知识管理系统

Knowledge management system for fourth generationR&D:KNOWVATION *Yongtae Park *,Seonwoo KimDepartment of Industrial Engineering,College of Engineering,Seoul National University (SNU),San 56-1,Shillim-Dong,Gwanak-Gu,Seoul 151-742,South KoreaAbstractSince the advent of the embryonic model almost a century ago,R&D systems have gone through an evolutionary process of development that can be classified into three generations.Today,the fourth generation of R&D is emerging that emphasizes both strategic and operational importance of knowledge management (KM).Despite the importance of KM,the network between conceptual scheme of the fourth generation R&D and practical system of KM remains a missing link.In response,the main objective of this paper is to present a framework for designing and implementing knowledge management system (KMS)for the fourth generation R&D.The proposed system is named KNOWVATION,which combines the notions of knowledge and innovation.First,the evolutionary classification of the R&D generations and the corresponding characteristics of the respective generations are defined.Second,the organizational structure and knowledge functions of the fourth generation R&D are derived.Finally,the overall design framework and detailed sub-modules are presented.q 2004Elsevier Ltd.All rights reserved.Keywords:Fourth generation R&D;Knowledge management;System;KNOWVATION;System design1.IntroductionSince the advent of the embryonic model almost a century ago,R&D systems have gradually and continuously evolved over time.Roughly speaking,this growth path can be classified into three generations,from the first generation to the third generation,in line with technology development and environmental change (Amidon,1996;Kerssens-Van et al.,1996;Rothwell,1994;Roussel et al.,1991;Tiwana,2000;Zack,1999).The longevity and traits of the first generation are clear.Starting from the beginning of the 20th century and lasting until the 1960s,the first generation paid little attention to the economic management of R&D,but gave free rein to science-based R&D labs,which acted as independent cost centers.Although it is rather difficult to make a precise demarcation between the second and third generations,the former is characterized by scientific and microscopicmanagement of R&D during the 1970–1980s,whereas the latter is delineated by the strategic and holistic management of R&D during the 1990s.Today,the fourth generation of R&D is emerging (Miller and Moriss,1999).The main objective of the fourth generation R&D systems is to identify the latent needs of prospective customers and secure the technical feasibility and marketability simultaneously in the very early stages.To this end,the modern R&D system magnifies the role of information technology (Barthes and Tacla,2002;Dennis et al.,1998)and also emphasizes the platform and architecture of the whole system.In this regard,knowledge management (KM)becomes an indispensable requisite of fourth generation R&D.KM is essential not only as an operational vehicle,but also as a systematic building block.Further,another version of this chronological taxonomy argues that this latest stage should be regarded as the fifth generation,rather than the fourth,in that the crucial asset is not the customer,but the knowledge (Amidon,1996).In fact,the R&D process can primarily be considered as a knowledge management process,because it transforms information on technological advancements and market demands into knowledge which can be used for developing new product0166-4972/$-see front matter q 2004Elsevier Ltd.All rights reserved.doi:10.1016/j.technovation.2004.10.008Technovation 26(2006)595–602/locate/technovation*It is confirmed that this item has not been published nor is currently being submitted elsewhere.*Corresponding author.Tel.:C 8228808358;fax:C 8228783511.E-mail address:parkyt@cybernet.snu.ac.kr (Y.Park).concepts and process designs(Kerssens-Van et al.,1996; Nieto,2002).Despite their intrinsically close relationship,the practical network between fourth generation R&D and KM has remained a missing link.In practice,the distinctive needs and characteristics of the fourth generation R&D still remain to be materialized in the form of an operational system or specialized knowledge management system (KMS).The pool of existing KMSs is abundant and each is useful in terms of its technical performance and operational efficiency.However,none of the existing commercial KMSs are R&D-specialized solutions,but rather are general-purpose solutions.They tend to focus on generic knowledge functions such as data registration, storage and retrieval.Recognizing the fact that the evolution into the fourth generation of R&D requires a restructuring of system architectures and a reorienting of system goals,the KMS for the fourth generation R&D must be tailored to the special-purpose needs of this new era.In response to this demand,the primary objective of this paper is to propose a framework for designing and implementing a KMS for the fourth generation R&D.The proposed system is named KNOWVATION.The term was coined by combining two crucial notions,knowledge and innovation.This paper is organized as follows.Firstly, based on a review of the literature,the major functions of a general-purpose KMS are identified.Secondly,the organ-izational structure and knowledge functions of fourth generation R&D are determined.Thirdly,we derive the requisite KMS functions by mapping the fourth generation R&D operations to the conventional organizational struc-ture.Finally,the overall framework and detailed sub-modules are described.One particular sub-module is described in detail for the purpose of illustration.2.Review of KM activities and KMS functionsIn essence,KM comprises two major pillars,KM activities and KMS functions.KM activities represent the process perspective of KM and are defined as those generic activities that enable the knowledge management process to be accomplished.On the other hand,KMS functions deal with the technology perspective and are defined as those functions that facilitate and/or supplement KM activities by providing specific and practical technologies and/or tools. Thus,even for the same KM activity,individual KMSs may differ from one another in terms of the conceptual design of the KM functions and the practical implementation of the KM tools.Thus far,a number of researchers have attempted to classify the major activities of KM.Among these,the most frequently cited work may well be that of Nonaka and Takeuchi(1995).These authors focused on the dynamics of knowledge activities and suggested that the four major activities of KM are socialization,externalization,combination and internalization.Despite its seminal contribution,this list of activities is too conceptual and even philosophical to be used in actual practice.Other versions are abundant.For instance,Tiwana(2000) suggested three fundamental activities;acquisition,sharing and utilization.Ruggles(1997)proposed such activities as generation,codification and transfer.Marquardt(1996) suggested four activities;acquisition,creation,utilization and storage.Wigg’s(1993)version consists of four activities:creation and sourcing,compilation and trans-formation,dissemination,and application and value realiz-ation.Van der Spek and Spijkervet(1996)proposed four activities:developing,securing,distributing and combining. Some other researchers presented more extensive frame-works consisting of six activities,namely acquire,select, internalize,use,generate and externalize(Holsapple and Joshi,2002),or eight activities,viz.identify,capture,select, store,share,apply,create and sell(Liebowitz and Beckman, 1998).In the current study,based on the review of the literature that we conducted,we suggest the following list of major knowledge activities:acquisition,organization, utilization,disposition and sharing.Table1shows the list of major KM activities and related sub-activities.As in the case of KM activities,previous research on KMS functions or tools is abundant.Generally,KMS functions are classified according to either the technology used or the method employed to support the KM activities. To name but a few,Tyndale(2002)derived16KMS functions from the main technological properties,Wensley (2000)focused on the application of web-based information Table1Knowledge activities and featuresMajor-activities Sub-activities FeaturesAcquisition Gathering Identification and capturefrom knowledge sources.Searching Need for intensivecommunication.Identifying Culture that accepts newideas.Organization Interpretation Identification of meaningfulknowledge.Filtering Valuefinding processes.Categorization Creation of insights,skillsand relationships. Utilization Contextualizing Knowledge recreation.Projecting Knowledge producingCompacting Value adding processes. Disposition Indexing Targeting knowledgeCollaboration Decision makingApplicationSharing Publishing Disseminating and makingavailable what is alreadyknownDissemination Collaboration andcollaborative supportTransmission Providing timely informationY.Park,S.Kim/Technovation26(2006)595–602 596technology to KMSs,in order to distinguish nine type of tools.Jackson(1999)reviewed59commercial KMSs and categorized them into six types,based on their size and the supporting method used for knowledge management.Zack (1999)segmented KMS system tools into integrative applications and interactive applications.Ricardo(2001) categorized KMSs into four kinds of tools.In addition,Park et al.(2003)proposed a classification scheme comprising six functions and/or tools.Based on our review of literature, we suggest the following KMS functions or tools:knowl-edge portal,document management system,information retrieval system,workflow management system,collabora-tive system and analysis system.Table2summarizes the major KMS functions and related sub-functions.Most of the research which has been done on knowledge activities was conducted by academics,whereas commercial KMS solutions were developed by practitioners.As a result, the link between KM activities and KMS functions is rather weak,if not inexistent.In an attempt to bridge this gap, Table3shows a guideline for linking knowledge activities and KMS functions.It describes the supporting-supported relationship between KMS functions and knowledge activities.This guideline can be used as a building block for designing and developing KMS.In particular,the proposed guideline provides some useful checkpoints for customizing the design of the KMS in accordance with the specific needs of organizations.That is,in order to customize the KMS design,an analysis of knowledge activities is carried out for the organization of interest,which allows the related KMS functions to be identified that support the respective activities.It should be noted, however,that there might exist multiple links between these two aspects of KM.That is,one particular activity may be supported by multiple KMS functions and vice versa. 3.The procedural structure of the knowledge management systemThe process of R&D has been studied extensively over the past30years and there are several general and/or empirical models.The definition of R&D process varies according to the objective of the research,such as the process itself(Utterback,1974),the success/failure of product development(Pinto and Mantel,1990),and the decision to terminate or continue an R&D project (Balachandra,1989;Pilar et al.,2004).In current research, KMSs are defined on the basis of Igal and Joel’s R&D process definition,which is composed of eight stages.Their research corresponds closely to the concept of fourth generation R&D,whose objective is platform development rather than product development,since it focuses on the process of hi-tech industrial product development.In addition,it suits the characteristics of KNOWVATION well,since innovation decisions are established stage-by-stage.Fig.1shows the KMS module based on Igal and Joel’s R&D process definition.The planning for market strategyTable2KMS FunctionsKMS Functions Sub-functions DescriptionKnowledge portal Integrated interface Personalization facilitiesLink management Set of information categoriesAnnotations Subsequent navigationInformation retrieval Search agents Obtained from search enginesUser profiling Used for searching and recalling dataVisualization Looking for both specific terms and related termsFinding expertsDocument management Finding documents Storefiles in a central libraryVersion control Control of access tofilesMetadata Management Changes in the managed documentsPermissions Management Search documents on either content or index termsEmulating paper/documentWorkflow management Process definition(Obtained from?)traditionalflowcharting toolsTask assignment Facilitating the work of a groupAuthority Delivering work items to appropriate usersManagement Invoking appropriate applications and utilitiesProcess modeling and managementCollaboration CoP*Setting up bulletin boardsChatting Real-time conferencing,whiteboards and chat rooms.Conferencing Vital to knowledge sharingMailingAnalysis User analysis(Obtained from?)information systemsMarket analysis(Complementary?)with information technologyKnowledge analysis Supporting decisionsCoP,Community of practice.Y.Park,S.Kim/Technovation26(2006)595–602597and technology strategy is supported by the industry and market analysis module.The generation of ideas for the dominant design module supports idea screening at the early stage and technology feasibility evaluation.The acquisition,organization and utilization of information and knowledge during the R&D process are supported by the project screening and monitoring module,the project scheduling and sourcing module and the research output and knowledge asset management module.The process management and document management modules support the disposition and sharing of information and knowledge.Finally,the commercialization and business-modeling module support business modeling process,including the development of the market strategy and subsequent commercialization.Business modeling as part of a comprehensive concept is required to launch a new product onto the market,since the objective of fourth generation R&D is to develop and satisfy the latent needs of the customers.4.KMS functions for fourth generation R&DAs mentioned,the KNOWVATION system is named after a combination of the words ‘Knowledge’and ‘Innovation’and is designed to cover eight modules referred to in the analysis of the R&D process.The guideline for linking knowledge activities and KMS functions provides the basic building block for designing the KMS.However,since the current study proposes an extended and customized KMS to support fourth generation R&D,it is necessary to diversify the range of functions,covering not only data processing,but also knowledge analysis and creation.As shown in Table 3,the existing KMS functions concentrate on the acquisition and sharing of knowledge.New KMS functions,therefore,should be added to implement the KNOWVATION system,which aims to include knowledge analysis and creation.To this end,we develop an overall matrix,comprising two major dimensions,namely the organizational dimen-sion and the operational dimension.As mentioned above,Table 3Linkage between Knowledge Activities and KMS Functions KMS functionsKnowledge activities AcquisitionOrganization UtilizationDispositionSharing PortalIntegrated interface †††Link management †††Annotations †††Information retrievalSearch agents ††User profiling ††Visualization †††Expert findings †††Document managementFinding documents †††Version control†††Metadata management ††††Permission management †††Workflow management Process definition †††Task assignment†††Authority management †††CollaborationCoP †Chatting ††Conferencing †††Mailing†††AnalysisUser analysis †††Market analysis †††Knowledge analysis†††Fig.1.KNOWVATION modules and innovation process.Y.Park,S.Kim /Technovation 26(2006)595–602598all of the organizations and capabilities of afirm should participate in R&D from the very early stages.Hence,the organizational dimension is defined in general terms comprising the entire organization of thefirm in question. However,the dimensions can be subdivided and modified depending on the features of the organization used for the implementation.The organizational dimension accounts for the principal management organizations in a corporation and includes the followingfive divisions:the strategy division, R&D division,finance division,production division and marketing division.The operational dimension includes the structural module of the KNOWVATION system,but excludes the document management and process manage-ment modules.These two modules are excluded due to their irrelevance to knowledge analysis and creation.By combining these two dimensions,organizational and operational dimensions,the overall matrix is developed,as shown in Table4.Note that the matrix may encompass numerous possible cells and that the matrix mainly focuses on analysis and creation.The development process and decision criteria for customized KM are subjective andfirm-specific.5.Overall system of KNOWVATIONBased on the matrix and conventional KMS functions, the KNOWVATION system is designed to cover the eight modules and25related KM functions which can support knowledge analysis and creation.Table5shows the list of modules and functions.These25newly proposed functions could be connected with general information systems such as groupware as well as with conventional KMSs.Not all of the25functions have to be used,but they are available as the building blocks,which can be used for constructing knowledge management system.A range of KNOWVA-TION types can be constructed depending on thefirm being investigated and the characteristics of the industry to which thefirm belongs.6.System design methodology for KNOWVATIONThere exist a number of system design methodologies, including the Generic Tasks approach,the Problem Solving Methods approach and the CommonKADS methodologies. Among these,we opted for CommonKADS as the basic methodology to implement KNOWVATION,because it has some superior features compared to the others.It is well documented and some support tools exist.In addition, CommonKADS implements many of the best features of the other knowledge level specification methodologies (Allsopp et al.,2002).CommonKADS is a methodology for the development of knowledge based systems,which is the result of the Esprit-IITable4KM requirements for fourth generation R&Da.Strategy division R&D division Finance division Production division Marketing divisionIndustry and market analysis Industry analysis Technology position Finance structure Resource analysis CompetitionstructureIdea generation fordominant designTechnology trend Technology opportunity Production value Needs analysisProject screening and monitoring Project selection Technology fusion Success/failureanalysisProject scheduling andsourcingProduct portfolio Technology outsourcing Technology roadmapResearch output/knowledge assetPatent map Industry standard Marketability testCommercialization/ business modeling TechnologyvaluationCashflow prediction Production efficiencytestCompetitor analysisTable5KNOWVATION module and KMS functionsMajor modules FunctionsIndustry and market analysis Industry analysisTechnology positionFinance structureResource analysisCompetition structureIdea generation for dominant design Technology trendTechnology opportunityProduction valueNeeds analysisProject screening and monitoring Project selectionTechnology fusionSuccess/failure analysisProject scheduling and sourcing Project portfolioTechnology outsourcingTechnology roadmapResearch output and knowledgeassetPatent mapIndustry standard managementMarketability testCommercialization and businessmodelingTechnology valuationCashflow predictionProduction efficiency testCompetitor analysisProcess management Workflow analysisDocument management Knowledge sharing with securityOutput managementY.Park,S.Kim/Technovation26(2006)595–602599project (P5248)monKADS supports most aspects of knowledge-based system (KBS)development projects,including project management,organizational analysis,knowledge acquisition,conceptual modeling,user interaction,system integration and design.It describes KBS development from two perspectives:the result perspective and the project management perspec-tive.The former is a set of models of different aspects of the KBS and its environment that are continuously improved during the project life-cycle.The latter is a risk-driven generic spiral life-cycle model that can be configured into a process adapted to the particular monKADS consists of four main models,the task model,communi-cation model,agent model and knowledge model.In spite of its wide usefulness,CommonKADS needs to be modified for KNOWVATION,which is a KMS specialized in R&D.The principal interest of current research is to identify those specific and specialized functions of the KMS that can be linked to R&D.The modified design framework for KNOWVATION,which is based on CommonKADS,is shown in Table 6.This framework shows the overall aspects,but is not intended to describe the detailed process at the bottom level.The framework consists of two parts,definition and structure.The former part includes the basic definition of each function and delineates the critical factors.The latter part shows the required resources and actors.In addition,it also defines the providers and end-users of the knowledgeand information,and shows the processes of knowledge utilization.Consequently,it is possible to trace out every process during which specific knowledge is generated,codified and transferred7.Illustrative function:project portfolio monitoring The project screening and monitoring module which can support strategic R&D management is employed for the purpose of illustration.Project Portfolio Monitoring (PPM)is a function of the project screening and monitoring module.It observes the whole project at the macro level and supports decision-making activities,such as efficient resource allocation and selected focusing.Table 7describes the PPM function.As a knowledge provider,the project manager inputs information on the proposal or progress of a project.The strategy team retrieves information,which helps to make a decision.The project information is analyzed on the basis of environmental information and previous best practice.The results of the analysis are then handed to the decision makers,after being processed in the system in such a way as to facilitate the decision.It is necessary to produce various types of portfolio,since it decision makers,such as the CEO and CTO,may need to analyze from various points of view during the R&D process.A project is characterized by the four mainTable 6Framework for KNOWVATION designSpecificationDefinitionFunction definitionDescription General function descriptionCritical factor Process Critical factors for process performance OutputCritical factors for output Function structureInput Input knowledge Required knowledgeKnowledge provider Person or division that is a provider not an owner Process ResourceRequired resources or expected input knowledge Knowledge creator Person/division that executes process OutputOutput knowledge Outcome of processKnowledge form Form of output knowledgeDecision-makerPerson/division that uses output knowledge to make a decisionTable 7Project Portfolio Management functionSpecificationDefinitionFunction definitionDescription Project analysis and evaluation at macro level,hence supports decision-making Critical factor Process Firm’s capacity analysis,OutputThe quality of the project profile and the number of dimensions of the portfolio Function structureInput Input knowledge Project profileKnowledge provider Each project managerProcess ResourceEnvironmental information,previous best practice Knowledge creator Strategy team OutputOutput knowledge Project portfolioKnowledge form Visual maps such as pie-charts,histograms,matrices and tableaux Decision-makerCTO,CEOY.Park,S.Kim /Technovation 26(2006)595–602600dimensions of time,size,actors and subject.The sub-dimensions and operational definitions of each dimension are summarized in Table 8.The PPM function supplies various diagrams,tables and matrices,which adopt the dimensions shown in Table 8for the purpose of supporting the four types of decision making.These are referred to as resource allocation,technology development policy,project magnitude and portfolio possibilities,Theoretically,the number of combinations of 10dimensions is more than the number of combinations in the matrix shown in Fig.2,however,only those combi-nations that are useful for making a strategic decision are adopted.After being analyzed by the strategy team,the project portfolio information is handed to the decision makers in the form of the table and matrix shown on the right-hand side of Fig.2.The proposed figures on the right-hand side show the relationship between the cost of R&Dspent to support decisions on resource allocation and the importance of technology.The decision makers can make use of these matrices and tables,which show the relationship between the field and newness of the technology,on the one hand,and the R&D cost and manpower on the other hand.8.Concluding remarksIn this study,we proposed a framework for designing and implementing a KMS for the fourth generation R&D.The proposed system first specifies the R&D process based on a review of the NPD process and innovation process.The major modules of the KNOWVATION system are defined for the purpose of supporting the R&D process.To cover knowledge creation and analysis,the KM requirements are developed using an organizational structure and appropriateTable 8Dimensions of Portfolio Major dimension Sub-dimensionOperational definitionTime Length of project Duration of R&D projectTime-to-completion Time remaining until completion of project Size Cost of R&DTotal expenditure of projectManpower of R&D Number of participating researchers Actor Mode of R&DMode of conducting projectDepartment of R&D Research unit conducting project SubjectField of technology Characteristic of research area Newness of technology Status in lifecycle of technologyImportance of technology Relative importance of technology for the organizationDifficulty of technologyDegree of developmentdifficultyFig.2.The Project Portfolio Management function.Y.Park,S.Kim /Technovation 26(2006)595–602601system modules.Then,the major modules and related KMS functions are identified.Finally,the framework for the system design is presented.The proposed system defines the whole R&D process, from the early R&D stage to thefinal commercialization stage,and comprises functions which facilitate activities at each stage and,supports the participation of all of the actors in the process of R&D and knowledge creation.Also,the KMS can be customized by combining different modules and functions,in accordance with the features of the specific firm being investigated,owing to the hierarchy of modules and functions.The current study is rather exploratory in nature,since it attempts to bridge the gap between generic KMSs and the specific needs of R&D.Consequently,despite its meaningful contribution,some discrepancies and missing links still remain that need to be extended and elaborated on in the future.Although the existing KMS functions are enlarged upon here,its integration with existing IT systems such as groupware is not taken into account. This study is also subject to limitation in that the framework focuses only on the macro level.In order to develop a more detailed process at the micro level,a more sophisticated design tool may be required,such as IDEF methodology.These tasks account for the research themes of future research.AcknowledgementsThis research was funded by the National Research Lab (NRL)program of the Ministry of Science and Technology of Korea.ReferencesAllsopp,D.J.,Harrison,A.,Sheppard,C.,2002.A database for reusable CommonKADS agent specification components.Knowledge-Base System15,275–283.Amidon,D.,1996.The challenge offifth generation R&D.Research Technology Management39(4),33–41.Balachandra,R.,1989.Early Winning Signals for R&D Projects.Lexington Books,Boston.Barthes,J.,Tacla, C.,2002.Agent-supported portals and knowledge management in complex R&D puters in Industry48,3–16. Dennis,R.,Flavin,P.,Davies,G.,1998.Online R&D management:the way forward.R&D Management28(1),27–35.Holsapple,C.W.,Joshi,K.D.,2002.Knowledge manipulation activities: results of a Delphi rmation&Management39(6),477–490. Jackson, C.,1999.Process to Product-Creating Tools for Knowledge Management Proceedings of Conference in Lisbon.Kerssens-Van,D.I.,Weerd-Nederhof,P.,Fisscher,O.,1996.Describing the issues of knowledge management in R&D:towards a communication and analysis tool.R&D Management26(3),213–230.Liebowitz,J.,Beckman,T.,1998.Knowledge Organizations:What Every Manager Should Know.St Lucie Press,Boca Raton.Marquardt,M.,1996.Building the Learning Organization.McGraw Hill, New York.Miller,W.L.,Moriss,L.,1999.Fourth Generation R&D.Wiley,New York. Nieto,M.,2002.From R&D management to knowledge management:an overview of studies on innovation management.Technological Forecasting and Social Change70(2),135–161.Nonaka,I.,Takeuchi,H.,1995.The Knowledge-Creating Company.Oxford University Press,New York.Park,Y.,Choi,C.,Kim,S.,2003.On the Linkage Between Knowledge Activities and Knowledge Management System Functions,Proceedings of DSI and APDSI2003,Shanghai2003.Pilar,C.,Munuera-Alema,J.L.,Rodrı’guez-Escudero,A.I.,2004.Criteria employed for go/no-go decisions when developing successful highly innovative products.Industrial Marketing Management33,307–316. Pinto,J.K.,Mantel,S.J.,1990.The cause of project failure.IEEE Transaction on Engineering Management37,269–276.Ricardo,F.J.,2001.Hypertext and Knowledge Management Proceedings of the Twelfth ACM conference on Hypertext and Hypermedia,A˚rhus. Rothwell,R.,1994.Industrial innovation:success,strategy,trends,in: Dodgson,M.,Rothwell,R.(Eds.),The Handbook of Industrial Innovation.Edward Elgar Publishing,Vermont,pp.33–53. Roussel,P.A.,Kamal,N.S.,Tamar,J.E.,1991.in:Little,A.D.(Ed.),Third Generation R&D.Harvard Business School Press,Boston. Ruggles,R.L.,1997.Knowledge Management Tools.Butterworth-Heinemann,Boston.Tiwana,A.,2000.The Knowledge Management Toolkit.Prentice Hall PTR,Upper Saddle River,NJ.Tyndale,P.,2002.A taxonomy of knowledge management software tools: origins and applications.Evaluation and Program Planning25,183–190. Utterback,J.M.,1974.Innovation in industry and the diffusion of technology.Science183(4125),620–626.Van der Spek,R.,Spijkervet,A.,1996.Knowledge Management,Dealing Intelligently with Knowledge.Kenniscentrum CIBIT,Utrecht. Wensley,A.,2000.Tools for Knowledge Management,BPRC Conference on Knowledge Management:Concepts and Controversies.Wigg,K.M.,1993.Knowledge Management Foundations:Thinking about Thinking-How People and Organizations Create,Represent and Use Knowledge.Schema Press,Arlington Texas.Zack,M.H.,1999.Managing codified knowledge.Sloan Management Review40(4),45–58.Yongtae Park is a faculty member of the Department of Industrial Engineering and director of Graduate Program of Technology Management at the Seoul National University(SNU).He holds BS in industrial engineering(from SNU),MS and PhD in operations management(both from University of Wisconsin-Madison).His research interests lie in areas of industrial knowledge network, knowledge management system,new product/service development, and on-line business modeling.Dr.Park has published numerous articles in,to name a few,Technovation,International Journal of Production Research,Decision Sciences,Technology Analysis and Strategic Management,R&D Management,Technology in Society, Technology Forecasting and Social Change.Seonwoo Kim is doctoral candidate at SNU.He holds BS and MS in industrial engineering(both from SNU).His dissertation research has focused on design and implementation of knowledge management system.Y.Park,S.Kim/Technovation26(2006)595–602 602。