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AUTHOR QUERY FORM
Journal: TFS Please e-mail or fax your responses and any corrections to:Carol ListonE-mail: [email protected]
Article Number: 17661
Dear Author,
Please check your proof carefully and mark all corrections at the appropriate place in the proof (e.g., by using on-screenannotation in the PDF file) or compile them in a separate list. Note: if you opt to annotate the file with software other than AdobeReader then please also highlight the appropriate place in the PDF file. To ensure fast publication of your paper please returnyour corrections within 48 hours.
For correction or revision of any artwork, please consult http://www.elsevier.com/artworkinstructions.
Any queries or remarks that have arisen during the processing of your manuscript are listed below and highlighted by flags inthe proof. Click on the ‘Q’ link to go to the location in the proof.
Location in article Query / Remark: click on the Q link to goPlease insert your reply or correction at the corresponding line in the proof
Q1 Please confirm that given names and surnames have been identified correctly.
Q2 Highlights should consist of 3-5 bullet points. However, more than 5 points were provided. Kindlymodify the provided Highlights to conform with the requirement. For more information, please seeGuide for Authors.”
Q3 Table 10 was not cited in the text. Please check that the citation suggested by the copyeditor is in theappropriate place, and correct if necessary.
Q4 Please supply the year of publication.
Please check this box if you have nocorrections to make to the PDF file. □
2Technological Forecasting & Social Change xxx (2012) xxx–xxx
4
5An integrated service-device-technology roadmap for6smart city development78Jung Hoon Lee a,⁎, Robert Phaal b, Sang-Ho Lee c
910a Graduate School of Information, Yonsei University, 134 Shinchon-dong, Seodaemun-gu, Seoul 120-749, Republic of Korea11b Centre for Technology Management, Institute for Manufacturing, Engineering Department, University of Cambridge, 16 Mill Lane, Cambridge, CB 1RX, UK12c Ubiquitous City Research Center, Dept. of Urban Engineering, College of Engineering, Hanbat National University, 16-1 Dukmyung-dong, Yuseong-gu,13Daejeon 305-719, Republic of Korea
1415► A novel integrated strategy process for large-scale service-oriented infrastructure systems ► National roadmap for smart cities, considering16convergence of technology, devices and services ► Integration of roadmapping and quality function deployment (QFD) methods to support17foresight ► Use of roadmapping to support coordination of large complex research program ► All tables and figures are readable and tested18with the printed manuscript. ► All typos are corrected by the co-author who is native English as reviewer 1 suggested. ► Numbers of tables19are reduced from 12 to 9 as reviewer 1 suggested. ► Numbers of figures are also reduced from 8 to 4 as reviewer 1 suggested.
20
21
Technological Forecasting & Social Change xxx (2012) xxxTFS-17661; No of Pages 1
Contents lists available at SciVerse ScienceDirect
Technological Forecasting & Social Change
Please cite this article as: J.H. Lee, et al., An integrated service-device-technology roadmap for smart city development,Technol. Forecast. Soc. Change (2012), http://dx.doi.org/10.1016/j.techfore.2012.09.020
OF 1An integrated service-device-technology roadmap for smart
2city development
3Jung Hoon Q1Lee a,⁎, Robert Phaal b,1, Sang-Ho Lee c,2
4a Graduate School of Information, Yonsei University, 134 Shinchon-dong, Seodaemun-gu, Seoul 120-749, Republic of Korea5b Centre for Technology Management, Institute for Manufacturing, Engineering Department, University of Cambridge, 16 Mill Lane, Cambridge, CB 1RX, UK6c Ubiquitous City Research Center, Dept. of Urban Engineering, College of Engineering, Hanbat National University, 16-1 Dukmyung-dong, Yuseong-gu, Daejeon 305-719,7Republic of Korea
8
10a r t i c l e i n f o 11a b s t r a c t
12Article history:13Received 13 March 201214Received in revised form 28 September 201215Accepted 29 September 201216Available online xxxx
30Keywords:31Integrated roadmapping process32Service and technology roadmap33Smart city planning and development34Quality function deployment
3536
37381. Introduction
39Technological innovations, and changes in globally competitive business environments, affect both firms' short-term40performance and long-term sustainability. In such a context, decisions about which technology to apply are critical to many firms'41competitive advantage. In particular, when future directions and options in technology are obscure and uncertain, it becomes42more important to an enterprise to formulate an appropriate technology strategy to support its planning for, and response to,43future technical developments [38,51,60,64]. Technology roadmapping (TRM), a strategic decision process framework that44supports enterprise innovation activities, has attracted the interest of an increasing number of academics and practitioners, and45has been applied in many different industrial sectors and organizations [44]. A study of U.K. manufacturing firms in 200146indicated that at that time 10% of medium-to-large companies had implemented TRM, with 80% of those companies using the47approach more than once or continuously, with exponential growth in interest in the method since the early 1990s [6]. As well as48responding to market needs, roadmapping is used to support the generation of new ideas for product development, derived by49predicting future technological trends and identifying potential technologies [23,45].50In recent years, a trend towards servitization has also caught the attention of academia, practitioners and governments51[10,63,73,74]. This term, initially proposed by Vandemerwe and Rada [79], has grown into a distinct concept of service science,52which has consolidated itself as a new academic discipline, providing impetus to developments in industry [5,53]. Service science53provides a conceptual foundation for service-oriented business models, promoting the development of flexible and robust
Technological Forecasting & Social Change xxx (2012) xxx–xxx
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Technological Forecasting & Social Change
Please cite this article as: J.H. Lee, et al., An integrated service-device-technology roadmap for smart city development,Technol. Forecast. Soc. Change (2012), http://dx.doi.org/10.1016/j.techfore.2012.09.020
54IT-based business models capable of responding efficiently to diverse customers' demands. In these terms, servitization is55intended to enhance an organization's ability to add value to new products by strengthening their planning processes, integrating56these with the delivery of services and generation of value in consumption or use [5]. For instance, the ‘smartphone’ and its57software applications are aligned in terms of the combination of technologies, products and services they offer (and depend on)58through a concept of service provision that prioritizes the creation of value to end-users [80].59Despite this emerging trend, research in technology roadmapping has tended to focus on specific examples of industrial60technology deployment and product development, paying much less attention to the application of roadmapping as a paradigm61to the service area [76]. This paper, therefore, highlights the importance of having an integrated roadmapping process as a holistic62framework for supporting improved decision-making. Further, it proposes an integrated roadmapping process that is systematic63and standardized in order to coordinate the development of integrated product and service strategies. The proposed roadmapping64process has been applied to a smart city development project in order to demonstrate and validate the utility and benefits65of the methodology. The process specifically aims to forecast the development of future service-oriented smart devices and66technologies, and thus to propose an integrated process for roadmapping. The paper adopts the QFD (Quality Function67Deployment) method to establish interconnections between services and devices for infrastructure, and between devices and68technologies serving a ‘smart city’. The method is particularly useful in coordinating and adjusting existing service, device and69technology roadmaps and lends itself to use as a communication tool to support smart city development.70The paper contributes to broadening our understanding of the technological impact of likely future technologies and71technology-based services on IT-based smart device development. The paper is organized as follows. Section 2 reviews the history72of the concept of TRMwith reference to the literature, establishing a conceptual foundation for roadmap development processes, and73identifying different types of roadmaps. Based on this analysis, a distinct methodology is proposed in Section 3, backed up by a74detailed case study. Finally, conclusions are presented in Section 4, recommending areas where further research would be beneficial.
752. Literature review
762.1. Smart city service development
77The smart city concept originated from that of the ‘information city’, and incrementally evolved to an idea of an ICT-centered78smart city. The concept of the smart city has six main dimensions: a smart economy, smart mobility, a smart environment, smart79people, smart living, and smart governance. It is defined as being “smart when investments in human and social capital and80traditional (transport) and modern (ICT) communication infrastructure fuel sustainable economic development and a high quality of81life, with a wise management of natural resources, through participatory governance” [27]. The smart city concept can be82distinguished from other similar ideas such as the digital city or intelligent city in that it focuses on factors such as human capital83and education as drivers of urban growth, rather than singling out the role of ICT infrastructure.84Since the term ‘ubiquitous’ in this context is derived from ‘ubiquitous computing’ [82], various definitions of Ubiquitous City85have been put forward by previous studies, in conjunction with terminology associated with the smart city concept. An ‘early86stage’ smart city can be defined as one that provides combined services via integration of IT and construction industries [37];87while highly advanced future cities will apply IT infrastructure and associated technologies and services to multiple components88of itself. Lee et al. [49] define a smart city in terms of the convergence of IT services within an urban space, such that the city's89citizens may access smart services regardless of time or place. This will enhance the city's competitiveness and its citizens' quality90of life. The Korean Ministry of Land, Transportation & Maritime Affairs have proposed a more technically-oriented definition [57],91as a city that is managed by a network and which supplies its citizens with services and content via the network using both fixed92and mobile smart city infrastructure, based on high-performance ICT. In summary, a smart city provides its citizens with services93via its infrastructure based on ICT technologies. This definition highlights the importance of identifying and planning for future94technologies that may serve future city demands, since it is almost certain that the smart city industry will grow. In this way,95evolving smart city technology is a fundamental component of the infrastructure underpinning the delivery of smart city services.96Additionally, other countries such as the U.S., Europe and Japan are also driving R&D initiatives and implementing smart city97technologies and applications, with the primarily aim of addressing current urban problems such as energy shortages, traffic98congestion, inadequate and poor urban infrastructure, health and education. In particular, the European Union (EU) is investing in99efforts to put in place smart city strategies for metropolitan city regions such as Barcelona, Amsterdam, Berlin, Manchester,100Edinburgh and Bath [58]. Other international cities such as Dubai, Singapore, San Francisco, London and Hong Kong are also101following a similar approach, aiming to improve quality of life for citizens and economic growth for industries within the city [49].
1022.2. Technology roadmapping
103Although there are various definitions of TRM, technology roadmaps may be also be defined with reference to the roadmapping104process—the set of activities required to develop a roadmap. Roadmapping has been described as a process that contributes to the105integration of business and technology, facilitating the formulation of both short- and long-term technology strategies based on the106interaction between products and technologies over time [28]. Other definitions of the roadmapping process describe it as a107demand-driven technology planning process serving market needs [19,22,32], a communication/knowledge management tool108supporting strategic decision-making [83] and as a collective approach to developing a strategy in which the integration of109science/technological considerations represents a valuable input into product and business planning [26]. In summary,
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110roadmapping is a rational methodology for seeking agreement when selecting technologies supporting organizational goals,111and a framework that may be used for establishing and adjusting technology development time lines.112The roadmapping literature suggests that the process broadly consists of three different phases: preliminary activity,113development of the TRM, and follow-up activity (Garcia and Bray [22] and Strauss et al. [75]). Appendix A includes a comparison114of different models from the literature, comprising process phases and activities. Notable examples of research and practice115relating to roadmapping at the sectorial and national level include the work of Industry Canada [30], the U.S. Department of116Energy [77], and Lee et al. [48]. Over a period of more than a decade, Industry Canada supported the development of roadmaps for117key industrial sectors, including energy, aerospace, textiles, printing, logistics and intelligent buildings. The Industry Canada [30]118approach highlights the importance of establishing a Steering Committee in the early stages of undertaking any roadmapping119initiative, in order to clarify the roles and responsibilities of organizations involved in the process. It is recommended that the120head of this committee be an expert on the roadmapping process itself rather than on the technology or industry being121roadmapped. The process developed by the U.S. Department of Energy is similar to that of Industry Canada, but places a greater122emphasis on technology assessment [77]. Lee et al. [48] build on this work by proposing a six stage roadmapping process for123national level R&D roadmap development and applied demand analysis, environment analysis, technical assessment, portfolio124analysis and prioritization, all envisioning the development of a more detailed and systematic TRM.125There have been many attempts to use various techniques in conjunction with the roadmapping process in order to enhance126or improve the method. What many such techniques have in common is their concern to improve decisions made about which127technologies should receive development priority. For instance, techniques such as AHP—the Analytic Hierarchy Process [16,26]128and portfolio analysis [54] have been introduced into roadmapping processes, while QFD (Quality Function Deployment) and129GRID (decision matrix) analysis have been applied to identify relationships between markets, products and technologies130[17,34,42,67]. Bhasin and Hayden [7] used gap analysis techniques to observe gaps between current and emerging technologies,131while Yasunaga and Yoon [84] and Suh and Park [76] deploy patent map/analysis techniques to estimate the status of emerging132technologies (or level of development) and trends. Cheong [9] has proposed the integration of TRIZ and Six-sigma methods with133roadmapping to generate new ideas for new product development under certain quality standards.134Research and practice have led to extension of the scope of roadmapping beyond the traditional technology development and135R&D focus to other areas, influencing the whole organization [24,25,35]. Roadmapping techniques can be customized to fit136specific contexts and objectives and/or to accommodate uncertainty associated with emerging technologies. Depending on the137roadmapping purpose, the degree of roadmap customization required is an important factor in evaluating the trade-off between138generalization/standardization that is critical for effective roadmap usage, taking into account user satisfaction [47].139The focus of the research described in this paper is on how the roadmapping method can be used to develop mid- to long-term140strategic planning for smart city development. In these terms, the paper will consider how services, devices (infrastructure) and141technologies can be incorporated into a roadmap in order to make available different types of smart services for citizens of the142city. An integrated roadmapping process is proposed in Section 3, guiding the development of smart city strategy.
1432.3. Quality Function Deployment in roadmapping process
144Quality Function Deployment (QFD) is a management innovation tool based on a matrix approach to mapping customer145requirements and engineering attributes of products [1]. It has been widely used as a communication tool for cross-functional146teams (e.g. manufacturing and marketing) in order to establish relationships and trade-offs in a simplified quantitative form. QFD147has been identified for roughly the last fifteen years as providing a reliable approach for linking the different layers of roadmaps148(e.g. in product-technology roadmapping). Groenveld [28] and Phaal et al. [65] suggest that different roadmap layers can be149coordinated with QFD through cross-functional collaboration to determine which product features should be given development150priority on the basis of customer-orientation. Lee and Lee [42] capture consumer preferences using QFD, applying these to a151roadmapping process in power line communication. An et al. [2] have also proposed an integrated approach that mediates152between products and services for a mobile communication company. These authors suggest modifying QFD by describing a153relationship between different product characteristics and customer needs and, further, by clarifying the relationship between154different service characteristics. Lastly, they represent relationships between product and service characteristics in the form of a155‘House of Quality’ QFD cross-impact matrix. This research has followed An's lead in adopting QFD as a coordinating tool to156determine relationships (of priority and otherwise) between different roadmap layers in smart city strategic planning.
1573. Design of an integrated service-device-technology roadmap
1583.1. Case background
159The smart city R&D project was initiated as one of 10 value creators (the so-called VC-10) by the Korean Ministry of160Construction and Transport in 2007. A dedicated government agency for promoting smart city projects was established to pursue161R&D on related issues, including strategy development and the elaboration of a vision for future smart city space and service162development. The agency also took on smart city infrastructure technology development, eco-technology development for the163smart city, and test-bed implementation. This substantial R&D program, with a budget of 490 billion won ($422 million) and164more than 1000 researchers participating in the project between 2008 and 2013. The scale of this initiative demonstrates the165degree to which smart city initiatives in Korea have the backing of government, at both national and local levels, with 36 local
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166government bodies (in 52 districts) backing the program, with advanced cities such as Hwaseong in Dongtan district, Woonjeong167in Paju, Inchon Chungla and Songdo currently developing integral smart city architectures. Of these, Songdo in Inchon district is168the largest smart city development project, due for completion in 2015. The various city developments provide a number of smart169technology-based services relating to health, traffic, parking and crime prevention, enabled by radio-frequency identification170(RFID) and wireless network technologies.
1713.2. Integrated service-device-technology (SDT) roadmapping process
172The purpose of this paper is to outline an integrated roadmap framework to support strategic planning for R&D initiatives for smart173city development. Other researchers have proposed roadmapping frameworks that are relevant to this kind of initiative. Phaal et al. [65]174generalize a TRM framework/architecture with three broadly different types of layers ranged from those at the top, relating to purpose175and format, to those at the bottom, relating to resources such as organization and the specific technology/competences/knowledge that176underpin given projects. The middle layer of the framework relates to forms of product or service development that deploy technology177tomeet market and customer needs, connecting the top and bottom layers. More specifically, An et al. [2] have developed an integrated178product-service roadmap supporting interdisciplinary research on mobile communications linking manufacturers and service179providers. Lichtenthaler [50] provide an integrated form of product-technology roadmap facilitating open innovation processes capable180of accessing and exploiting external technologies.181Based on a review of this integrated roadmap literature, three different critical factors for designing the roadmapping process182were identified.183Firstly, the roadmapping process needed to rest on a systematic classification of service-device-technology in a smart city184context. Furthermore, possible roadmap types needed to be established according to their purpose within a classification scheme185that enabled the selection of a type suitable to particular smart city applications. In general, technology roadmaps are structured186along two dimensions, representing a system of layers and sub-layers against a time frame [65]. Roadmaps need to be able to187represent and support product planning, the object of the most common type of TRM, to coordinate service/capability provision188and the delivery of smart city services through devices enabled by emerging technology. In this paper, the vertical axis of the189roadmap is more critical than the time dimension, as this provides a common language and structure for the whole program.190Thus, initial roadmapping efforts were focused on the definition of layers and sub-layers based on a systematic classification of191smart city services, devices and technology. Since these three layers are interrelated with each other, it was necessary to define192each layer according to a detailed classification.193Secondly, the research required the development of appropriate templates for use in the integrated roadmap. Since the194roadmap serves as a visualization tool supporting communication between different interested groups, it is desirable for195roadmaps to be structured in a common format, within which multiple layers are arranged to facilitate effective new services,196device and technology development and service introduction.197Thirdly, the proposed roadmapping process needs to provide a systematic way to maintain and update roadmaps, as has been198suggested by other TRM studies [43,44,65]. This requires continuous efforts to build a database of smart city service/device/technology.199It is essential to keep updating information in the database at a frequency relevant to the most rapidly evolving service or device200parameters.201The development of a classification system of topics and themes is a critical step in developing a roadmap, as emphasized by202previous research [15,48,54,68,69]. Additionally, a government-driven initiative such as this tends to need a systematic policy for203planning technical task assignment and development work [33]. Therefore, the first requirement in drawing up a roadmap is the204crafting of an identification process of the various services generally applicable across the entire scope of smart city development.
2053.3. Design of a roadmapping development process
206Structured methods for developing roadmaps have been proposed by previous research, which can be classified into three parts:207preliminary activity, development of the TRM, and follow-up activities [22,75]. For this research these were further subdivided into208detailed steps and activities relevant to smart city development and the three domains of services, devices and technology,209summarized in Table 1. Each of the 8 phases is described below, and subsequently illustrated with reference to a detailed case study.
2103.3.1. Planning phase211The vision and objectives associated with mid- and long-term strategies are set during the planning phase, identifying the212characteristics needed to support smart city development. In addition, planning has to define the Critical Success Factors (CSFs) of213the roadmapping process in relation to the overall intended outcome and structure of the roadmap. In this phase, a task force214team that will be ultimately responsible for the creation of the roadmap is formed, together with a working group providing215support for the roadmap drafting stage.
2163.3.1.1. Step 1: Setting the vision and goals for the development of mid- to long-term strategies. In order to develop mid- to long-term217strategies for a smart city, the future configurations of the city need to be anticipated, and the principal direction and goals of218developing the smart city framed. For this purpose, a literature review of studies of existing city developments was undertaken,219supported with expert interviews. This review generated six different smart city visions: ‘a convenient city’, ‘a safe city’, ‘a220comfortable city’, ‘a cultural city’, ‘a productive city’, and ‘a city open for participation’. These visions can be accomplished by
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221improving the efficiency and effectiveness of existing services, and/or by providing and developing new services in response to222civic demand [57]. Thus, it was decided to establish a mid- to long-term strategy that placed a greater weight on market demand223(user requirements), rather than technology/production capability [48].
2243.3.1.2. Step 2: Definition of the roadmap. This step involved clarification of the objectives of developing the roadmap whilst225determining its limits and scope. As Lopez-Ortega et al. [52] have pointed out, organizations behind the roadmap need to226determine the role that technology will play in fulfilling their business vision, which sets the context for creating a roadmap,227establishing alignment between the smart city vision and available and emerging technological resources.228The framing of these definitions should lead to the establishment of a development timetable for all aspects of the roadmap,229including preparation and systematic preliminary processing. For the smart city integrated roadmap three development themes230received further focus. The first objective was to identify and verify the R&D topics to be passed on to the ‘national level of smart city231development strategy’, which in turn aims to realize a high-end city that can keep pace with an ever changing technical and service232environment. The roadmap's second objective was to provide a strategic direction for carrying out the program in light of the likely233redundancy of tasks in the smart city development program driven by the government. The final objective was to support the Project234Management Office controlling and managing the program with respect to monitoring and assessing the current status of service/235device/technologies and their future potential. Based on these themes, 8 different roadmap development objectives were identified.236Of these objectives, ‘suggestion of optimal integration of the service/devices/technologies’was the most critical for the development237team due to the complexity of interdependency relationships between the three different layers.
2383.3.1.3. Step 3. Identifying CSFs for the roadmap development. In this stage, the critical success factors were derived after conducting239interviews with experts with experience in the development of roadmaps and with senior researchers in the smart city project240team. Since the complexity of the integrated roadmap is high, ‘effective roadmapping process’, ‘reflection of customer demand’241and ‘continued improvement and adjustment’ were ranked as being the most important for the roadmap development.
Table 1t1:1
t1:2 A Technology roadmapping process for smart city development.
t1:3 Preliminary activity Phase 1. Planningt1:4 Step 1. Smart city mid- to long-term vision and goals identified
Step 2. Definition of roadmapActivity 1. Individual objectives of the roadmapActivity 2. Setting roadmap boundaries and scopesActivity 3. Defining an individual time tableStep 3. Critical success factors for the roadmap consideredStep 4. Organization of the project teamActivity 1. Identify the party responsible for the development of the roadmapActivity 2. Form a working group
t1:5 Development activity of integrated roadmap Phase 2. Demand identificationt1:6 Step 1. Identify urban problems
Step 2. Infer demands and solutionst1:7 Phase3. Service identificationt1:8 Step 1. Smart city services classification
Activity 1. Set classification standardsActivity 2. List services (‘list-up’)Activity 3. Develop and verify service classification systemStep 2. Analysis of service trends (Delphi)
Activity 1. Set classification standardsActivity 2. List devices (‘List-up’)Activity 3. Develop and verify device classification systemStep 2. Analysis of device trends (Delphi)Phase 5. Technology identificationStep 1. Smart city technologies identificationActivity 1. Set classification standardsActivity 2. List technologies (‘List-up’)Activity 3. Establishment and verification of classification systemStep 2. Analysis of technical trends (Delphi)Phase6. Roadmap draftingStep 1. Develop roadmap formatsStep 2. Analyze interdependencies between service/device/technologyStep 3. Develop integrated roadmapPhase 7. Roadmap adjustmentStep 1. Roadmap adjustmentStep 2. Roadmap verification
Follow-up activity Phase 8. Follow-up stageStep 1. Development of execution planStep 2. Execution of plan
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2423.3.1.4. Step 4: Organizing the project team. The fourth step involved identification of a roadmap development team and undertaking243preliminary tasks before the Working Group was formed [17,52]. The development team is designed as a cooperating body between244project teammembers actually participating in smart city R&D projects. This is because all the characteristics of smart city evolution245point to the increasing combination and integration of various smart, technology-based service initiatives. It made sense, then, to246create a development team, together with its cooperating entities, out of project team members, as well as out of experts from247academia, industry and government agencies. The roadmap development team comprised 10 academic professors and 25 senior and248junior researchers in the fields of urban planning and development, and information systems. These researchers have their own249expertise, with a different focus, and provide a new impetus to the effort to converge technologies with services delivered in the250urban space. These scholars' ongoing empirical research is important in terms of supporting the roadmapping program, generating251process learning and continuous improvements and adjustments in the provision of technology-based services.252The expert group included urban experts, such as those from the main task research planning organization and from other253participating bodies in the smart city project. These were public officers from local government, academic scholars, engineers,254technical experts (GIS and ICT) and representatives from IT and communications service providers.
2553.3.2. Demand identification256Citizens place a wide variety of demands on technology-based services in modern cities, which were identified during this phase257of the project, with potential solutions proposed through the provision of smart city technology. This form of problem identification258served in turn as the basis for organizing services, devices and technology types relevant to the smart city of the future.
2593.3.2.1. Step 1: Identification of urban problems. ‘Problems’ in this context refer to the social obstacles and nuisances caused by the260city's structural imbalances. Kwon et al. [40] classifies urban problems into those concerning, respectively, housing/land,261transportation, environment/sanitation, parks and greenery, social development, disaster control, leisure/tourism development/262land rehabilitation, taxation, the development of the rural outskirts, population intensity in the metropolitan area and suburbs,263local development in relation to the location of shops and services and new town development. The author goes on to measure264the intensity of problems within each class [41,56].265In addition, Choi [13] attribute urban problems to reasons such as the shortage of public services, heavy traffic, inequality,266over-development, land shortages and crime. A total of 17 urban problems were identified in this study, categorized into six267different urban domains: housing/land (e.g. Low quality housing), transportation (e.g. Pollution and traffic accidents), disaster268control/safety (e.g. Natural disasters and man-made hazards), environment/energy (e.g. Deflection of fossil energy and269insufficient user information), urban landscapes (e.g. Insufficient support facilities for minorities) and civil participation270(e.g. Conflicts among individuals, areas, classes).
2713.3.2.2. Step 2: Proposing solutions for urban problems and defining smart city demands. Some of the urban problems introduced above272can be solved, or at least mitigated, by smart city developments, and the solutions outlined here are connected to the demands made273of the smart city by citizens. In line with this vision, interviews with 15 experts were conducted, from fields ranging from city274services to technology, taken from people involved in the groups drawn up in the planning phase and organization of the Project275Team. As a result, it was concluded that 14 out of 17 urban problems could be addressed and potentially resolved through smart city276technology. These demands were further narrowed down to 9 smart city demands such as sysmatic management/control of277environment pollution, efficient energy management, open environment for civic participation through a number of workshops.278These demand types provide a comprehensive view of how smart technologies can contribute to smart city development.
2793.3.3. Service identification280In this stage, the roadmapping process identified the services that smart cities will support, and collected information on these281services in a systematic manner through a service classification system. In addition, by monitoring trends in the development of282(and demand for) services, some preliminary work was carried out to underpin the designation and design of service layers in283later stages of the roadmapping process.
2843.3.3.1. Step 1: Smart city service classification. The services identified in this phase need to be classified properly in order to285promote a shared understanding of the nature of smart city services and of efficiencies that may be achieved through the project's286execution [29]. A robust classification helps local governments to develop services that address their own unique requirements.287For a smart city developer, the generic classification can be used as an indicator that helps to check the current status of smart city288services and to anticipate potential services that may be adopted later on. In addition, new services can be identified and289developed by exploring connections between services that have already been developed. In this regard, the intention is to290establish a classification system that sets out to minimize any difference in team workers' (crucially developers') conceptions of291the evolution of service models. This should in turn facilitate the development of systematic R&D projects.292Details of such activities include developing standards for the service classification, listing services and developing and verifying293the service classification system. The multi-dimensional service classification modes proposed in this research are shown in Table 2.294This form of multi-dimensional classification represents an effective alternative to ad hoc adaptations of a generic model in cases295where roadmapping has to accept the requirement of diverse classes and still hold together as a rational service model. In other296words, every smart service (for example, smart education, smart health and many other services) can be classified according to297various dimensions, which can be described as ‘entity of embodiment’, ‘applied space’, ‘spatial facilities’, ‘objective of embodiment’,
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298‘mode of embodied function’ and so on. With the strategic goal of developing a classification standard, this work performed nine299multi-dimensional analyses on 228 detailed service units. In these terms, services' Legal/Regulatory View, Space Factors, and Human300and Functional Elements are further broken down and shown in systematically classified form in Table 2. With the classification301standard created as described above, service lists were drawn up and expert groups (of ten participants) invited to verify them.302Table 3 shows some examples of service classification along with their definitions (to a degree consistent with confidentiality).303For instance, ‘U-Work Service’, as shown in Table 3, is defined as the creation of a virtual work space between remote workers and304their company that enables a safe and easily navigated working environment through web-based software applications. This service305can be categorized as ‘administration’ and used at a metropolitan scale, since its primary objective will be to achieve reductions in306carbon emissions and to cut transportation time. This service requires InformationMedia Facilities such as a SmartWorking Center near307train or subway stations or sited by a local community center. The servicewill also be open to general public to use, since the public will308be its main beneficiary. Within the classification scheme for featured elements, the objective of service is to support business activity309within the community. The service is defined as belonging to ‘work’ and as being grounded in a common human perspective.
3103.3.3.2. Step 2: Service trend analysis. A two-stage Delphi survey was conducted over a period of three months to identify current311and future trends in smart city services while fitting these into a rigorous classification (Table 4).312Since smart city services are very futuristic and cover a wide scope, it is only of limited use to gather information from ordinary313citizens, who are unlikely to have encountered or demanded such services yet, and indeed experts, who tend to be very specific in314their field of knowledge. This explains the rationale for selecting the Delphi survey, which is capable of gathering information315from a relatively large number of subjects, accumulating it, and finally allowing it to support objective decision making [46]. As316the surveyed service pools are large and complex in their different categories, 12 small groups were formed as a result of the317Delphi analysis. The survey was distributed to 320 people including local government civil servants, members of the Smart City318National Association and urban experts, from which 147 responses were collected, representing a 49% response rate.
3193.3.4. Device identification320A classification of device types has been made to collect related information and monitor the necessary progress in a more321systematic way, contributing to the device layer within the roadmap.
3223.3.4.1. Step1: Smart city device classification. In the smart city environment, multiple devices perform various functions that can be323recognized by the users in physical or virtual connections via the network. Therefore, in this study, if a function is performed by a324multiple number of devices grouped together, the devices are classed as a single unit. In addition, when using networks, it is325possible that a newly recognized device (actually, a group of devices connected together) may be spread over a wide range of326physical locations (i.e. urban spaces). To account for this, a space-oriented classification standard has been established, enabling a327clearer identification of these service device clusters. Such a classification system serves as preliminary groundwork for the328collection of device-related information and the monitoring of technological progress; it should eventually support a better329understanding of various devices used in smart cities through the systematic acquisition of information.330The first step for classifying devices is to set up a classification standard, which has been done in respect of space type,331infrastructure components and formal type. The definitions of these three standards and classifies as space-oriented standards332devices' space type (urban node, landmark, path, edge, district, metropolitan) and infrastructure components (ceiling, walls,333floors, complex, network), while under the heading of forms type it classes separate or independent, single devices (standalone334devices) and grouped/converged devices that work integrally in combination with the urban space. After setting up the
Table 2t2:1
t2:2 smartCity service classification standard.
t2:3 Category Sub-category Descriptions Types
t2:4 Service names Integrated services Name of mega service with multiple servicecomposition
N/A
t2:5 Single unit service Name of single unit service N/At2:6 Law standard Applicable service domains Domains are defined by Ubiquitous City
Construction LawAdministration, transportation, public health andmedicine, environment, crime prevention, facilitymanagement, education, culture and tourism,logistics, labour and employment, MISC
t2:7 Spatial elements Spatial unit Spatial which service can be supplied Metropolitan, city, district, facility, street, buildingt2:8 Spatial facility Spatial facility in which service are supplied Control tower, community centre, unit spatial
facility, fixed information facilityt2:9 Human perspective Embodying facility The service provider's entity Public, private, public and privatet2:10 Beneficiary Service beneficiary Public, citizens and corporations
Feature elements Embodiment objective Service objective Business support, life quality support,industry support
Human behaviour Types of service user's activity Living, working, moving, playing and cyberingFunctional embodimentmode
Supporting urban activity Common ground, specialization, potentiality
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335classification standards, the study identified those devices that already exist, in Korea or elsewhere, together with those likely to336be developed in the future to ensure they fit into the classification standards and wider typology. Ten experts from technological337fields were selected to verify the device classification system.338Table 5 shows an example of devices that are plausible to potentially combine with smart city services. For instance, ‘U-Booth’339is an interactive space for enabling various smart city services that can be positioned within an urban node or placed as a340landmark. This single device form will be located within an existed complex space infrastructure. Similarly, other smart devices341such as ‘Intelligent Bus Station’ and ‘U-Dome’were classified into this category. There are also converged forms of device that can342be combined with other infrastructure, such as wall, floor, path or edge space. For an instance ‘Info-Bench’ was recognized as a343single device that can be placed with floor and path space while ‘Intelligent Cross-Walk’ converged device form (i.e. multiple344devices) with floor element under path space.
3453.3.4.2. Step2: Device trend analysis. Similarly to technologically-based services, Delphi surveys were conducted for three months346to analyze the progress that devices were making towards availability. The survey was sent to 108 technical experts working in347smart city related departments of private corporations and 30 experts from the academic sector with a specialism in the smart348city field, receiving a total of 97 useful responses.349Previous studies have assessed the marketability, feasibility and development capability of devices in order to project larger350trends about device development [36]. In this study, the detailed information that would normally be contained in these351assessments was reorganized to suit the specific task requirements (Table 6), further adding as parameters Time to Availability,352Time before Application within the city is Ready, and the ‘plausibility’ associated with device development in order to anticipate353the likely timeframe of the actual application of the device in smart city networks.
3543.3.5. Technology identification355This stage entails the generation of a classification system into which technology-related data is systematically input and356verified as a preliminary task before the creation of the roadmap's technical layers.
3573.3.5.1. Step1: Smart city technology classification. The first requirement in technology classification was to draw up an overall358taxonomic system for the ICT technologies applicable to smart cities, and then to identify which technologies fitted into this359classification. For this study, a daily life environment was assumed where information would flow to users via a variety of devices360through smart infrastructure.361Baek [3] sets out a process in which users act on information delivered to them through smart networks in three stages:362Awareness, Decision, and Action [4]. This conceptual classification further suggests a subdivision of technical functions and roles363in sub-categories of Sensing, Networks, Processing, Interfaces, and Security, as shown in Table 7 [4,18,61,70,78]. At this stage364individual technologies that fitted in each category were identified on the basis of industrial data and existing literature.
Table 4t4:1
t4:2 smartService Assessment Index and definitions.
t4:3 Category Sub category Operational definition Evaluation scales
t4:4 Service measurement Service demand Expected demand from citizens and ability to resolveurban problems
5 level scale
t4:5 Business feasibility Expected economic profitst4:6 Importance Importance of service in connection to urban problemst4:7 Urgency of development Urgency of service development within cityt4:8 Commercialization Time before service will be available or commercialized
in the market for first-hand usest4:9 Innovative diffusion How service can be diffused with its expected impacts
within cityt4:10 Service anticipation Commercialization time Time before service will be available or commercialized
in the market for first-hand usagesYear
Applicable time for smartCity implementation Likely time for the service's becoming actually applicable tosmartCity in light of various circumstances, including regulation
Table 5t5:1
t5:2 smartCity device classification standard.
t5:3 Category Definitions Sub-category
t5:4 Space type The location where the device lies, or the range in whichthe devices can communicate with each other
t5:5 Infrastructure components The location where the devices are installed when connectedwith existing infrastructure
Ceiling, walls, floors, combined, network
t5:6 Formal type The number of the devices needed to perform their functionsor whether the devices are connected with other devices.
Single devices (standalone devices), grouped/convergeddevices that work integrally in combination
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365The smart city related technologies collected through the survey were divided into 12 sub-categories and 27 more detailed366groupings, to derive 114 technology factors. An expert group of 10 respondents further validated the adequacy of the technical367classification, confirming that the classification standard was accurate, and indicating any technologies that might be excluded368due to duplication or other reasons.
3693.3.5.2. Step2: Technology trend analysis. In order to establish the trend of technological development, a Delphi survey with ICT370technical experts from industrial, academic, R&D backgrounds was conducted over a period of three months. Participants371comprised 126 technical developers from private information or communication service providers, 100 experts from the372academic sector, and 50 researchers from governmental technical research institutes, resulting in 226 responses. The answers373provided to the survey focused heavily on questions of network and sensing technologies, accounting for 65% of the responses.374In the survey designed to help smart city planners anticipate mid-to-long term technology development, the focus was375principally on the importance of the technologies, the current stage of development, and future scope given likely future376innovation [14,20,59,62]. Therefore, technical assessment indexes were organized into categories for Importance, Current level,377and Future expectations, as shown in Table 8. Each category is further defined for detailed assessment, giving a total of 14 criteria378to measure using quantitative methods. In addition, similarly to the analysis of service and device trends, the expected time of
Table 6t6:1
t6:2 An example of smartCity device classification and a device definition matrix.
t6:3 Space type Infrastructure elements Device form Devices
t6:4 Urban node, Landmark Complex Single device U-Dome, U-Booth, Intelligent BusStation, Cave type Experienced Box
t6:5 path, Edge Ceiling Single device Sky-boardt6:6Converged (Roof) Roof-board
t6:7 Wall Single device Electronic boardt6:8Converged U-Signt6:9Info-boardt6:10Media Facade Ambient
InteractionFloor Single device Intelligent traffic light,
District Combined Converged U-playground, U-Eco Library,Artificial Island, U-Public space,
Metropolitan Network Single device Mobile device
Table 7t7:1
t7:2 smartCity Device Assessment Index and definitions.
t7:3 Category Sub category Operational definition Evaluation scales
t7:4 Device importance Marketability Overall assessment of current marketcompetitiveness of the device, as wellas future growth potential
5 level scale
t7:5 Consequential influence Overall assessment of the technical influenceof the device toward others and industrialand economic consequences
t7:6 Feasibility Expected economic profitst7:7 Economic soundness Soundness of the device application in city in
light of assessment of economic costst7:8 Utilization Extent of utilization of the devicet7:9 Device level Device maturity Device's stage of current development Introduction/Growth/Maturity/Fade outt7:10 Device productivity Availability of existing production facilities
for the device and likelihood of mass production(0~100)%
Device anticipation Time of availability Expected time to completion of developeddevice and of market availability
Year
Time of application Likely time for the device to become actuallyapplicable to smartCity in light of legal andother circumstances
Intensity of plausibility Measure of respondent's confidence inanswers about timing
5 level scale
Obstacles to introduction of the device Possible obstacles that might frustratedevice's application to smartCity
Lack of Core Technology/Immaturity of theIndustry/High Required Investment Volume
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379availability and smart city integration aspects were separated out, in order to factor in additional possible barriers associated with380regulatory, commercial or other non-technical reasons [11,12,20,31].
3813.3.6. Roadmap development382In the roadmap drafting stage, a first version of the roadmap was developed and using the data collected during the previous383steps that defined service, devices, and technology aspects.
3843.3.6.1. Step 1: Developing the roadmap format. In this step, a simple and easy-to-understand roadmap format (structure) was385developed. Service, device and technology perspectives were considered by the project team, including trends and associated386timescales. Based on this, the time horizon for the smart city roadmap was split up into three periods: the ‘near future (up to3872013)’, ‘a possible future (2014 to 2020)’, and the ‘far future (2021 and beyond)’. The ‘near future’ designates a relatively close388period of time for which it is possible to predict changes that will take place in infrastructures and related technologies with a389degree of confidence. A ‘possible future’ points to a future further away but not yet so far off that it has become impossible to390make predictions for it. The end of the ‘possible future’, that is 2020, marks the end-point of the time schedules of most national391development projects, providing an end point for smart city developments in practice. The ‘far future’ should not be taken to392imply an actual date, but rather an assumed point in time when all of the services and values embodied in smart city can be393realized without technical constraints, setting out a coherent vision for the system.394The vertical axis of the roadmap represents services, devices and technology as a set of layers and sub-layers, which form395separate aligned service, device and technology roadmaps. The direction of development for each individual service, device and396technology is depicted within this structure using the ‘bar’ format, one of the types identified by Phaal et al. [66]. A set of common397symbols was used to populate the roadmaps, described in Table 9 and explained below.398The beginning point on the bar-shaped arrows denotes the time of inception for the development of the service, device or399technology in question. The time of availability and time of application are marked with triangular icons. ‘Time of availability’400refers to the moment in which the subject becomes commercially available. Even after successful commercialization, however,401legal and regulatory issues, as well as issues to do with standardization, may lead to a delay in actual deployment within the smart402city, and hence these notional times are distinguished. The current maturity of the service, device or technology is marked as403‘Introduction’, ‘Growth’, ‘Maturity’ and ‘Fade Out’ based on a life-cycle perspective, and the production capability of the device and404current domestic technical proficiency are indicated.
4053.3.6.2. Step2: Interdependency analysis. Previous phases involved separate information-gathering processes for service, device and406technology aspects of the smart city system. However, with this information being compiled from different sources it can be407challenging to define with confidence the kind of devices smart cities require, and indeed the services than can be provided via408such devices. Nor is it easy to decide what kind of technology is necessary to realize a service and deliver it to users. To solve this409problem, this research has incorporated a version of the quality function deployment (QFD), as described in Section 2.3. The410characteristics of this method are defined in a number of publications [2,28,34,65] where QFD follows a ‘Market Oriented411Approach’ and is also useful in capturing and expressing interdependencies between the layers of a roadmap.412The above characteristics indicate the congruence of QFD with the aims of this step, namely to systematically identify the413service/device/technology capable of satisfying citizens' needs in part through understanding the interdependencies between414these, and bearing in mind that countless services/devices/technologies may exist at different times and in different locations. The415implication of this multiplicity of factors is that the importance of different factors (devices/services/technologies) changes over416time, as do relationships between devices, services and technologies. Thus, the first step was to establish a database with the417information collected, and then to identify forms of interdependency before the QFD approach could be applied. Previous studies418making use of QFD in roadmapping [34,65] have tended not to make a clear distinction between products and services. As a result,419they are unable to present a methodology for QFD that is capable of simultaneously analyzing customer demands and possible420products and services except An et al. [2]. They have proposed that products and services can be imagined as existing on a similar421‘level’, suggesting a modified method of QFD able to identify relationships between customer demands, products and services.422As a first step, a preliminary QFD analysis was performed to identify key interdependencies between smart city demands and423devices/services as shown in Fig. 1. The total scores of ‘Demand-Device/Service Inter-relationship’ are listed for both device (from424‘Mobile Devices’ to ‘Intelligent Bus Station’) and service (from ‘Home Automation Service’ to ‘Integrated Pollution Control425Services’). ‘Intelligent Pole’ was ranked highest, followed by ‘Mobile Devices’ for smart device development under given ‘Smart426City Demands’, while ‘Integrated and Social Security Card’ was ranked highest as a service, followed by ‘Integrated Customer
t8:4 Sensing Monitor any external change of status and transmit collected data to process and respond to signals from sensorst8:5 Processing Process data from sensors according to an analysis leading to a rational decisiont8:6 Network Connect each device and user to support efficient communicationt8:7 Interface Convert the information that flows between devices or between users and devices into a more intelligible form (Graphical, Textural)t8:8 Security Control illegal access to information from users or facilities over the entire smart environment and protect personal privacy
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427Service’. Furthermore, the relationships between products and services are denoted as ‘*’ in the ‘House of Quality’ (i.e. the428roof-shaped triangular cross-impact matrix part of the QFD diagram in Fig. 1). ‘Home Automation Service’, ‘Integrated Social429Security Card’, ‘Public Transportation Info. Service’ and ‘Emergency Recovery Service’ are highly co-related and able to provide430these services with ‘Mobile Devices’ such as smart phones and tablet PCs while ‘Public Transportation Information Service’, which431shows a high co-relation, is provided through ‘Mobile Devices’, ‘Intelligent Traffic Lights’, ‘U-Booth’ and ‘Intelligent Bus Station’.432These relationships enable experts to the rank overall weightings for each device and service area.433Based on the overall weightings from Fig. 1, interdependency relationships between service/device and technology attributes434(sensing, network, interface and processing) were analyzed and the interrelationship scores between device/service and technology435were assessed. Fig. 2 shows that ‘OLED’ in interface, ‘Binary CDMA’ in network and ‘RFID’ in sensors are ranked with higher scores436based on the expert review. As a result, it was possible to identify the most important services and devices that are most capable of437meeting citizens' needs, and to determine how these might relate to existing or emerging technology through the QFD analysis.
4383.3.6.3. Step 3: Integrated development of the roadmap. This step involved integrating the roadmap format developed in Step 1 and439the representation of the interdependencies between services, devices and technologies from Step 2. These are combined in such440a way as to support an initial visualization of the collected data based on total priority (weighting). This area of service is441identified as being the most important from the QFD analysis, alongside the related devices and supporting technology. Next,442information for these items is conceptualized using the roadmap format.443An roadmap example, as shown in Fig. 3, is that of Public ‘Transportation Information Service’which can be delivered by a number of444devices such as ‘Mobile Devices’, ‘Intelligent Traffic Lights’, ‘U-Booth’ and ‘Intelligent Bus Stations’ that can be implemented by theend of4452012. ‘Intelligent Traffic Lights’ and ‘Intelligent Bus Stations’ have low levels of technological maturity (i.e. ‘Introduction’) compared to446the other two devices, which are interdependent on different technologies. OLED technology is already available (since before 2009),447yet needs to develop further for city implementation in 2020, while RFID and GPS have already reached the ‘Mature’ stage.
4483.3.7. Roadmap adjustment449This stage involves adjustment and verification of roadmap projections as they have been derived through previous stages of450the roadmapping process, with a view to improving objectivity and reliability.
4513.3.7.1. Step 1: Roadmap adjustment. In general, a roadmap contains information gathered from a number of different sources,452since predictions from experts in individual fields are not in themselves sufficient to anticipate and prepare for the future. For this453very reason, a process of repeated adjustment of the roadmap is necessary after the first version has been created in its complete454form [6]. In particular, it is very likely that roadmapping processes of the kind described in this study will be subject to error, not455least because of errors in the information compiled in the roadmap's assembly. Surveys of experts' and practitioners' predictions
Table 9t9:1
t9:2 smartCity technology assessment indexes.
t9:3 Category Sub category Operational definition Evaluation scales
t9:4 Technologyimportance
Marketability Overall assessment of the technology's current marketcompetitiveness and potential for future growth
Respondent's confidence about application timetableof technologyto smartCity
5 level scale
Obstacles to technology Possible obstacles for technology's application torelated industries
–Lack of core technology–Immaturity of the industry–High required investment volume
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456regarding services/devices/technologies do not generally yield a unanimous or unambiguous result, since the experts all have the457perspectives appropriate to their own fields and experience. The adjustment step aims to identify difficulties that have come to458light with the roadmap, refining and enriching roadmapping content though internal discussions and the addition of secondary459data. These adjusting steps improve the roadmap accuracy and credibility. Three different adjustment approaches are identified:4601) adjusting the roadmap with device and (or) technology determined by service; 2) adjusting the service roadmap due to461current technology limitations; and 3) all three layers adjusted based on inputs from both the integrated development team and462the expert group (Table 10 Q3).463An example of such an adjustment process is shown in Figs. 3–4, highlighting roadmap adjustments:For ‘Public Transportation464Information Service’ it was found that ‘intelligent traffic lights’ and ‘intelligent bus station’ devices need to extend to 2014 since465OLED technology, a primary technology for both devices, would be implemented within the city later than 2020 according to466Fig. 4. Again discussions and expert reviews concluded that OLED technology requires an adjustment on the time line not later467than 2014, where both devices can be extended to 2014. Overall, service development time has adjusted from 2011 to 2014. In468this case of adjustment three parties negotiated a change to multiple layers of the roadmap.
4693.3.7.2. Step 2: Verification of the integrated roadmap. According to Kostoff and Schaller [38], it is not possible to derive a definitive form470for the roadmap before it has been completed, even for those experts who drafted it. It is necessary rather to secure the help of outside471authorities if the map is to be credible. Hence, in this study, a verification process was added to the methodology, with the aim of472making the roadmapmore credible and valid, soliciting the involvement of both internal researchers and external experts in the field of473smart city services. A series of smart city workshops and open seminars were held during and after roadmap development to enable474wider participation and engagement, capturing and using feedback from this consultation to improve the quality of the roadmap.
4753.3.8. Follow-up stage476During this stage the roadmap is evaluated and an execution plan developed. Feasibility studies and a process/system for477continuous updating of the roadmap are also undertaken and put in place during this stage. In the case of the smart city project, the478expectation is that continued adjustments and enhancements of the TRM will be achieved though surveys and interviews with479experts, supported by input of secondary data from other research institutes and the media. This will serve the purpose of bringing
Fig. 1. Analysis of the interdependencies between service/device/technology.
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480together a consensus on the completed roadmap insofar as it ensures that the roadmap content is sufficiently accurate. The follow-up481stagewill also generate an integrated execution plan, based on the priority assessment carried out byQFD analysis. The aim is to assist482designers' decision-making processes in selecting technologies and developments to be pursued. Further, the information gathered at483the definitional stages of each areawill be retained and rationalized as a database allowing amore informed style ofmanagement and484better data sharing within the project teams. This recommendation of coordinated data is in line with Lee et al.'s study [44], which485pointed out ‘the establishment of [an] adequate software system’ as a key factor in roadmap utilization.
4864. Conclusions
4874.1. Lesson learned
488This paper has described the development of a smart city roadmap in Korea, placing particular emphasis on the underlying489classification system, the development of roadmap formats and database accumulation of the large volume of information related490to smart devices, technologies and services necessary to develop the roadmap. Through this case study, the following lessons have491been identified, which may be relevant to similar projects in the future.492Firstly, the developed roadmaps have provided the first comprehensive and unified view of current and future trends for smart city493development in Korea, since therewas noprior strategic guidance available. Each city has been developing their own services based on494current technologies without coherent strategic planningwhich requires a national level coordinating view. Therefore, the developed495roadmap serves an important strategic resource and communication tool to support smart city R&D initiatives in Korea (i.e. what is496possible in near future andwhat areas need to be developed in nationally or locally). In addition, the roadmap points to best practices497for other smart city developments, creating an integrated knowledge platform founded on technological trajectories.498Secondly, structuring the layers and time frames for smart city development was found to make an important contribution to499the overall program objectives. The multi-layered roadmaps, conceptualized through consultation with experts and stakeholders500within the project, provided an integrated architecture for the whole system, relating to the architecture of the smart city itself501(i.e. services-devices-technologies). Each layer has its own classification system, with sub-categories that supported the502identification of different and new services with potential devices and technologies. Through the roadmapping process, which503involved a series of workshops, in-depth interviews and surveys, the roadmapping process itself becomes a communication504platform enabling knowledge exchange within the large and extended project team, including service development, integrated505platform team, legislation and regulation policy team, and device-technology development team. Since the roadmap served as a
Fig. 2. Analysis of the interdependencies between service/device/technology.
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506long- and mid-term strategic planning framework for smart city development, the time frame was also critical, divided into three507time horizons (‘near future’, ‘mid-future’ and the ‘far future’).508Thirdly, one of challenges in developing the integrated roadmap was dealing with a large number of R&D researchers and other509stakeholders, to enable a comprehensive and broad view of smart city development for the roadmap. Sincemany different interested
History Short term Med term Long term Importance
Service
Device
Public Transportation Information Service
Application
Availability
A
E B
CD
Mobile Device
Application
Availability
A
E B
CD
Intelligent Traffic Lights
Application
Availability
A
E B
CD
U- Booth
Application
Availability
A
E B
CD
Intelligent Bus Station
Application
Availability
A
E B
CD
Fig. 3. Integrated roadmap for ‘public transportation information service’ (before adjustment).
15J.H. Lee et al. / Technological Forecasting & Social Change xxx (2012) xxx–xxx
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510groups needed to participate in order to project current and future trends, the roadmap for each layer (service-device-technology)511was individually developed in a parallel manner, whereas prior roadmapping approaches have generally been more sequential. For512instance, the service roadmap may be sequentially designed followed by mapping available technologies, which are limited to513customized devices and technologies, whereas this study focused rather on a generalization/standardization roadmap at the national514R&D level. In addition, the smart city context may be different, since certain services can be delivered by multiple devices (smart515phone, smart wall paper) with different technologies, and the roadmap development was a rather exploratory learning process.516Thesemaps are combined with adjustment through QFD analysis, as they are interdependent, coupled by demand-pull (service) and517technology-push (device-technology) views. Since many of the exploratory roadmaps were technology-driven the integrated518roadmap attempts to account for both views.519Fourthly, the roadmapping method was combined with other management techniques in order to strengthen the overall520process, and to engage with different stakeholders. The survey-based Delphi method was used for constructing three basic521roadmaps that offered grounded information for projecting current and future trends. The process was also distinctive in its522deployment of QFD within the roadmap adjustment phase to assess multiple possible forms of interdependency between523services, devices and technology. In using a modified form of QFD, the roadmap could clearly highlight important services and524devices that best matched service demands. This was a step further than existing studies, in not only suggesting modifications to525QFD, but in applying them in an actual implementation case.526Lastly, the roadmap content, as represented using the symbols shown in Table 9, provides a more realistic view from a527commercialization perspective. The roadmap accounts for detailed time frames described by ‘availability and ‘applicability’. The528former indicates commercialization whereas the latter accounts for regulatory and legal issues to project future deployment. This529identifies which regulation or policy may be acting as a bottleneck for service implementation, and enables a more realistic time530frame which accounts for exogenous variable such as social concerns (e.g. privacy) or security (e.g. RFID adoption creating privacy531problems although the technology is already available for implementation).
5324.2. Research limitations and future research
533The defined classification systems could be further developed, extended and validated with other experts in order to provide a534more holistic view of smart services, devices (infrastructure) and technologies. In order to test the applicability of the general535framework developed in this research, it would be useful to focus on a specific smart city development, creating a customized536roadmap and process to support alignment of the city's strategic objectives. The methods developed could be further enhanced by537combining other techniques such as patent and portfolio analysis, to improve data, analysis and decision-making quality. The538current project focused more on the communication benefits of the roadmapping process—in the future, building on the data539collected the emphasis could shift towards developing a knowledge management tool to support smart city initiatives in the
Table 10t10:1
t10:2 Service/Device/Technology layer formats.
Service Diagram Device Diagram Technology Diagram
Name Name Name
Time of
Availability
Time of
Availability
Time of
Availability
Time of
Application
Time of
Application
Time of
Application
Importance Importance Importance
Maturity Maturity Maturity
Service
CapabilityN/A
Production
Capability
Domestic
technical
level
against
Global
Introduction Growth Maturity Fade out Introduction Growth Maturity Fade out Introduction Growth Maturity Fade out
A
E
D C
BA: Feasibility
B: Demand
C: Importanc
D: Influence
E: Urgency
: 100%: 76% ∼ 99%
: 51% ∼ 75%: 26% ∼ 50%
: 0% ∼ 25%
: 100%: 76% ∼ 99%
: 51% ∼ 75%: 26% ∼ 50%
: 0% ∼ 25%
A
E
D C
BA: Marketability
B: Consequential Influence
C: Feasibility
D: Economic Soundness
E: Utilization
A
E
D C
B
A: Marketability
B: Consequential Influence
C: Feasibility
D: Economic Soundness
E: Utilization
Availability
Application
Availability
Application
Availability
Application
Unit Service Name Device Name Technology Name
16 J.H. Lee et al. / Technological Forecasting & Social Change xxx (2012) xxx–xxx
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540future. The development of a database in which to store various forms of information has the potential to facilitate the developed541new services along with technology and devices. The particular specification of the roadmapping process described in this paper542is expected not just to support ongoing smart city development but also to lend itself to applications in other technology-based543industries that need to both coordinate a vast scale of activities and to keep abreast of continual new developments.
Technology
Before 2008 2009 2010 2011 2012 2013 2014~2020 After 2020 Importance
A
E B
CD
Binary CDMA
Availability
Application
A
E B
CD
Touch Sensor
Application
Availability
A
E B
CD
RFID (Passive, Active Tag/Low & High Freq)
Application
Availability
A
E B
CD
GPS
Availability
Application
A
E B
CD
A
E B
CD
RFID/USN Security
Availability
Application
OLED
Availability
Application
Change
Fig. 4. Integrated roadmap for ‘public transportation information service’ (after adjustment).
17J.H. Lee et al. / Technological Forecasting & Social Change xxx (2012) xxx–xxx
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544As the smart city roadmap was constructed in a formal and systematic way, accumulating a large volume of data, software545based roadmapping tools could improve roadmap utilization. Such tools enable the reuse of roadmaps and also to capture,546maintain andmanage their data over time. The benefit of such a developed system could contribute to automated and customized547roadmapping processes and could play an important role in supporting knowledge management activities within distributed R&D548teams for smart city development.
549Acknowledgment
550This research was supported by a grant (code 07-High Tech-A01) from High Tech Urban Development Program funded by551Ministry of Land, Transportation and Maritime Affairs of the Korean government.
552Appendix A. Technology roadmapping processes
553Author (Year) Preliminary activity Development of TRM Follow-up activity
Kim and Park [34] 1.Roadmap framing 2.Roadmap creation1) Uncertain events recognition2) Influenced elements identification3) QFD adjustment4) Scenario roadmap creation
7. Formulation of adecision document8. Update
Phaal and Muller[67]
1. Ideation 2. Divergence3. Convergence
4. Synthesis
Daim and Oliver[15]
1. Survey of the organization'sgoals, strategies, and surveyof the sector
2. Develop and implement a training program3. Collect data and create the roadmaps
4. Review and ratify
Gerdsri et al. [25] 1. Initiation 2. Development 3. ImplementationYasunaga et al.[84]
1. Product range characterizationand thermal issue qualification,technology listing andcharacterization,fitting criteria and weightingfactor definition
2. Link between technologies andproduct thermal issues3. Idenfication of technical performance, cost,and technical risk in the application4. Creation of the TTR based on thermalperformance and technical availabilities in time
5. Follow-up activities
Lopez-Ortega et al.[52]
1. Selecting and characterizingthe technological destinies
2. Routes identification3. Technology roadmap construction
4. Technology roadmapscheduled updating
Eom et al. [19] 1. Making common sense 2. Development 3. Follow-up activityBhasin and Hayden[7]
4. Gap analysis5. Identify technology gap6. Development of the roadmap
Bruce and Fine [8] 1. Planning 2. Input and analysis3. Development of the roadmap
18 J.H. Lee et al. / Technological Forecasting & Social Change xxx (2012) xxx–xxx
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(continued)
Author (Year) Preliminary activity Development of TRM Follow-up activity
Fujii and Ikawa[21]
1. Deciding theme,Time-frame, Strategic factors
2. Workshop1) Identify market driven2) Determine the future vision3) Identify and determine product,function, technology, R&D process,resource4) Identify correlations
1. Collection of literature and data2. confirmation of experts list
3. First expert symposium for the trendof the technology and TRM framework4. Second expert symposium for designingtechnology roadmap5-1. Industry questionnaire investigation5-2. Academic research questionnaire investigation6. Third expert symposium to make clearindustry demandDraw TRM
7. Form report
Slabbert and Buys[72]
1. Identify stakeholdersand coordinating body2. Identify current statusof technology and market
3. Identify Vision for Future4. Identify barriers to market entry5. Identify strategic approaches to overcomebarriers6. Produce roadmap document
Suh and Park [76] 1. List of services2. Initial technologies of services3. Initial keywords of technologies
4. Construct a patent map5. Evaluate technology's priority using thepatent map6. Build up a service-oriented technology roadmap
Walsh [81] 1. Satisfy essential conditions2. Provide leadership/sponsorship3. Define the scope and boundaries
4. Identify the product that will be the focusof the roadmap5. Identify the critical system requirementsand their targets6. Specify the major technology areas7. Specify the technology drivers and their targets8. Identify technology alternatives and theirtime lines9. Recommend the technology alternatives thatshould be persuaded10.Create the technology roadmap report
11. Critique and validatethe technology roadmap12. Develop an implementationplan13. Review and update
Appendix (continued)
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658[78] K.Y. Um, M.S. Choi, Y.B. Eo, Y.S. Yoo, B.N. Lee, ICT roadmap case and use, Korea Society, Innov. Manag.& Econ. (2003).659[79] S. Vandermerwe, J. Rada, Servitization of business: adding value by adding services, Eur. Manag. J. 6 (1988) 315–324.660[80] S.L. Vargo, R.F. Lusch, Evolving to a new dominant logic for marketing, J. Mark. 68 (1) (2004) 1–17.661[81] S.T. Walsh, Roadmapping a disruptive technology: a case study: the emerging micro-systems and top-down nanosystems industry, Technol. Forecast. Soc.662Chang. 71 (2004) 161–185.663[82] M. Weiser, The Computer for the 21st Century, Scientific American, September 1991.664[83] R. Wells, R. Phaal, C.J.P. Farrukh, D. Probert, Technology roadmapping for a service organization, Res. Technol. Manage. (March-April 2004) 46–51.665[84] Y. Yasunaga, T. Yoon, Technology roadmapping with structuring knowledge and its advantages in R&D management, Int. Eng. Manage. Conf. (2004)666581–585.667668669Jung Hoon Lee is currently an associate professor at the Graduate School of Information, Yonsei University, Seoul, Korea and also visiting scholar at Stanford670Program on Regions of Innovation and Entrepreneurship (SPRIE) at Stanford Business School. He received his B.Eng./MSc. in Electronic Engineering/Information671Systems Engineering and MSc. in Information Systems from University of Manchester and London School of Economics respectively. He obtained his Ph.D. in672Manufacturing Engineering and Management from the Institute for Manufacturing, University of Cambridge. His current research interests include performance673management in technology management, technology roadmapping and forecasting and simulation modeling in technological innovation.
674Rob Phaal joined the Centre for Technology Management at the University of Cambridge in 1997, where he conducts research in strategic technology675management. Areas of interest include management processes, frameworks and tools, with a particular focus on technology roadmapping and evaluation. Rob has676a mechanical engineering background, with a doctorate in computational modelling and industrial experience in technical consulting, contract research and677software development.
678Sang Ho Lee is a professor at the Department of Urban Planning and Engineering and the chairman of lead Ubiquitous City Research Center at Hanbat University,679Korea. He has also been a project manager for R&D initiatives for U-City project which supported by Ministry of Land and Transport in Korea. Prior to join Hanbat680University, he has worked for SAMSUNG Group. Prof. Lee is also an executive board member of Knowledge City World Summit and currently served as an681international jury of Barcelona Smart City Award. Prof. Lee graduated from Yonsei University in Architecture Engineering then obtained his MSc/Ph.D. in Urban682Planning and Engineering from Yonsei.683684
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