in the European Union, due to the deep social and economic changes that are taking place. So far, these subjects have been analysed separately, generally neglecting the mutual connections. This project aims at filling in this gap, scrutinising the effects of the emerging atypical working profiles (self-employment, temporary work, tele-work) on the welfare systems in several EU countries. The data, gathered from heterogeneous sources and structured by means of standardised indicators, will be collected in a central database, for a comparative prospect of the current situation and a projection of the expected trends. The final results will be presented at an International Conference to be organised at this purpose.
The project covers key and long debated EU issues on indicators, competitiveness and the impact of public policy. Within this broader topic it deals with issues of how public policy for
Project URL: http://www.istat.it/diecofis
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Indicators on COmpetitiveness and FIScal Impact on Enterprise Performance
enterprises and economic activity (notably tax and support policies) can be chartered and benchmarked by means of a system of ad hoc indicators derived from: (a) a multi source, integrated data base of cross-section and longitudinal microdata from enterprise administrative registers and surveys and (b) microsimulation models that can serve to simulate and monitor how policy affects the competitive process and, by so doing, foster or hinder living standards, opportunities, the growth of knowledge and innovation, and the process of development and renewal of e- and non e-activities.
RESCUE The Re-naissance Economy ; Strategy And Coordination For Europe
The clarity of 20th century markets was based on a system of fixed boundaries, with one-to-one trading relationships, linear value-chains and balance accounting concepts. A number of transformations are at work in the economy today and the impact has far-reaching implications for companies, financial markets and investors, accountants, public institutions and regulators. The search for new modes of competitiveness has opened the way for visionary entrepreneurs to exploit intangibles in previously unforeseen ways. Intangibles - R&D, propriety know-how, intellectual property, workforce skills, world-class supply networks and brands - are now the key drivers of wealth production, while physical and financial assets are increasingly regarded as commodities. The present statistical, accounting and IPR conventions have failed to keep pace with economic reality. A new generation of conceptual and analytical tools is needed to enable company boards, shareholders and investors to judge management performance and differentiate good, bad and delinquent corporate stewardship.
BISER Benchmarking the Information Society e-Europe Indicators for European Regions
The main goal of the BISER project is to define, develop and pilot a set of statistical indicators for benchmarking the progress of European regions in respect of the eEurope Initiative and the emerging Information Society. This requires to ensure that the eEurope Regions Indicators are reliable, fully comparable, based on real life, rich in information, responsive to dynamic change, cost-effective to construct and easily used in policy development and decision-making at all levels. In doing so, BISER will seek close co-operation with official statistical offices. BISER will take full account of existing statistical concepts and data sources and make every effort to ensure the newly developed indicators are taken up by official statistics agencies. The expected outcome is to provide a detailed picture of IS development at regional level across the EU, as a
means to help the EU profit from the enormous potential for achieving EU policy goals at regional level, especially in terms of social cohesion and regional development.
ESIS Development of a European Satisfaction Index System for the new economy and design of information delivery system allowing international comparisons
The ESIS project has the target to research, to develop and to implement a regular measurement of Customer satisfaction in Europe with and ad hoc software tool, and simultaneously a Data Warehouse system able to collect and manage the whole successive questionnaires. The main objective underlying the design of this system is to tackle the problem from data collection to information interpretation. This requires methodological advances in the fields of statistical models and techniques of satisfaction index estimation for the New Economy, and technical development of tools for fast data collection from the Net and functionally rich delivery of information. The system will deliver index values for individual companies, industries and sectors as well as the entire economy, and will be prepared to the e-Government.
Project URL: http://www.decisia.fr/actu/actu_esis.htm Contact Person: Name: MORINEAU, Alain Centre International de Statistique et d'Informatique Appliquees CISIA-CERESTA S.A.r.l. 261 Avenue de Paris 93100 Montreuil FRANCE Tel: +33-1-55821515 Fax: +33-1-43632100 Email: [email protected]
