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Journal of Scientifi c & Industri al Research Vol. 60, M arch 200 I , pp 2 1 1-2 19

Science and Technology Indicators in a Market Driven Economy: A Profile of India, China and Japan

S Pruthi Nati ona l Institute o f Sc ience, Technology and Development Studies,

Dr K S Kri shnan M arg, New Delhi 110 0 12

Genera ll y sc ience and techn o logy (S&T ) indicato rs are used for mapping o f S&T potenti a ls in a country. A

pe rusal o f avail able lite rature ind icates th at there is no standard model ava il able so far. Consequentl y, many

models have been deve loped in diffe rent co untri es suitin g to the ir needs. A n attempt is made to eva luate vari ous

model s ava il able in the lite rature. A few models whi ch are dealt w ith in-depth are input-output mode l o f USA. cascade model of Japan, three tie r mode ls o f Nethe rl ands and European S&T Indi cato rs model. A n a ttempt has been made to sugges t a viabl e mode l fo r mapp ing S&T potenti a ls in a marke t dri ven econo my. A mode l is

proposed bas icall y on the basis of the fo ll ow ing ass um pti ons. O nl y a robust soc io-econom ic system can support

a sound S&T system . S&T is the e ngine o f an economy. Innovati on is a non-linear process . S&T ind icators can -J.. lead to better dec is ion mak ing. W hil e sugges tin g ind ica tors , foc us is on building up o f S&T compe titi ve ness as

it is competiti veness a lone that can g ive edge to a country ove r the other country. A t present , it may not he

poss ible to constru ct compos ite ind icators o f competiti ve ness. T here fore , an attempt is made to construc t st ruc­

tura l ind icators of economic and sc ie nti fi c and technolog ica l competitiveness o f Indi a , China, and Ja pan .

Introduction A survey o f li terature on sc ience and techn ology

(S&T) indicators highli ghts that genera ll y these indi ­

cators have been used to measu re S&T potenti a ls or to describe its status in a country. Different countries have used di fferent mode ls su iting the ir needs from time

(0 time. Sc ience planners and po licy- makers in the US were not sati sfied with R&D stat ist ics and this led to

publicat ion of the first Sc ience and Techno logy Ind ica­tors Report in 1972. S ince then, S&T Indicators Re­

p0l1 has been publi shed regul arly in the US every 2y. Th is repoI1 uses in put-ou tput data, mainly on financ ial resources, and on S&T manpower as inputs and publ i­

cations and patents as ou tpu ts. In addi tion, ind icators of publ ic att itude towards S&T and achievements in sc ience are covered . Recently, a new dimension on en­gineering has been added and the report is now known as Science and Engi neeri ng I nd icators I. [n the Nether­

lands\ a th ree-tier model is used for describ ing diffe r­ent aspects of the S&T system. Tier one represents the S&T base captu red by ind icators peI1aining to the higher educational system, e.g. number of univers it ies and stu­

dents, public attitude towards S&T and its results , level

of unemployment of graduates, postgraduates and doc­torates. Tier two represents the R&D infrastructure cap­

tured by indicators that cover the aspect of direct sup-

port to R&D acti vities , such as S&T manpower, R&D

funds, technology, ba lance of payments and institutional

framework. Tie r th ree comprises R&D results. Output indi cators of sc ienti fic and technological know ledge re late to papers publi shed, patents filed and accepted ,

the ir c itation patte rns and nati onal and in ternat ional col­

labo rat ion underl y ing there in. The author argues in this paper that a set of these in terre lated ind icators can gi ve

a pic ture of the S&T system and its economic perform­ance, thereby he lping in ascerta ining the hea lth of S&T system.

A cascade structu re as an appropriate way of describ­

ing S&T has been adopted by the system prevalent in

Japan \ This approach addresses two crucial issues: relevance and causa lity. In a report on Japanese S&T Ind icators, indicators were arranged in a se ri es or stages

whereby each stage derives or acts upon the product/ output of the precedi ng stage; th is atTangement is termed

as cascade structure . This structure consists of six ma­jor categories: soc ietal infrastructure, sc ientific and tech­

nological infrastructure, R&D infrastruc ture, R&D re­sul ts, S&T contribution and societal acceptance of S&T.

The US model bas ically represents sc ientifi c research as a black box . For doing research, one needs financ ial and manpower resources and therea fter output is gen­erated in terms of research publicati ons and patents.

2 1 2 J SCI IND RES VOL 60 MARCH 200 1

Table I - Indicators of technological competitiveness (Scores)

Country National orientation Socio-economic Technological Productive infrastructure infrastructure capacity

China 62.3 43.4 38.6 33 .2

India 52.4 46.4 33.0 38.6

Japan 85.3 72.7 83.7 92.7

Source: Asia s New High Tech Competitors An SRS Special Report, National Science Foundation NSF 90-309

Since S&T is not supported by public funding alone, an attempt to capture the perception of the public to­wards S&T i s also incorporated . However, it has not been attempted to l ink the S&T system with the other socio-economic systems in the US and to compare the US S&T system with other intematioiial S&T systems. In the Netherlands, the first tier describes the status of the educational system responsible for generation of S&T manpower, the second tier represents R&D infra­structure in terms offinancial resources and S&T man­power and the institutional frame, and the third tier rep­resents the output of R&D results. Although it has taken balance of payment as one of the parameters for meas­uring R&D infrastructure, it does not take into account the socio-economic system as such into consideration, inside which the science system is operating. Though the Japanese cascade structure consists of social struc­ture, scientific and technological infrastructure, R&D infrastructure, R&D resu lts, S&T contribution and societal acceptance of S&T, the interre lationships among various parameters have not been considered.

This paper argues that in the era of global isation, where competitiveness is the thrust of economic devel­opment, it is necessary to capture indicators of various parameters representing l inkages between the socio­economic system and the S&T system. This is so be­cause the S&T system is not operating in vacuum. It is embedded in the socio-economic system. If one flour­ishes, the other is bound to prosper. It is a different matter that the S&T system faci l itates prosperity of the socio-economic system and in turn the funding of S&Tsystem gets strengthened. The funding mechanism, whether through government or industry, may not ap­pear significant. Secondly, in a globalised economy, the countries are interdependent and so are the differ­ent S&T systems. Therefore, competitiveness and co­operation are the crucial needs of the hour (Table I ) .

With the globalisation of world economy and rapid development of means of transport and communication, national economies have been thrown open. Nations

are facing common and crucial problems, such as ex­ploding populations, environmental pol lution, ozone depletion, and inadequate management of scarce water resources. Consequently, the economic systems and the S&T systems have become interdependent. As a re­sult, there is a thrust on co-operation, collaboration,joint programmes and co-operative projects. Since competi­tiveness has become the thrust of economic develop­ment and each nation is attempting to gain advantage over the other nations, there is a need to evolve a new set of indicators reflecting competitiveness of a coun­try in terms of the joint-performance of its economic and S&T systems, considered together. Secondly, indi­cators reflecting comparison among different S&T sys­tems and economic systems at different stages of de­velopment and S&T networking, etc. need to be worked out .

An attempt has been made in th is paper to evaluate various models available in the l i terature. A few mod­els which are dealt with in-depth are input-output model of the US, cascade model of Japan, three tier models of Netherlands and European S&T Indicators model . An attempt is also made to suggest a viable model for mapping S&T potentials in a market driven economy. A model is proposed basical ly on the bas is of the fol lowing assumptions. Only a robust socio-eco­nomic system can support a sound S&T system. S&T is the engine of an economy. Innovation i s a non- lin­ear process. Science and technology indicators can lead to better decis ion making. Whi le suggesting indica­tors, focus is on bui lding up of S&T competi tiveness as it is competitiveness alone that can give edge to a country over the other country. At present, it may not be possible to construct composite indicators of com­petitiveness. Therefore, an attempt is made to construct structural indicators of economic and scientific and technological competitiveness of India, China and Ja­pan . The next section describes the pyramid model proposed in the paper, fol lowed by the section on in­dicators of economic competitiveness. The subsequent section describes indicators of science and technol-

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PR UTHI : S&T INDICATORS IN MARKET DRIVEN ECONOMY 213

ogy competiti veness, including indicators on sc ientific co-operati ons. A brief conclusion foll ows.

S&T Indicators and Market Driven Economy The proposed model of S&T indicators is based on

the foll ow ing assumptions: S&T playa crucial ro le in socio-economic development of a country. It is we ll known that technology is the engine of economic de­velopment. It helps in meeting the bas ic needs includ­ing access to food, better education, improved health care, or an increased industri al output and more effi­cient means of transportation and communicati on. In the developed countries, these technological deve lop­ments are being effec ted through their formal R&D in­frastructure. It is we ll recogni sed that R&D not onl y help in the absorption, ass imil ati on and adapt ati on of imported technology, but also helps in deve lopment of indigenous technologica l capabilities . Therefore, here S&T has been considered as a single enti ty. The sec­ond assumption is that onl y a robust econom ic system can support a sound S&T system. This is quite ev ident fro m the relati onshi p between the quantum of R&D expenditure and GNP of advanced countries.

Thi rdly, innovation is a non-linear process where output is not merely a functi on of input. A country can acquire innovati on from both intern al and ex tern al sources. Internal sources represent indigenous R&D in frastructu re, while innovati ons/technologies can be acquired from advanced countries. The developed coun­tries account fo r about 82 per cent of global R&D ex­penditure and also have a major share (93 per cent) of technological capabilities in terms of paten:s filed in the US and Europe. Tn other words, the develop ing countries are completely dependent on advanced coun­tries fo r acqu iring technologica l development4• In view of global isati on of the market, where competi ti on is the key to economic development, it may not be possible to get the latest technology from abroad . In thi s con­text, it becomes essenti al fo r the develop ing count ries to develop their own R&D infras tructure/system which will fac ilitate not only absorption, ass imilation and ad­aptation of impol1ed tech nologies but will al so facili ­tate development of tech nology capab ility and ulti­mately help them in bui ldi ng up competitiveness and giv ing an edge to the country over other countries. Hence, S&T indicators in a market driven economy need to focus on building up of "S&T indicators of competi­tiveness", as it is competitiveness alone that can hel p in building economic competence and giving an edge to the country over other countries. However, competi­tiveness of a country depends upon its capacity to inno-

vate and the capac ity to innovate depends upon the sta­tu s of S&T system it possesses. An attempt has been made here to construct structural indicators of economic as well as scientific and technologica l competiti veness of India, China and Japan. The main focus is on cap­turing ind icators of competiti veness which arguabl y is the main thrust of economic development. The rea­sons fo r choosing China, India, and Japan for th is exer­cIse are:

First, to compare indicators of competiti veness of an advanced country with those representing countries which are not so well developed. Secondly, comparing indicators of these countries will fac ilitate making a rea listic assessment of the degree of soc io-econom ic and technologica l developments these countries had undergone. Thirdl y, the analys is will reflect on link­ages between S&T and economic development and per capita nat ional income in respect of these countries . Fourthly, Japan is considered as a technologicall y ad­vanced country, while China and India are not so tech­nologicallyadvanced. Nevertheless, these three coun­tri es be long to th e same reg ion, As ia. Therefo re. commonalties and diversities of th is reg ion may make the exercise interesting. Although China and India have diffe rent po litica l systems, they are fac ing comillon soc io-economic problems such as large populati on, poverty and underdevelopment, an ag ricultu re-based economy. Apart from thi s, the geograph ical locations of China and Ind ia are strategica ll y important in the globa li sed scenario. Despi te the fact that Ch ina does not have a progress ive and democrat ic pol itical system, it is coming up in a big way in a globalised world , while India is still lagging behind in spi te of the fact tha t it is one of the largest democracies in the world .

lndicators of competitiveness can be represented by a pyramid' (Figure I).

Standard of livi ng is the crown of the competitive­ness pyramid, because achieving it , is the ultimate aim of a market economy. Standard of liv ing is perhaps the central indicator of nat ional competitiveness. For sim­pl icity, it is represented by per capita GNP/GDP. Sec­ond tier represents exports. Exports are dependent on nati onal productivity rate and national levels of capita l investment in products and processes of production. Growth rates and levels of exports can be significant ind icators of national competitiveness. This should also include growth rates and levels of imports and balance of payment. Export/import ratio could be an important indicator of trade efficiency. Export as percentage of total production can also serve as a crucial indicator of efficiency of the production system and serv ice. of a

2 1 4 1 SCI IND RES VOL 60 MARCH 2001

Productivity

Figure 1 - Represents indicators of competitiveness

nation. Third tier represents productivity. Productivity is the efficiency with which goods and services are pro­duced and provided. It is mainly determined by previ­ous investment and by the quality of plant and equip­ment and the effectiveness with which these factors of production are uti l ised. As such, productivity is both a determinant and an indicator of national competitive­ness. Here, an attempt is made to study agricultural and industrial productivities. Investment is the fundamen­tal building block of current and future economic ac­tivities and, therefore, forms the base of the Gompeti­tiveness pyramid. Investment is also the fundamental determinant of national competitiveness. In addition to investment in hard assets, investment in soft assets - R&D expenditure and technological development - are crucial components of investment in respect of S&T competitiveness of a country.

Here indicators of competitiveness have been dealt with under the fol lowing heads: (i) Indicators of Eco­nomic Competitiveness and (i i) Indicators of S&T Com­petitiveness. Data have been collected from publ ished reports. S ince data have been compiled and computed from different reports, it is but natural to have variation in data definition, base years, and even in the concepts used while collecting data. Nevertheless, terms used in this paper are universally understood and no separate definition l isting is provided. Data regarding trade stmc­ture for various countries for a particular period were not available. Hence, a short write up describing the stmctural changes in technology trade in respect of the said three countries has been included. Final ly, because

of lack of relevant data, only a few indicators have been constructed. Indicators described here are only repre­sentative of the probable l ist of indicators which one should have constructed. Therefore, one had to remain contented with structural indicators, in the absence of developing upon the composite indicators. Secondly, it has not been possible to make causal and relevance analyses. The present study gives the descriptive sta­tus of indicators only. The fol lowing discussion draws upon data and findings reported in the cited texts, and hence in order not to repeat the same, th is paper refers to the cited texts without presenting the proper tables.

Indicators of Economic Competitiveness At macro-level, effort has been made to examine a

set of economic factors which are l ikely to influence R&D investment in a country. A few of such crucial factors are: growth of GDP/GNP per capita, changes in composition of GDP and value added in agriculture, industry and services; trade and BOP in respect of manu­facturing of high-tech products and productivity of ag­riculture and industry resulting in generation of sur­pluses. Ultimately, a part of these surpluses may be in­vested in bui lding R&D infrastructure of a country. At

micro level, an attempt has been made to examine stmc­tural changes in trade of manufactured high tech prod­ucts and ratio of exports to import:5 .

China appears to be performing better than India and China's average annual growth rates of gross domestic products (GDP) were h igher (around 6 per cent) during 1 99 1 - 1 992 compared to those for India. However, Ja-

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PRUTHI : S&T INDICATORS IN MARKET DRIVEN ECONOMY 2 1 5

pan had the highest per capita GDP throughout, while India had the lowest per capita GDP. A steady increase in per capita GDP in the case of India was an encourag­ing trend6. In year 1 997, Japan had the highest per capita GNP ($37050), whereas India had the lowest per capita GNP ($390)7. Variation in value added changes in GDP in these three countries over a period of time indicates the structural changes taking place which may be re­lated to the stage of economic development of a coun­try. In respect of China, industry and services had made relatively greater contribution in 1 997 in comparison to 1 980, while the share of value addition by agricul­ture had decl ined significantly over the period. A simi­lar pattern can be noted in the case of India. Services in Japan had made significant contribution in 1 997 com­pared to 1 980. To sum up it could be said that services in Japan, industry in China and agriculture in India had contributed the largest share to value addition to GDP in 1 997.

During 1 990-95, Japan had shown double digit rates of growth in the imports of high tech products' ; im­ports and the rates of growth in respect of these varied between 1 25 per cent and 30.8 per cent. In the case of India, the rates of growth showed considerable varia­tion during 1 980-95 . Rates of growth were the highest during 1 980-85 ( 1 1 7.5 per cent average) and declined in 1 990 (- 1 3 .3) and 1 99 1 (-30.70). S ince then, rates of growth were 28.86 per cent in 1 992, 80.7 per cent in 1 993, and -7.42 per cent in 1 994, later in 1 995 the rate of growth rose to 5 per cent. Thus, the picture in this respect has been rather erratic. Japan showed a steady rise in exports, the rate of growth in respect of high­tech products, was the highest in year 1 993 (20. 1 6 per cent) and the lowest in 1 990 (-0.6 per cent). Export of high-tech products in the case of China showed a con­tinuous rise during 1 992-95, but rates of growth showed a great variation, i .e. , between 36 to 53 per cent. In the case of India, exports of high-tech products showed an uneven pattern of growth. The highest rate of growth was recorded in year 1 994 (35 .6 per cent) and the low­est was recorded in 1 992 (-2.66 per cent).

Export/import ratios were excel lent in respect of Ja­pan throughout the period. This ratio was more than two. However, in the case of both India and China the ratios were less than one. There was, however, a steady improvement during 1 992-95 . China was mainly ex­porting machinery, electronics products, electrical ma­chinery, telecommunication and sound recording and reproducing equipment and transport equipment. In respect of h igh-tech products, China was exporting com­puters and telecommunication, electronics equipment,

nuclear and biotechnology materials while importing computers, telecommunication, l ife sciences, aerospace and aviation equipment, electronics goods, and materi­als, etc., in year I 992x. In respect of manufactured goods, India is sti l l importing a substantial quantities of artifi­c ial resins, plastics, petroleum crude and petroleum products, chemicals, iron and steel, machinery and in­struments, electrical machinery, electronic goods, etc. India's comparative advantage in h igh-tech products, petrochemicals, electronics, and consumer goods is pres­ently poor.

Again India's comparative advantage i s potentially high in food and food processing, agricultural commodi­ties, textiles, specialty chemicals, automotive parts and mineral based products. India's comparative advantage is presently high in two wheelers, leather, gems and jewellery, software, l ight engineering products,), etc. In Japan, the three top technology exporting areas are the transport machinery, and electrical machinery, electronic equipment. Iron and steel industry is another industry enjoying high technological surpluses. However, mo­tor vehicle industry exports had increased rapidly over the past five years. The increase in trade was attribut­able to highly developed R&D expertise of the Japa­nese. In the case of pharmaceuticals, communication equipment and electronics/electrical industry the export and import trades balance each other I I). Agricultural productivity is measured in terms of agricultural value added per worker of land. Both agricultural value added per worker and per hectare were the highest in the case of Japan. Though, agricultural value added per worker showed a great deal of improvement during 1 979-8 1 and 1 994-96, the agricultural value added per hectare of land however, showed lower increase. However, in the case of India agricultural value added per hectare showed relatively higher increase than value added per agricultural worker.

Indicators of Science and Technology Competitiveness

The developing countries can fol low any number of paths for economic development. Japan provides a highly successful model, partly drawing its strength from large national investments in education and R&D as wel l as from its wil l ingness to learn from and bu ild on technological advances made elsewhere l l . R&D ac­tivities serve as an incubator for new ideas that lead to new processes, products, and even industries. In addi­tion, R&D activities are associated with many new ideas that have shaped the development of modern technol­ogy. Here, an attempt has been made to capture the

2 1 6 J SCI IND RES VOL 60 MARCH 200 1

potentials of S&T system of Japan, China and India in tenns of R&D expenditure as per cent of GNP, expendi­ture on S&T manpower, research publications, citations, patents filed and granted and other related aspects. In addition, i t is also believed that in order to achieve �uc­cessful innovations along with a competi tiveness, it is necessary to have co-operation . Therefore, efforts have also been made to quantify S&T co-operation at inter­national level . S&T competitiveness can be measured on the basis of the following parameters:

• R&D expenditure denotes national commit­ment of a country to R&D. It is the base of competitiveness.

• Sources of R&D funds: Diversity in financial sources for support to R&D indicates the use­fulness of R&D to different sectors : govern­ment, industry, foreign and others.

Scientists engaged in R&D represent another measure of support to R&D activity. Techni­cians are indicators of technical support given to R&D scientists/engineers engaged in R&D.

R&D expenditure per scientist denotes ameni­ties and facil ities provided to R&D scientists in a country.

• Number of publications/patents gives an idea regarding output generated by R&D scientists and engineers and it is also a measure of pro­ductivity of scientists.

• Citations received i s an indicator of the impor­tance given to a research publication by fellow scientists/engineers engaged in R&D in a spe­cific discipline or related discipl ines.

a Patent activity by resident inventors provides a measure of R&D productivity of a nation. The numerical ratio between resident and for­eign inventors is a measure of sufficiency in technological development in different disci­plines. This measure is also known as auto sufficiency.Ratio of foreign patents to resident patents also suggest dependency of a nation on foreign scientific and technological develop­ment. At the same time patenting by foreign inventors highl ights a nation's attractiveness as a market for new technologies. Residents patenting in foreign countries is an indicator of technological development playing a cru­cial role in future economic competitiveness. In fact, al l these parameters can be grouped

under three categories: (a) Financial Resources devoted to R&D, (b) Human Resource Devel­opment and (c) Output.

Financial Resources Devoted to R&D

Total R&D expenditure showed a steady increase in all the three countries. Japan devoted the largest quan­tum of R&D funds during 1 980- 1 995, fol lowed by China while India accounted for the lowest share in tenns of R&D expenditure as percentage of gross do­mestic product. R&D expenditure by industry was also on similar l ine except that Chinese Industry started in­curring expenditure only after 1 992. However, its share was larger than that of India. Major sources of R&D funds were government and industry in all the three countries, Japan government contributed the smallest share to its total R&D funds. Needless to say that per capita R&D expenditure was highest in Japan ($825) fol lowed by China ($2.5) and India ($2.4). R&D ex­penditure as percentage of GNP exhibited a similar trend (Table 2).

Human Resources Development

The number of bachelors in natural sciences and engineering grew faster in India than in Japan and China during 1 980-90. However, the number of scientists and engineers per mil l ion popUlation was the highest in Ja­pan (6309), fol lowed by China (350). S imilar trend was observed in respect of technicians per mil l ion popu­lation . India had the highest number of technicians/ scientists (0.7), closely fol lowed by China (0.6).

Output

The number of scientific publ ications showed a steady growth in Japan and China, while the pattern of growth was uneven in the case of India. The average rate of growth was the highest in China ( 1 7.4 per cent average) fol lowed by Japan (4.40 per cent), it was low­est in the case of India (2. 1 2 per cent). The number of citations received showed the highest average rate of growth (26.3 per cent) in the case of China, whi le Ja­pan had only 6.40 per cent average growth rate. The lowest average rate of growth was observed in the case of India (0.06 per cent).

In Japan, more than 75 per cent of the patents were filed and granted to resident inventors. In the case of China the share of residents i nventors was about 50 per cent. However, the share of resident inventors in India was about 30 per cent. The share of non-resident in­ventors fi l ing patents in India was around 70 per cent during 1 985-90. The number of patents fi led in Japan

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PRUTHI : S&T INDICATORS IN MARKET DRIVEN ECONOMY 217

Table2 - Publication output and trans-national links of maj or countri es

1982- 1984 1992- 1994

PUB COP PUB COP

China 8 103 18 14 23943 H729

India 34783 2438 33457 5702

Japan 99643 6926 156023 245750

by non-resident inventors was only 8 per cent of the tota l patents fil ed in 1990. The number o f patents fil ed in the European countries by Japanese inventors has been continuously increas ing, this numbe r standing around 8000 in 1994; while in the case of China and India the number is very low (a mere fracti on of Ja­pan 's share).

Technological Competitiveness

Technological competiti veness has been assessed on the basi s of scores, (as suggested by the National Sci­ence Foundation of the US), assigned to national ori en­tati on to technol ogy, soc io-econo mic infrastructure, technolog ical in frastruc ture and productive capac ity (Table l).

National Orientation - This indicates that a nat ion is tak ing directed action to achieve techno logica l com­

petitiveness.

Socia-economic Infrastructure - This indicator as­sesses the social and econom ic inst itutions that support and maintai n the phys ical , human , organizat ional and economic resources essentia l to functioning of a mod­ern , techno logy based industrial nature.

Technological Infrastructure - T hi s indicator as­sesses the institutions and resources that contri bute to a nati on's capacity to deve lop, produce and market new technology.

Product Capacity - This indicator assesses the physical and human resources devoted to manufacture products and effic iency with which those resources are employed.

Japan had the highest score in respect of nat ional orientation, socio-economic in frast ructure, technolog i­cal infrastructure and productive capacity; whi Ie C hina had a higher score in respect of nat ional orien tati on and techno logical infrastructu re in comparison to India but

Table 3 - Growth rates in publi ca tions and co-operatioll l inks during 1980-84 to 1992-94

Country Publi cation output , Link,

per cent per cellt

China 11 .4 17.0

India -0.4 8.9

Japan 4.6 13.6

these scores are far below than those for Japan. China and India have to go a long way to reach the scores achieved by Japan in respect o f national ori entation, socio-economic infrastructure, technological infrastruc­ture and productive capac ity.

Scientific Co-operation

Here an attempt has been made to measure sci entific co-operation in terms of co-authorship 's of artic les which s ignify fo rmal ack now ledgement of j oint re­

search. International co-operati on has been playi ng a greater role in the generati on of knowledge than in the past and this role is like ly to become cruc ial in future in the g loba li sed scenari o. It appears that the vo lu m of sc ientific co-operati on is growing faster than research output and research publications 11. The co-operati ve

e fforts [COP] made by a g iven set of countri es can be measured by counting the lin ks created through co­authored artic les. Us ing the counts of co-operation links three indicators can be employed for assessing and com­

paring the co-operati ve efforts made by di fferent coun­tries. T hese are: ( i) Partic ipation Index [PAl] , (ii ) Co­operati on Index [COl] , and (iii ) Co-operation Densi ty [COD].

Parti cipation Index shows the degree of parti c ipa­tion of a country in the inte rnational sc ienti fic COllllllU­

nity. PAl is computed as fo llows:

Total COP of a country PAl = ---------X 100

Total COP's of the world

Co-operation Index - This index measures the inci­dence of co-operation links in a g iven fi e ld compared to publication output in that field .

Number of Co-operati on links COI =------~-----

Number of all articles X 100

2 1 8 J SCI IND RES VOL 60 MARCH 2001

Table 4 - Comparison of co-operation links

Country

China

India

Japan

PAl

085

1 . 1 4

.34

1 982-84

COl

22.39

7.0 1

6.95

Legend: PUB = Total Number of Publications

PAl : Participation Index

COD : Co-operation Density

Co-operation Density is an index which compares the co-operation index of a country with that of the entire world. The index is computed as fol lows :

cal of Country A COD =-----­

COl of the World

During 1 982-84 to 1 992-94, India had a negative or zero growth rate (-0.4 per cent) in research publications and had contributed about 9 per cent to the total co­operation l inks. China had 1 1 .4 per cent growth rate in research publications and contributed 1 7 per cent of the total co-operation l inks, while Japan showed about 4.6 per cent of growth in research publications. Japan had the highest participation index (2.4 in 1 982-84 and 4.02 in 1 992-94), while China had the highest co-op­eration index in both 1 982-84 and 1 992-94, i .e., 22.39 and 36.46 ,respectively. India could be ranked second in respect of participation index and co-operation in­dex, but its co-operation density was the lowest (Ta­bles 2, 3 and 4) . During 1 982-84, China had only the US and the UK as partners . However, in 1 992-94, it had maintained strong l inks with the US, the UK, Ja­pan, Australia, Canada, Germany and Italy. Ind ia's sig­nificant partners were USA, Germany and Japan, How­ever, l inks with UK and Canada were not as strong as during 1 982-84. It is interesting to note that Japan had only one partner, i .e., the US.

Conclusion

In terms of both economic and S&T competitive­ness, Japan has performed velY wel l . As regards eco-

COD

1 .67

0.52

0.5

PAl

1 .42

0.93

4.02

1 992-94

COl

36.46

1 7 .04

1 5 .80

COD

1 .23

0.57

0.53

COP = Total Number of Co-operation Links

COl : Co-operation Index

nomic competitiveness, the annual rate of growth of GDP was h ighest in the case of Japan . Even per capita GDP was highest throughout the period under study. Service sector had contributed the largest share of GDP. Japan had performed well, both in-terms of publication and citation indicators. In the case of patenting activ­ity, Japan was at the top, both in its own country and in European countries. It appears that China is coming up in a big way in its scientific and technological and eco­nomic competitiveness, while India has to go a long way. It has done wel l in respect of scientific publica­tions but not so well in patenting activity. Simi larly, in respect of scientific co-operation in terms of co-opera­tion density, India is sti l l to go a long way.

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About the author S Pruthi graduated from Delhi University and obtained her doctorate from Banaras

Hindu University. Her research interest includes planning and management of research,

science and technology indicators. She has published three books and contributed

more than 55 research papers in Indian and foreign journals.