用户参与产品创新的研发模型及其群体协作模式研究
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摘要
创新的重要性在国内外已得到重视,经济转型和产业链提升成为共识。渐增的产品创新活动必然导致对创新人才的大量需求,未来几年产品创新的瓶颈将逐渐转移到人才的供给方面。本论文的研究主题——用户参与产品创新——着眼于关注普通用户创新资源的开发,研究内容涉及普通用户和群体用户两方面。论文研究的问题主要包括三个部分：1)普通用户对产品创新的参与机制；2)用户参与创新的辅助技术；3)群体用户在非契约状态下的协作创新模式。
针对上述三个问题,论文采用理论建模与实验验证的方法对用户参与产品创新的研发工具箱(UTI)模型及群体用户间协作创新模式进行研究。首先以I空间理论作为解释框架,建立了用户创新行为的信息流模型；基于用户创新的学习循环特征,论证了进化算法用于辅助用户创新的实践意义及可行性,并选择交互式遗传算法(IGA)作为构建UTI模型的技术基础。通过实验验证了群体用户间协作创新(CIGU)的效果,并构建了CIGU的网络运行机制。最后开发了用户创新辅助技术的原型系统,并通过产品外观开发案例进行了验证。
本论文的主要研究内容与研究成果有以下几方面：
1.基于Boisot的I空间框架构建了用户创新的信息流模型,分析了Von Hippel给出的用户创新工具箱(UTI)的四个基本特征：学习循环、人性化交互、模块化与边界化,给出了实现用户创新所需的辅助技术特征。在信息流模型中对产品创新所需的用户信息资源在三维空间中进行了定位,把信息处理的方法表达为不同的行走路径,提出用户和辅助技术结合的研发路径。
2.提出了布尔型的IGA评价方法以降低用户评价疲劳,并基于改进的交互式遗传算法建立了UTI技术框架,制订了外部知识内嵌、敏感度系数识别、敏感度系数应用、进化态势可视化和基于可视化交互的进化控制等面向用户创新学习循环不同环节的辅助技术方案。通过产品设计案例验证了UTI技术框架的有效性。
3.提出了一种基于引用的群体用户协作创新模式(CIGU),综合考虑了一致性、收敛性等群体协作目标。分析指出CIGU模式应具备五个特征：价值累积、信息推送、小世界生成、分工演化和涉众利益的保证。实验结果从集聚性、引用特征、最优性条件、协作结果、协作程度等方面表明了群体用户协作创新的可行性。
4.基于IGA技术和UTI框架构建了CIGU的网络运行机制,设计了该机制对个体用户、群体用户和产品需求发布方三方的辅助功能,并通过实验验证了CIGU机制的关键部分——引用辅助模型的效果。
5.基于改进的IGA技术开发了用户创新工具箱原型系统,通过产品外观设计案例进行了应用验证。
最后,论文对全文的工作进行了总结,并展望了群体用户协作创新需要进一步研究的课题。
The importance of product innovation has been realized gradually in domestic industries. Increasing innovation behavior will soon demand for large amount of developers, and will probably cause shortage in human resource supply. The subject of the thesis——user's participation in product innovation——aims at the exploring of ordinary user's innovative resource, including both single user and group users. The thesis studies mainly three subjects of user innovation:1) mechanism of ordinary user's participation in product innovation;2) aiding techniques;3) group users' collaboration style under non-contractual state.
Considering the three subjects, the thesis carried out research work on user toolkit of innovation (UTI) and users'collaboration through theoretical modeling and experimental study. An information stream model of user innovation is established based on1-Space frame. On the background of user innovation's learning loop features, the feasibility and practicability of genetic algorithms are discussed and interactive genetic algorithms (IGA) is chosen as the technical tool for constructing UTI. Group users'collaborative innovation (CIGU) is studied through experiments, together with aiding techniques of UTI for the main processes, and a web-based CIGU mechanism is designed. A proto-system is established, in which the techniques are tested with typical examples.
The contents and research conclusions of the thesis are as follows:
1. An information stream model is constructed based on Boisot's I-Space frame. User-belonged information resources for product innovation are positioned in the3D space. Information processing methods are expressed as moving paths in I-Space, in which different roles——professional developers, users and aiding techniques——are discussed. The feasibility and conditions for replacing the first with the other two are analyzed. The paths are evaluated from the view of information transaction costs. With the help of information stream model, the author analyzed the four basic features of UTI proposed by Von Hippel:learning loop, friendly interaction, modularity and boundary. Moving paths of the four features in I-Space are observed, from which the aiding technique's properties for realizing learning loop are given.
2. The thesis constructed a UTI technical frame based on IGA, whose traditional evaluation methods are improved. A Boolean evaluation method is designed and proved useful in reducing user's evaluating fatigue. In the UTI model, key aiding techniques are designed for each stage of user's learning loop in I-Space, such as embedding of exterior knowledge, recognision of sensitive factor, utilitiy of sentive factor, visualization of evolutionary situation and evolution control. The techniques are tested with experiments in user innovation.
3. The thesis proposed a collaborative innovation method for group users (CIGU), and derived five features of CIGU through analysis:value accumulation, information propelling, small world generating, labor division and the guarantee of related people. Designed a collaboration method based on citing and carried out experiments. With a comprehensive consideration of consistence and convergence target, the author designed the collaboration model including profit allocation plan. Features of CIGU are observed through the experiment results, and the collaborative method's feasibility to product innovation are proved from the view of concentration, citing pattern, optimality conditions, collaboration results and collaboration degree.
4. With the support of IGA and UTI frame already constructed, a citing-based innovation aiding technical model for CIGU participants is proposed, which provides technical support for user's citing through two models:island model and cell model. A web-based CIGU mechanism is designed, with a detailed description to its aiding mechanisms to individual user, group users and the requirement's demanders.
5. A UTI protosystem was programmed with IGA theory on Solidworks platform, on which user and aiding technique's combination in product innovation are proved feasible.
Conclusive remarks are given for the thesis, with a perspective to further research work.
针对上述三个问题,论文采用理论建模与实验验证的方法对用户参与产品创新的研发工具箱(UTI)模型及群体用户间协作创新模式进行研究。首先以I空间理论作为解释框架,建立了用户创新行为的信息流模型；基于用户创新的学习循环特征,论证了进化算法用于辅助用户创新的实践意义及可行性,并选择交互式遗传算法(IGA)作为构建UTI模型的技术基础。通过实验验证了群体用户间协作创新(CIGU)的效果,并构建了CIGU的网络运行机制。最后开发了用户创新辅助技术的原型系统,并通过产品外观开发案例进行了验证。
本论文的主要研究内容与研究成果有以下几方面：
1.基于Boisot的I空间框架构建了用户创新的信息流模型,分析了Von Hippel给出的用户创新工具箱(UTI)的四个基本特征：学习循环、人性化交互、模块化与边界化,给出了实现用户创新所需的辅助技术特征。在信息流模型中对产品创新所需的用户信息资源在三维空间中进行了定位,把信息处理的方法表达为不同的行走路径,提出用户和辅助技术结合的研发路径。
2.提出了布尔型的IGA评价方法以降低用户评价疲劳,并基于改进的交互式遗传算法建立了UTI技术框架,制订了外部知识内嵌、敏感度系数识别、敏感度系数应用、进化态势可视化和基于可视化交互的进化控制等面向用户创新学习循环不同环节的辅助技术方案。通过产品设计案例验证了UTI技术框架的有效性。
3.提出了一种基于引用的群体用户协作创新模式(CIGU),综合考虑了一致性、收敛性等群体协作目标。分析指出CIGU模式应具备五个特征：价值累积、信息推送、小世界生成、分工演化和涉众利益的保证。实验结果从集聚性、引用特征、最优性条件、协作结果、协作程度等方面表明了群体用户协作创新的可行性。
4.基于IGA技术和UTI框架构建了CIGU的网络运行机制,设计了该机制对个体用户、群体用户和产品需求发布方三方的辅助功能,并通过实验验证了CIGU机制的关键部分——引用辅助模型的效果。
5.基于改进的IGA技术开发了用户创新工具箱原型系统,通过产品外观设计案例进行了应用验证。
最后,论文对全文的工作进行了总结,并展望了群体用户协作创新需要进一步研究的课题。
The importance of product innovation has been realized gradually in domestic industries. Increasing innovation behavior will soon demand for large amount of developers, and will probably cause shortage in human resource supply. The subject of the thesis——user's participation in product innovation——aims at the exploring of ordinary user's innovative resource, including both single user and group users. The thesis studies mainly three subjects of user innovation:1) mechanism of ordinary user's participation in product innovation;2) aiding techniques;3) group users' collaboration style under non-contractual state.
Considering the three subjects, the thesis carried out research work on user toolkit of innovation (UTI) and users'collaboration through theoretical modeling and experimental study. An information stream model of user innovation is established based on1-Space frame. On the background of user innovation's learning loop features, the feasibility and practicability of genetic algorithms are discussed and interactive genetic algorithms (IGA) is chosen as the technical tool for constructing UTI. Group users'collaborative innovation (CIGU) is studied through experiments, together with aiding techniques of UTI for the main processes, and a web-based CIGU mechanism is designed. A proto-system is established, in which the techniques are tested with typical examples.
The contents and research conclusions of the thesis are as follows:
1. An information stream model is constructed based on Boisot's I-Space frame. User-belonged information resources for product innovation are positioned in the3D space. Information processing methods are expressed as moving paths in I-Space, in which different roles——professional developers, users and aiding techniques——are discussed. The feasibility and conditions for replacing the first with the other two are analyzed. The paths are evaluated from the view of information transaction costs. With the help of information stream model, the author analyzed the four basic features of UTI proposed by Von Hippel:learning loop, friendly interaction, modularity and boundary. Moving paths of the four features in I-Space are observed, from which the aiding technique's properties for realizing learning loop are given.
2. The thesis constructed a UTI technical frame based on IGA, whose traditional evaluation methods are improved. A Boolean evaluation method is designed and proved useful in reducing user's evaluating fatigue. In the UTI model, key aiding techniques are designed for each stage of user's learning loop in I-Space, such as embedding of exterior knowledge, recognision of sensitive factor, utilitiy of sentive factor, visualization of evolutionary situation and evolution control. The techniques are tested with experiments in user innovation.
3. The thesis proposed a collaborative innovation method for group users (CIGU), and derived five features of CIGU through analysis:value accumulation, information propelling, small world generating, labor division and the guarantee of related people. Designed a collaboration method based on citing and carried out experiments. With a comprehensive consideration of consistence and convergence target, the author designed the collaboration model including profit allocation plan. Features of CIGU are observed through the experiment results, and the collaborative method's feasibility to product innovation are proved from the view of concentration, citing pattern, optimality conditions, collaboration results and collaboration degree.
4. With the support of IGA and UTI frame already constructed, a citing-based innovation aiding technical model for CIGU participants is proposed, which provides technical support for user's citing through two models:island model and cell model. A web-based CIGU mechanism is designed, with a detailed description to its aiding mechanisms to individual user, group users and the requirement's demanders.
5. A UTI protosystem was programmed with IGA theory on Solidworks platform, on which user and aiding technique's combination in product innovation are proved feasible.
Conclusive remarks are given for the thesis, with a perspective to further research work.
引文
[1]Allen, R.C. Collective invention [J]. Journal of Economic Behavior and Organization,1983(1):1-24
[2]Arrow, K. "Economic welfare and the allocation of resources for inventions" in R.R. Nelson, ed., The rate and direction of inventive acivity. Princeton Univeristy Press,1962
[3]Azevedo, C.D., Herriges, J.A., Kling, C.L. Combining Revealed and Stated Preference:Consistency Tests and Their Interpretations [J]. American Agricultural Economics Association,2003.85(3):525-537
[4]Benkler, Y. TheWealth of Networks [M]. New Haven:Yale University Press, 2006
[5]Beyer, H.G. Actuator noise in recominant evolution strategies on general quadratic fitness models[C]//Proceedings of Genetic and Evolutionary Computation Conf(GECCO2004). Seattle, WA, USA:Springer,2004: 654-665.
[6]Boisot, M.H. Is your firm a creative destroyer? Competitive learning and knowledge flows in the technological strategies of firms [J]. Research Policy, 1995.24:489-506
[7]Boisot, M.H., MacMillan, I.C. Kyeong, S.H. Explorations in Information Space [M]. London:Oxford University Press,2007
[8]Branke, J., Schmidt, C. Sequential sampling in noisy environments[M]//Lecture Notes in Computer Science. Berlin:Springer,2004: 202-211.
[9]Brownstone, D., Bunch, D.S., Train, K. Joint mixed logit models of stated and revealed preferences for alternative-fuel vehicles [J]. Transportation Research, 2000.34:315-338
[10]Chambers, J.M., Cleveland, W.S., Kleiner, B., Turkey, P.A. Graphical methods for data analysis [M]. New York:Chapman and Hall; 1983
[11]Chebrough, H. Open services innovation [M]. Jossey-Bass,2011
[12]Chesbrough, H. Managing open innovation [J]. Research Technology Management,2004.47(1):23-26
[13]Chesbrough, H. Open Innovation, the new imperative for creating and profiting from technology [M]. Harvard business school press,2003
[14]Chesbrough, H. The Era of Open Innovation [J]. MIT sloan management review,2003.44(3):35-41
[15]Cohen, W.M, Levinthal D.A. Absorptive capacity:a new perspective on learning and innovation [J]. Administrative Science Quarterly, 1990.35:128-152
[16]Connolly, T., Routhieaux, R.L., Schneider, S.K. On the effectiveness of group brainstorming:Test of an underlying cognitive mechanism [J]. Small Group Research,1993,24:490-503.
[17]Coombs, R., Metcalfe, J.S. Organizing for innovation:Co-coordinating Distributed Innovation Capabilities. In:Foss N., Mahnke V. Competence, Governance and Entrepreneurship [M]. Oxford:Oxford University Press,2002: 209-231
[18]Curado, C., Bontis, N. Parallels in knowledge cycles [J]. Computers in Human Behavior,2011.27:1438-1444
[19]DeGroot, M.H. Reaching a Consensus [J]. Journal of the American Statistical Association.1974(69):118-121
[20]Demartines, P. Herault, J. Curvilinear component analysis:a self-organizing neural network for nonlinear mapping of data set [J]. IEEE Transactions on Neural Networks,1997.8(1):148-154
[21]Devine, D.J. Effects of cognitive ability, task knowledge, information sharing, and conflict on group decision-making effectiveness [J]. Small Group Research,1999,30 (5):608-634.
[22]Dipietro, A., While, L. Applying evolutionary algorithms to problems with noisy, time-consuming fitness functions[C]//Proceedings of the 2004 Congress on Evolutionary Computation. Portland, OR, USA:[s.n.],2004:1254-1261
[23]Espino, R., Roman, C., Ortuzar, J.D.D. Analyzing demand for suburban trips: A mixed RP/SP model with latent variables and interaction effects [J]. Transportation,2006.33:241-261
[24]Frank, N., Von Hippel, E. Satisfying heterogeneous user needs via innovation toolkits:the case of apache security software [J]. Research Policy, 2003.32:1196-1215
[25]Frey, K., Liithje, C., Haag, S. Whom Should Firms Attract to Open Innovation Platforms? The Role of Knowledge Diversity and Motivation [J]. Long Range Planning 2011.44:397-420
[26]Fuller, F., Faullan, R., Matzler, K. Triggers for virtual customer integration in the development of medical equipment—From a manufacturer and a user's perspective [J]. Industrial Marketing Management,2010.39:1376-1383
[27]Fuller.J.,Jawecki.G.,Miihlbacher.H. Innovation creation by online basketball communities [J]. Journal of Business Research,2007(60):60-71
[28]Golub, B., Jackson, M.O. Naive learning in social networks:convergence, influence, and the wisdom of crowds. Available at http://www.standford.edu/-jackson/naivelearning.pdf,2007
[29]Gong, D., Zhou, Y., Li, T. Cooperative interactive genetic algorithm based on user's preference [J]. International Journal of Information Technology, 2005.11(10):1-10.
[30]Gong, DW., Guo, GS. Interactive genetic algorithms with interval fitness of evolutionary individuals [J]. Dynamics of Continuous, Discrete and Impulsive Systems, Series B,2007,14(S2):446-450.
[31]Gong, DW., Guo, GS., Lu, L., Ma, HM. Adaptive interactive genetic algorithms with individual interval fitness [J]. Progress in Natural Science, 2008.18:359-365
[32]Gong, DW., Hao, GS., Zhou, Y., Sun, XY. Interactive genetic algorithms with multi-population adaptive hierarchy and their application in fashion design [J]. Applied Mathematics and Computation,2007.185:1098-1108
[33]Grant, R.M., Barden-Fuller, C. A knowledge-based theory of inter-firm collaboration [J]. Academy of management best paper proceedings, 1995:17-21
[34]Griffiths, D., Boisot, M.H., Mole, V. Strategies for managing knowledge assets: a tale of two companies [J]. Technovation,1998.18(8/9):529-539
[35]Grijalva, T., Bohara, A.K., Berrens, R.P. A seemingly unrelated Poisson model for revealed and stated preference data [J]. Applied Economics Letters, 2003.10.443-446
[36]Gu, ZY., Tang, MX., Frazer, J.H. Capturing aesthetic intention during interactive evolution [J]. Computer-Aided Design,2006.38:224-237
[37]Guo, GS, Gong, DWi, Hao, GS, Zang, Y. Interactive Genetic Algorithms with Fitness Adjustment[J]. J. China Univ. of Mining & Tech. (English Edition), 2006.16(4):480-484
[38]Hao, GS., Huang, YQ. Fitness Noise in Interactive Evolutionary Computation and the Convergence Robustness [J]. Proceedings of the Sixth International Conference on Intelligent Systems Design and Applications (ISDA'06):2006
[39]Harhoff, D., Henkel, J., Von Hippel, E. Profiting from voluntary information spillovers:how users benefit by freely revealing their innovation [J]. Research Policy,2003.32(10):1753-1769
[40]Hasan, H., AI-hawari, M. Management styles and performance:a knowledge space framework [J]. Journal of Knowledge Management,2003.7(4)
[41]Hayashida, N., Takagi, H. Visualized IEC:interactive evolutionary computation with multidimensional data visualization[C]. Proceedings of 2000 IEEE International Conference on Industrial Electronics, Nagoya, Japan: 2000:2738-2743
[42]Henmi, S., Iwashita, S., Takagi, H. Interactive evolutionary computation with evaluation characteristics of Multi-IEC users[C].2006 IEEE International Conference on Systems, Man, and Cybernetics, Vols 1-6, Proceedings, Taipei,China:2006:3475-3480
[43]Hensher, D.A., Rose, J.M., Greene, W.H. Combining RP and SP data:biases in using the nested logit'trick'-contrasts with flexible mixed logit incorporating panel and scale effects [J]. Journal of Transport Geography,2008(16):126-133
[44]Hensher, D.S., Bradley, M. Using stated response choice data to enrich revealed preference discrete choice models [J]. Marketing Letters, 1993.4(2):139-151
[45]Herstatt, C., Von Hippel, E. From Experience:Development New Product Concept Via the Lead User Method:A Case Study in a "Low" Field[J]. The Journal of Product Innovation Management,1992,9(3):213-221
[46]Hienerth, C., Keinz, P., Lettl, C. Exploring the Nature and Implementation Process of User-Centric Business Models [J]. Long Range Planning 2011.44 344-374
[47]Holland, J. Adaptation in natural and artificial systems:an introductory analysis with application to biology, control, and artificial intelligence [M]. Cambridge:MIT Press,1992
[48]Hyvarinen, A. Survey on independent component analysis [J]. Neural Computing Surveys,1999.2:94-128
[49]Ichijo, K. Knowledge exploitation and knowledge exploration:twostrategies for knowledge creating companies. In C. Choo & N. Bontis (Eds.),The Strategic Management of Intellectual Capital and Organizational Knowledge. New York:Oxford University Press.2002:477-483
[50]Ingwersen, P. The calculation of Web Impact Factors [J]. Journal of Documentation.1998.54(2):236-243
[51]Inselberg, A., Dimsdale, B. Multi-dimensional lines I:representation and multi-dimensional lines II:proximity and applications [J]. SIAM Journal of Application Math,1994.54(2):559-596
[52]Jackson, M.O., Wolinsky, J. A strategic model of social and economic networks[J]. Journal of Economic Theory.1996.71(1):44-74
[53]Jin, Y., Branke, J. Evolutionary optimization in uncertain environments-A survey[J]. IEEE Transactions on Evolutionary Computation,2005,9(3): 303-317.
[54]Joseph, A. Schumpeter. The theory of economic development[M]. Havard University Press, (1921)1961
[55]Joshi, M., Kumar, V, Agarwal, R. Evaluating boosting algorithms to classify rare classes:comparison and improvements [C]. Proceedings of the 1st IEEE international conference on Data mining. Washington DC:IEEE Computer Society,2001:257-264
[56]Kamalian, R., Yeh, E., Zhang, Y., Agogino, A.A., Takagi, H. Reducing human fatigue in Interactive Evolutionary Computation through fuzzy systems and machine learning systems[C].2006 IEEE International Conference on Fuzzy Systems,2006:678-684
[57]Kamalian, R., Zhang, Y, Takagi, H., Agogino, A.M. Reduced human fatigue interactive evolutionary computation for micromachine design [C]. IEEE,2005:5666-5671
[58]Karacapilidis, N., Papadias, D. Computer support argumentation and collaborative decision making:the HERMES system [J]. Information Systems,2001(26):259-277.
[59]Kay, J., Kummerfeld, B., Lauder, P. Personis:A server for user models [C]. Proceedings of Adaptive Hypermedia and Adaptive Web-based Systems. London,UK:Springer-Verlag,2002
[60]Kennedy, J., Eberhart, R. Particle swarm optimization [C]. Proceedings of IEEE International Conference on Neural Networks, Piscataway:IEEE Service Center,1995:1942-1948
[61]Kennedy, J., Mendes, R. Population structure and particles swarm performance [C]. Proceedings of the IEEE Congress on Computation Intelligence,2002:1671-1675
[62]Kim, H.J. Motivations for hyperlinking in scholarly electronic articles:A qualitative study [J]. Journal of the American Society for Information Science, 2000.51(10):887-899
[63]Kim, HS, Cho, SB. Supporting serendipity:Using ambient intelligence to augment user exploration for data mining and Web browsing[J]. International Journal of Human-Computer Studies,2007.65 (5):421-433
[64]Knott, A. Exploration and exploitation as complements. In C. Choo & N.Bontis (Eds.), The Strategic Management of Intellectual Capital and OrganizationalKnowledge. New York:Oxford University Press.2002:339-358
[65]Kobsa, A. Generic user modeling systems[J]. User Modeling and User-Adapted Interaction Journal,2001.11 (1/2):49-63
[66]Kohonen,T. The self-organizing map [J]. Proceedins of the IEEE, 1990.78(9):1464-1480
[67]Kumar, M., Krishna Rao, K.V. A stated preference study for a car ownership model in the context of developing countries [J]. Transportation Planning and Technology,2006.29(5):409-425
[68]Lane, D.A, et al. Complexity Perspectives in innovation and Social Change [M]. Springer, Berlin:2009
[69]Lee, JH, Cho, SB. Analysis of direct manipulation in interactive evolutionary computation on fitness landscape [C].2002,IEEE:460-465s
[70]Lee, JY, Cho, SB. Sparse fitness evaluation for reducing user burden in interactive genetic algorithm[C]. Proc of FUZZ—IEEE'99. Seoul,1999,2: 998-1003.
[71]Lerner, J. Tirole, J. Some simple economics of open source [J]. Journal of Industrial Economics 2002.50(2):197-234
[72]Lett, C., Herstatt, C., Gemuenden, H.G. Users'Contributions to Radical Innovation:Evidence from Four Cases in the Field of Medical Equipment Technology[J]. R & D Management,2006.36 (3):251-272
[73]Lewis, T.G. Network Science:Theory and Applications [M]. John Wiley & Sons, Inc.2009:199-225
[74]Loomis, J. An investigation into the reliability of intended visitation behavior [J]. Environmental and Resource Economics,1993.3(2):183-191
[75]Loureiro, M.L., McCluskey, J.J., Mittelhammer, R.C. Are stated preferences good predictors of market behavior? [J]. Land Economics, 2003.82(4):623-640
[76]Luethje, C. Characteristics of Innovating Users Consumer Goods Field:An Empirical Study of Sport2related Product Consumer[J]. Technovation, 2004,24 (9):683-695.
[77]Lutton, E., Pilz, M., Vehel, J.L. The Fitness Map Scheme Application to interactive multifractal image denoising [J]. IEEE,2005:2278-2285
[78]Magnusson, P.R.. Exploring the contributions of involving ordinary users in ideation of technology-based services[J]. Journal of Product Innovation Management,2009 (26):578-593
[79]Mahr, D., Lievens, A. Virtual lead user communities:Drivers of knowledge creation for innovation [J]. Research Policy,2012(41):167-177
[80]Mark, J., Clayton, J., Kunz, C., Martin, A. Rapid Conceptual Design Evaluation Using a Virtual Product Model. EngngApplic. Artif lntelL, 1996.9(4):439-451
[81]Masthoff, J. Group modeling:Selecting a sequence of television items to suit a group of viewers [J]. User Modeling and User-Adapted Interaction, 2004.14(1):37-85
[82]Matsubara, Y; Nagamachi, M. Hybrid Kansei Engineering System and design support[J]. International Journal of Industrial Ergonomics,1997.19 (2):81-92
[83]Merton, R. The sociology of science [M]. Theoretical and empirical investigations. Chicago:Univeristy of Chicago Press.1973
[84]Miki, M., Hiroyasu, T., Ogawa, Y., Nagaya, Y, Yoshida, S. Effectiveness of parallel distributed model in interactive genetic algorithm [C]. The Japanese Society for Artificial Intelligence,2002
[85]Miki, M., Hiroyasu, T., Tomioka, H. Validity of the consensus building system using the parallel distributed interactive genetic algorithm [J]. Transactions of The Japanese Society for Artificial Intelligence,2005.20:289-296.
[86]Miki, M., Yamamoto,Y, Wake, S., et al. Global asynchronous distributed interactive genetic algorithm [C]. IEEE International Conference on Systems, Man and Cybernetics. Taipei,2006:3481-3485.
[87]Miles, R.E., Miles,G., Snow, C.C. Collaborative Entrepreneurship:How Communities of Networked Firms Use Continuous, Innovation to Create Economic Wealth[M]. Stanford, C.A. Stanford University Press,2005
[88]Moed, H.F. The impact-factor debate:The ISI's uses and limits [J]. Nature, 2002.415:731-732
[89]Morikawa, T. Correcting stated dependence and serial correlation in the RP/SP combined estimation method [J]. Transportation,1994.21:153-165
[90]Morrison, P.D., Roberts, J.H, von Hippel, E. Determinants of User Innovation and Innovation Sharing in a Local Market[J]. Management Science, 2000,46 (12):1513-1527.
[91]Morrison, P.D., Rorbert, J.H.,Midgley, D.F. The nature of lead users and measurement of leading edge status [J].Research Policy,2004 (33):351-362
[92]Mukhtar, M., Ismail, M.N., Yahya, Y. A hierarchical classification of co-creation models and techniques to aid in product or service design [J]. Computers in Industry,2012.63:289-297
[93]Nagamachi, M. Kansei engineering as a powerful consumer-oriented technology for product development[J]. Applied Ergonomics,2002.33 (3): 289-294
[94]Nam Pyo Suh.公理设计——发展与应用[M].北京：机械工业出版社,2004
[95]Nelson, R.R., Winter, S.G. An evolutionary theory of economic change [M]. Canbridge, Mass.:Havard University Press,1982
[96]Nojima, Y., Kojima, F., Kubota, N. Trajectory generation for human-friendly behavior of partner robot using fuzzy evaluating interactive genetic algorithm [C]. Proceedings of 2003 IEEE International Symposium on Computational Intelligence in Robotics and Automation,2003:306-311
[97]Nonaka, I. A dynamic theory of organizational knowledge creation [J]. Organization Science,1994.5(1):14-37
[98]Nonoka, I. The knowledge-creating company [J]. Harvard Business Review, 1991.69(6)
[99]Nonoka, I., Konno, N. The concept of "Ba":building a foundation for knowledge creation [J]. California Management Review,1998.40(3)
[100]Ogawa, S. Does sticky information affect the locus of innovation? Evidence from the Japanese convenience-store industry [J]. Research Policy, 1998.26:777-790
[101]Ogawa, Y., Miki, M., Hiroyasu, T., Nagaya, Y. A New Collaborative Design Method Based on Interactive Genetic Algorithms[C]. eurogen,2001
[102]Ohsaki, M, Takagi, H, Ohya, K. An input method using discrete fitness values for interactive GA[J]. J of Intelligent and Fuzzy Systems,1998,6(1):131-145.
[103]Olson, M. The logic of collective action [M]. Harvard University Press,1967
[104]Packham, I.S.J. An interactive visualisation system for engineering design using evolutionary computing [D]. PhD Thesis, University of Plymouth, December; 2003
[105]Pijl, G.J., Boven, H.P. Knowledge management as a full-grown discipline:a framework for a universal approach to knowledge management [C]. In Buhalis,D., Tjoa, A., Jafari, J. eds. Information and communication technologies in Tourism,1998:Proceedings of the international conference in Istanbul, Turkey,1998. New York:Springer-Verlalg,1998
[106]Polanyi, M. Study of man [J]. Chicago:The university of Chicago Press,1958
[107]Raymond, E. The cathedral and the bazaar [M]. O'Reilly,1999
[108]Ren, J.J. Consumptive Innovation Oriented R&D Strategy for Jewelry Industry's Product Design Techniques [J]. Communications in Computer and Information Science,2012.96:142-146
[109]Reynolds,R. G. An introduction to cultural algorithms[C]. Proceedings of the 3rd Annual Conference on Evolutionary Programming,.New Jersey: 1994:131-139
[110]Reynolds, C. Flocks, herds, and schools:a distributed behavioral model [J]. Computer Graphics,1987.21(4):25-34
[111]Reynolds, R.G., Michalewicz Z.,Cavaretta M., Using cultural algorithms for constraint handling in GENOCOP[C]. Proceedings of the 4th Annual Conference on Evolutionary Programming.1995:298-305
[112]Rothwell, R. Towards the fifth-generation Innovation Process [J]. International Marketing Review,1994.11(1):7-31
[113]Roweis, S.T., Saul, L.K. Nonlinear dimensionality analysis by locally linear embedding [J]. Science,2000.290(12):2323-2326
[114]Sanchez-Gonzalez, G., Gonzalez-Alvarez, N., Nieto, M. Sticky information and heterogeneous needs as determining factors of R&D cooperation with customers [J]. Research Policy,2009.38:1590-1603
[115]Sano, Y., Kita, H. Optimization of noisy fitness functions by means of genetic algorithms using history of search with test of estimation[C]//Proceedings of IEEE Congress on Evolutionary Computation (CEC2002). New York:Morgan Kaufmann,2002:360-365.
[116]Sawhney, M.,Verona, G, Prandelli, E. Collaborating to create:Theinternet as a platform for customer engagement in product innovation[J]. Journal of Interactive Marketing,2005.19(4):4-17
[117]Shannon, C. E. A mathematical theory of communication [J]. Bell System T echnology Journal,1948.27:379-429,623-656
[118]Shapley, L.S. A value for n-person games [J]. Annals of Mathematics Studies, 1953(28):307-317
[119]Sheth, J.N. Book Reviews:The Sources of Innovation [J] Journal of Marketing,1990,54 (1):139-141
[120]Sidney, G., Winter, S. Knowledge and Competence as Strategic Management Assets, in David J. Teece (ed), The Competitive Challenge:Strategies for Industrial Innovation and Renewal, Chapter 8, MA:Ballinger Publishing Company,1987:171-173
[121]Simonin, B.L. Ambiguity and the process of knowledge transfer in strategic alliances [J]. Strategic Management Journal,1999.20:595-623
[122]Simonin, B.L. Transfer of marketing know-how in international strategic alliances:an empirical investigation of the role and antecedents of knowledge ambiguity [J]. Journal of International Business Studies.1999.30(3):463-490
[123]Slonim, T.Y., Schneider, M. Design issues in fuzzy case-based reasoning [J]. Fuzzy Set s and Systems,2001.117(2):251-267
[124]Stewart, T.J. A critical survey on the status of multiple criteria decision making theory and practice [J]. Omega,1992.20(5/6):569-586
[125]Stigler, G. The economics of information [J]. Journal of Political Economy, 1961.69(3):213-225
[126]Sun, Y., Wang, WL., Lv, RM., Liu, XJ. Fatigue-Decreasing Oriented Study on the Evaluation Precision of IGA in Product Design Optimization [C]. Asian Conference on Design and Digital Engineering 2011(ACDDE 2011), Shanghai: 2011:103-107
[127]Szulanski, G. Exploring internal stickiness:Impediments to the transfer of best practice within the firm [J]. Strategic Management Journal, Winter Special Issue,1996.17:27-43
[128]Szulanski, G.The process of knowledge transfer:A diachronic analysis of stickiness [J]. Organizational Behavior and Human Decision Process, 2000.82(1):9-27
[129]Takagi, H. Interactive evolutionary computation:Fusion of the capabilities of EC optimization and human evaluation[C]. Proceedings of the IEEE,2001.89 (9):1275-1296
[130]Tallman, S. Global strategic management. In M. Hitt, R. Freeman,& J.Harrison (Eds.), Handbook of Strategic Management. Malden, MA: Blackwell,2001
[131]Teece, D.J. Profiting from technological innovation:Implications fro integration, collaboration, licensing and public policy [J]. Research Policy, 1986.15(6):285-305
[132]Tenenbaum, J.B., Vin de Silva, Langford, J.C. A global geometric framework for nonlinear dimensionality reduction [J]. Science,2000.290(12):2319-2323
[133]Thelwall, M. Link Analysis:An Information Science Approach[M]. Elsevier Inc.2004
[134]Thomke, S. Enlighted Experimentation:The New Imperative for Innovation[J]. Harvard Business Review,2001,79 (2):67-75
[135]Thomke, S., Von Hippel, E. Customers as innovators[J]. Harvard Business Review,2002,80(4):74-84
[136]Todoroki, Takagi, H. User interface of an interactive evolutionary computation for speech processing[C].6th Int Conf on Soft Computing. Iizuka,2000: 112-118.
[137]Torgerson, W.S. Multidimensional scaling Ⅰ:theory and method [J]. Psychometrika,1952.17:401-419
[138]Urban, G.L., Von Hippel, E., Lead User Analyses for the Development of New Industrial Products [J]. Management Science,1988.34(5):569-582
[139]URL:http://baike.baidu.com/view/48146.htm
[140]URL:http://baike.baidu.com/view/729695.htm
[141]URL:http://secondlife.com/
[142]URL:http://Threadless.com
[143]URL:http://www.Fluevog.com
[144]URL:http://www.zhubajie.com
[145]URL:http://www.avant-lab.com/GUCI.html
[146]URL:http://www.scriptspot.com
[147]URL:http://www.threadless.com
[148]URL: http://zh.wikipedia.org/wiki/%E4%BA%91%E8%AE%A1%E7%AE%97
[149]Van Raan, A.F.J. The Pandora's box of citation analysis:Measuring scientific excellence the last evil? In:Cronin,B.& Atkins, H.B. (Eds). The web of knowledge:a festschrift in honor of Eugene Garfield. Metford, NJ: Information Today Inc. ASIS Monograph Series,2000:301-319
[150]Verhoef, P.C., Franses, P.H., Combining revealed and stated preferences to forecast customer behavior:three case studies [J]. International Journal of Market Research,2003.45:467-474
[151]Von Hippel, E. "Sticky Information"and the Locus of Problem Solving: Implications for Innovation [J], Management Science,1994,40 (4):429-439
[152]Von Hippel, E. Democratizing Innovation [M]. Cambridge:MIT Press,2005.
[153]Von Hippel, E. Economics of Product Development by Users:The Impact of Sticky"Local Information[J]. Management Science,1998.44(5):629-644
[154]Von Hippel, E. Perspective:User Toolkits for Innovation [J]. The Journal of Product Innovation Management,2001,18:247-257
[155]Von Hippel, E., Democratizing Innovation Cambridge[M]. MA:MIT Press, 2005.
[156]Von Hippel, E., Katz, R. Shifting innovation to users via toolkits[J]. Management Science,2002,48 (7):821-833
[157]Von Hippel, E., The Dominant Role of the Users in Semiconductor and Electronic Subassembly Process Innovation [J]. IEEE Transactions on Engineering Management,1977.24(2):60-71
[158]Von Hippel, E., The Sources of Innovation [M]. Oxford University Press, New York,1988.
[159]Von Hippel, E., Thomke, S., Sonnack, M., Creating Breakthroughs at 3M[J]. Health Forum Journal,2000,43 (4):20-26
[160]Von Hippel, E.,. Lead Users:A Source of Novel Product Concepts [J]. Management Science,1986(32):791-805
[161]Von Hippel,E.,The Dominant Role of Users in the Scientific Instrument Innovation Process [J]. Research Policy,1976.5(3):212-239
[162]Wang, YM. On fuzzy multi attribute decision making models and methods with incomplete preference information [J]. Fuzzy Sets and Systems, 2005,151(2):285-301
[163]Williams, K. O'Reilly C. The complexity of diversity:A review of forty years of research[J]. Research in Organizational Behavior,1998,20:77-140.
[164]敖成龙,苏英,龚元明.基于相似度的复杂数据对象比较[J].北京理工大学学报,2003,23(5)：593-595
[165]柏格森,亨利.创造进化论[M].凤凰出版传媒集团,2011
[166]保罗.拉索.图解思考——建筑表现技法[M].北京：中国建筑工业出版社,2002
[167]鲍尔,P.预知社会：群体行为的内在法则[M].当代中国出版社,2010
[168]伯特,R.结构洞：竞争的社会结构[M].格致出版社,上海人民出版社,2008：34-35
[169]博伊索特,M.H.知识资产：在信息经济中赢得竞争优势[M].上海：上海人民出版社,2004
[170]布坎南,M.隐藏的逻辑[M].The Garamond Agency, Inc,2007
[171]布瓦索,M.H.信息空间：认识组织、制度和文化的一种框架[M].上海：上海译文出版社,2000
[172]曹毅,贺卫红.基于用户兴趣的混合推荐模型[J].系统工程,2009.27(6)：68-72
[173]曹振飞.网络社会生态系统中信息流动的模型研究[J].技术与创新管理,2010.31(6)：684-688
[174]常宝,储雪林,李红艳.试论粘滞知识及其管理对策[J].科学学研究,2005.23(2)：23-26
[175]陈劲,龚焱,雍灏.技术创新信息源新探：领先用户研究[J].中国软科学,2001(1)：86-88
[176]陈劲,王鹏飞.选择性开放式创新---以中控集团为例[J].软科学,2011.25(2)：112-115
[177]陈劲,阳银娟.协同创新的理论基础与内涵[J].科学学研究,2012.30(2)：161-164
[178]陈钰芬,陈劲.开放式创新：机理与模式[M].科学出版社,2008
[179]陈钰芬,陈劲.用户参与创新：国外相关理论文献综述[J].科学学与科学技术管理,2007(2)：52-56
[180]崔志华,曾建潮.微粒群优化算法[M].北京：科学出版社,2011
[181]戴凌燕,陈劲.产品创新的新范式：用户创新[J].经济管理,2003(12)：16-20
[182]董艳,张大亮,徐伟青.用户创新的条件和范式研究[J].浙江大学学报(人文社会科学版),2009.39(4)：43-54
[183]董艳,张大亮,徐伟青.基于创新方式的用户创新资源开发策略研究[J].科技进步与对策,2010.27(9)：22-25
[184]冯.希普尔,E.技术创新的源泉[M].柳卸林译.北京：科学技术文献出版社,1997
[185]冯.希普尔,E.民主化创新[M].北京：知识产权出版社,2007
[186]高忠义,王永贵.用户创新及其管理现状与展望[J].外国经济与管理,2006.28(4)：40-47
[187]耿新,彭留英.企业知识的分类、分布于转化机制研究[J].管理科学,2004(4)：43-48
[188]龚艳冰,丁德臣,何建敏.一种基于直觉模糊集相似度的多属性决策方法[J].控制与决策,2009,24(9)：1398-1401
[189]巩敦卫,郝国生,严玉若.交互式遗传算法基于用户认知不确定性的定向变异[J].控制与决策,2010.25(1)：74-78
[190]巩敦卫,郝国生,周勇,郭一楠.交互式遗传算法原理及其应用[M].北京：国防工业出版社,2007
[191]巩敦卫,任洁,孙晓燕.区间适应值交互式遗传算法神经网络代理模型[J].控制与决策,2009.24(10)：1522-1525
[192]巩敦卫,孙晓燕,任洁.基于联赛评价和知识提取的交互式遗传算法[J].山东大学学报(工学版),2009.39(2)：1-7
[193]巩敦卫,孙晓燕.协同进化遗传算法理论及应用[M].北京：科学出版社2009
[194]巩敦卫,周勇,郭一楠.基于多近似模型的交互式遗传算法[J].控制理论与应用,2008.25(3)：434-438
[195]古斯塔夫.勒庞.乌合之众[M].新世界出版社,2011
[196]古斯塔夫.勒庞.心理学统治世界[M].金城出版社,2011
[197]关庆珍,周竹荣.基于Ontology的用户模型研究[J].计算机应用,2007.27(10)：2504-2507
[198]哈肯,H.信息与自组织[M].成都：四川教育出版社,1988
[199]郝国生,史有群,黄永青等.交互式进化计算的适应值噪声及收敛鲁棒性[J].软件学报,2007.18(9)：2183-2193
[200]何国正,陈荣秋.消费品行业领先用户识别方法研究[J].统计与决策,2009(4)：15-17.
[201]何国正.基于领先用户的顾客参与新产品研发研究[D].武汉：华中科技大学博士论文,2008
[202]亨利·切萨布鲁夫,维姆·范哈佛贝克,乔·韦斯特.开放创新的新范式[M].北京：科学出版社,2010
[203]黄永青,张祥德.交互式进化计算研究进展[J].控制与决策,2010.25(9)：1281-1286
[204]蒋姗姗,曹先彬,王煦法.基于IGA的用户Agent模型与设计[J].模式识别与人工智能,2004.17(2)：244-249.
[205]蒋占四,陈立平,罗年猛.最近邻实例检索相似度分析[J].计算机集成制造系统,2007,13(6)：1165-1168
[206]杰夫.豪.众包[M].北京：中信出版社,2011
[207]金英,苏萌.消费者自述偏好与实际选择的矛盾：中国汽车市场的实证研究[J].管理世界,2010(1)：98-106
[208]卡尔.波普尔.客观知识：一个进化论研究[M].上海：上海译文出版社,2001
[209]科林.F.凯莫勒,乔治.罗文斯坦,马修.拉宾.行为经济学新进展[M].北京：中国人民大学出版社,2010
[210]莱昂.瓦尔拉斯.纯粹经济学要义：或社会财富论[M].北京：商务印书馆,1989
[211]李德毅.云计算技术发展报告[M].北京：科学出版社,2011
[212]李刚,刘益.国内外企业知识转移的研究现状分析[J].情报杂志,2007(9)：10-13
[213]李红玲,廖建桥.从Shannon-Weaver到Boisot:解读国外若干典型知识转移模型[J].科技管理研究,2008(4)：243-249
[214]李景峰.企业知识运动研究——创新视野中的企业知识协同演化[D].太原：山西大学管理学院博士学位论文,2008
[215]李兆军.资本市场信息空间的路径选择[D].天津：天津财经大学博士学位论文,2008
[216]梁昌勇,蔡美菊,陆青.面向隐性目标优化的改进小生境遗传算法及其在汽车造型设计中的应用[J].中国管理科学,2011.19(1)：126-134
[217]刘合翔.“信息空间”理论视角下的信息服务产业界定与划分[J].图书情报工作,2010.54(22)：47-50
[218]刘树林,席酉民.年龄与群体创建决策方案数量和质量的实验研究[J].控制与决策,2002,17卷增刊：798-801.
[219]刘潇,孙强,王秀坤.一种改进的最优保存人机交互遗传算法[J].辽宁师范大学学报(自然科学版),2004.27(2)：168-171
[220]刘肖健.机电产品计算机辅助形态设计中的人机工程设计方法研究[D].西安：西北工业大学博士学位论文,2005
[221]路易斯(Lewis, T.G.).网络科学——原理与应用[M].北京：机械工业出版社,2011
[222]马峻.创新设计的系统与决策技术[M].北京：科学出版社,2008
[223]马克.格兰诺维特.找工作：关系人与职业生涯的研究[M].上海：上海人民出版社,2008
[224]玛格丽特.博登.人工智能哲学[M].上海：上海译文出版社,2001
[225]马修·O·杰克逊(Jackson, M.O.).社会与经济网络[M].北京：中国人民大学出版社,2011
[226]彭冬梅,刘肖健,孙守迁.信息视角：非物质文化遗产保护的数字化理论[J].计算机辅助设计与图形学学报,2008.20(1)：119-125
[227]齐岩,卢德唐.交互式遗传算法在基于内容的图像检索中的应用[J].中国图象图形学报,2004.9(1)：46-55
[228]任晓,杨锡怀,邹家兴.基于组合相似度的混合多指标信息聚类分析方法[J].东北大学学报(自然科学版),2010,31(11)：1657-1660
[229]芮明杰,李鑫,任红波.高技术企业知识创新模式研究[J].外国经济与管理,2004(5)：8-12
[230]瑞萨电子与Morpho公司共同开发出可通过手势操控家电的人机交互技术[J].中国电子商情,2010(7)：74
[231]萨缪尔森,保罗.经济分析基础[M].大连：东北财经大学,2006
[232]上海财经大学高等教育研究所.诺贝尔经济学奖之路[M].上海财经大学出版社,2010
[233]盛小平,吴菁.知识管理流派浅析[J].国家图书馆学刊,2007.1：55-61
[234]盛小平,吴菁.知识管理流派浅析(续)[J].国家图书馆学刊,2007.2：53-57
[235]施蒂格勒,J.乔治.施蒂格勒回忆录：一个自由主义经济学家的自白[M].北京：中信出版社,2006
[236]宋东明,朱耀琴,,吴慧中.基于交互式遗传算法模型的群体论证方法[J]. 中国工程科学,2009.11(11)：64-69
[237]宋媛媛,孙坦.个性化推荐系统中的用户模型问题[J].图书馆杂志,2004.23(12)：53-56
[238]孙晓燕,巩敦卫.自适应分区多代理模型交互式遗传算法[J].控制与决策,2009.24(2)：170-175
[239]孙晓燕,王煦法,巩敦卫.分布协同交互式遗传算法及其在群体决策中的应用[J].信息与控制,2007.36(5)：557-561
[240]孙艳,刘肖健,王万良.创新性与满意度融合的用户创新方法及其在产品外观优化中的应用[J].计算机辅助设计与图形学学报,2012.24(7)：954-960
[241]孙艳,刘肖健.研发团队与产品创新的协同进化机制研究[J].科技与管理,2006.40(6)：113-119
[242]泰普斯科特,D.维基经济学[M].中国青年出版社,2011
[243]托夫勒,A.,托夫勒,H.财富的革命[M].中信出版社,2006
[244]托夫勒,A.第三次浪潮[M].中信出版社,2005
[245]瓦茨,D.J.六度分隔：一个相互连接的时代的科学[M].中国人民大学出版社,2011
[246]汪丁丁.知识社会与知识资产问题in财富的革命[M].中信出版社,2006
[247]王毅.粘滞知识转移研究评述[J].科研管理,2005.26(2)：71-75
[248]王永贵,姚山季,司方来,马双.组织顾客创新、供应商反应性与项目绩效的关系研究：基于组织服务市场的实证分析[J].南开管理评论,2011.14(2)：4-13
[249]王志伟.企业外部知识网络嵌入性对破坏性创新绩效的影响机制研究[D].浙江大学,2010
[250]魏学成,李文涛.基于改进Shapley值法的供应链联盟利益分配研究[J].决策参考,2010(23)：53-55
[251]文卡特.托马斯瓦米,弗朗西斯.高哈特.众包：群体创造的力量[M].北京：中信出版社,2011
[252]吴贵生,谢伟.用户创新概念及其运行机制[J].科研管理,1996(5)：14-19
[253]武瑞娟,周兴社,王海鹏,王柱.普适环境下的群体用户建模机制研究[J].计算机科学,2009.36(5)：225-228
[254]西蒙,H.管理行为(第四版)[M].北京：机械工业出版社,2007
[255]熊励,孙友霞,蒋定福,刘文.协同创新研究综述——基于实现途径视角[J].科技管理研究,2011(14)：15-18
[256]许海玲,吴潇,李晓东,阎保平.互联网推荐系统比较研究[J].软件学报,2009.20(2)：350-362
[257]姚山季,来尧静,唐娟.用户创新工具箱的研究现状与展望[J].科技管理研究,2009(2)：88-90
[258]野中郁次郎,绀野登.知识经营的魅力：知识管理与当今时代[M].中信出版社,2012
[259]雍灏,陈劲,郭斌.技术创新中的领先用户研究[J].科研管理,1999.20(3)：57-61
[260]尤海峰,王煦法.锦标赛选择交互式遗传算法及其应用[J].小型微型计算机系统,2009.30(9)：1824-1827
[261]于明玖,刘肖健,叶军,陆长德.一种基于设计空间的产品开发CAD工具分析[J].中国机械工程,2006.17(17)：1803-1806
[262]袁志发.群体遗传学、进化与熵[M].北京：科学出版社,2011：29-31
[263]曾楚宏,林丹明,朱仁宏.基于信息空间的组织学习与知识转化[J].商业经济与管理,2006(9)：29-34
[264]曾楚宏,王斌.基于信息空间的知识流动过程研究[J].情报科学,2011.29(1)：19-23
[265]张美香,陈俊杰,赵栓柱.信息过滤中用户兴趣模型的表示[J].电脑开发与应用,2005.18(5)：2-4
[266]张青山,田庆军.企业供应链的结构类型研究[J].商业研究,2002(5)：80-81
[267]张绍娟,贾存良,郭一楠.基于知识迁移的多用户交互式遗传算法[J].控制理论与应用,2007.26(10)：14-16
[268]张爽.企业内部员工知识共享动机的实证研究[D].大连：大连理工大学博士学位论文,2010
[269]张文莉,左洪福,Dieter Roller.基于自适应交互进化的设计意图驱动造型[J].中国机械工程,2006.17(4)：350-353
[270]张兴学,张朋柱.研讨群体创新及其绩效的研究评述与展望[J].系统管理学报,2009.18(1)：89-95
[271]张学龙,王道平.信任链对知识扩散的影响研究——基于二维信息空间理论[J].中科技论坛,2010(12)：93-98
[272]张永.“学习型社会”界定的反思：基于信息空间理论的视角[J].教育学报,2011.7(2)：21-27
[273]张玉臣,郭丽.基于三维空间构架的知识转移机理研究[J].情报杂志,2008(2)：104-107
[274]赵南元.认知科学与广义进化论[M].北京：清华大学出版社,1994
[275]周海燕.网络经济的信息空间理论分析[D].合肥：中国科学技术大学博士学位论文,2011
[276]周勇,巩敦卫.交互式遗传算法的噪声及降噪策略[J].控制理论与应用,2008.25(2)：223-227
[277]朱朝晖,陈劲.开放式创新的技术学习模式[M].北京：科学出版社,2008
[278]竹内弘高,野中郁次郎.知识创造的螺旋：知识管理理论与案例研究[M].知识产权出版社,2006
[2]Arrow, K. "Economic welfare and the allocation of resources for inventions" in R.R. Nelson, ed., The rate and direction of inventive acivity. Princeton Univeristy Press,1962
[3]Azevedo, C.D., Herriges, J.A., Kling, C.L. Combining Revealed and Stated Preference:Consistency Tests and Their Interpretations [J]. American Agricultural Economics Association,2003.85(3):525-537
[4]Benkler, Y. TheWealth of Networks [M]. New Haven:Yale University Press, 2006
[5]Beyer, H.G. Actuator noise in recominant evolution strategies on general quadratic fitness models[C]//Proceedings of Genetic and Evolutionary Computation Conf(GECCO2004). Seattle, WA, USA:Springer,2004: 654-665.
[6]Boisot, M.H. Is your firm a creative destroyer? Competitive learning and knowledge flows in the technological strategies of firms [J]. Research Policy, 1995.24:489-506
[7]Boisot, M.H., MacMillan, I.C. Kyeong, S.H. Explorations in Information Space [M]. London:Oxford University Press,2007
[8]Branke, J., Schmidt, C. Sequential sampling in noisy environments[M]//Lecture Notes in Computer Science. Berlin:Springer,2004: 202-211.
[9]Brownstone, D., Bunch, D.S., Train, K. Joint mixed logit models of stated and revealed preferences for alternative-fuel vehicles [J]. Transportation Research, 2000.34:315-338
[10]Chambers, J.M., Cleveland, W.S., Kleiner, B., Turkey, P.A. Graphical methods for data analysis [M]. New York:Chapman and Hall; 1983
[11]Chebrough, H. Open services innovation [M]. Jossey-Bass,2011
[12]Chesbrough, H. Managing open innovation [J]. Research Technology Management,2004.47(1):23-26
[13]Chesbrough, H. Open Innovation, the new imperative for creating and profiting from technology [M]. Harvard business school press,2003
[14]Chesbrough, H. The Era of Open Innovation [J]. MIT sloan management review,2003.44(3):35-41
[15]Cohen, W.M, Levinthal D.A. Absorptive capacity:a new perspective on learning and innovation [J]. Administrative Science Quarterly, 1990.35:128-152
[16]Connolly, T., Routhieaux, R.L., Schneider, S.K. On the effectiveness of group brainstorming:Test of an underlying cognitive mechanism [J]. Small Group Research,1993,24:490-503.
[17]Coombs, R., Metcalfe, J.S. Organizing for innovation:Co-coordinating Distributed Innovation Capabilities. In:Foss N., Mahnke V. Competence, Governance and Entrepreneurship [M]. Oxford:Oxford University Press,2002: 209-231
[18]Curado, C., Bontis, N. Parallels in knowledge cycles [J]. Computers in Human Behavior,2011.27:1438-1444
[19]DeGroot, M.H. Reaching a Consensus [J]. Journal of the American Statistical Association.1974(69):118-121
[20]Demartines, P. Herault, J. Curvilinear component analysis:a self-organizing neural network for nonlinear mapping of data set [J]. IEEE Transactions on Neural Networks,1997.8(1):148-154
[21]Devine, D.J. Effects of cognitive ability, task knowledge, information sharing, and conflict on group decision-making effectiveness [J]. Small Group Research,1999,30 (5):608-634.
[22]Dipietro, A., While, L. Applying evolutionary algorithms to problems with noisy, time-consuming fitness functions[C]//Proceedings of the 2004 Congress on Evolutionary Computation. Portland, OR, USA:[s.n.],2004:1254-1261
[23]Espino, R., Roman, C., Ortuzar, J.D.D. Analyzing demand for suburban trips: A mixed RP/SP model with latent variables and interaction effects [J]. Transportation,2006.33:241-261
[24]Frank, N., Von Hippel, E. Satisfying heterogeneous user needs via innovation toolkits:the case of apache security software [J]. Research Policy, 2003.32:1196-1215
[25]Frey, K., Liithje, C., Haag, S. Whom Should Firms Attract to Open Innovation Platforms? The Role of Knowledge Diversity and Motivation [J]. Long Range Planning 2011.44:397-420
[26]Fuller, F., Faullan, R., Matzler, K. Triggers for virtual customer integration in the development of medical equipment—From a manufacturer and a user's perspective [J]. Industrial Marketing Management,2010.39:1376-1383
[27]Fuller.J.,Jawecki.G.,Miihlbacher.H. Innovation creation by online basketball communities [J]. Journal of Business Research,2007(60):60-71
[28]Golub, B., Jackson, M.O. Naive learning in social networks:convergence, influence, and the wisdom of crowds. Available at http://www.standford.edu/-jackson/naivelearning.pdf,2007
[29]Gong, D., Zhou, Y., Li, T. Cooperative interactive genetic algorithm based on user's preference [J]. International Journal of Information Technology, 2005.11(10):1-10.
[30]Gong, DW., Guo, GS. Interactive genetic algorithms with interval fitness of evolutionary individuals [J]. Dynamics of Continuous, Discrete and Impulsive Systems, Series B,2007,14(S2):446-450.
[31]Gong, DW., Guo, GS., Lu, L., Ma, HM. Adaptive interactive genetic algorithms with individual interval fitness [J]. Progress in Natural Science, 2008.18:359-365
[32]Gong, DW., Hao, GS., Zhou, Y., Sun, XY. Interactive genetic algorithms with multi-population adaptive hierarchy and their application in fashion design [J]. Applied Mathematics and Computation,2007.185:1098-1108
[33]Grant, R.M., Barden-Fuller, C. A knowledge-based theory of inter-firm collaboration [J]. Academy of management best paper proceedings, 1995:17-21
[34]Griffiths, D., Boisot, M.H., Mole, V. Strategies for managing knowledge assets: a tale of two companies [J]. Technovation,1998.18(8/9):529-539
[35]Grijalva, T., Bohara, A.K., Berrens, R.P. A seemingly unrelated Poisson model for revealed and stated preference data [J]. Applied Economics Letters, 2003.10.443-446
[36]Gu, ZY., Tang, MX., Frazer, J.H. Capturing aesthetic intention during interactive evolution [J]. Computer-Aided Design,2006.38:224-237
[37]Guo, GS, Gong, DWi, Hao, GS, Zang, Y. Interactive Genetic Algorithms with Fitness Adjustment[J]. J. China Univ. of Mining & Tech. (English Edition), 2006.16(4):480-484
[38]Hao, GS., Huang, YQ. Fitness Noise in Interactive Evolutionary Computation and the Convergence Robustness [J]. Proceedings of the Sixth International Conference on Intelligent Systems Design and Applications (ISDA'06):2006
[39]Harhoff, D., Henkel, J., Von Hippel, E. Profiting from voluntary information spillovers:how users benefit by freely revealing their innovation [J]. Research Policy,2003.32(10):1753-1769
[40]Hasan, H., AI-hawari, M. Management styles and performance:a knowledge space framework [J]. Journal of Knowledge Management,2003.7(4)
[41]Hayashida, N., Takagi, H. Visualized IEC:interactive evolutionary computation with multidimensional data visualization[C]. Proceedings of 2000 IEEE International Conference on Industrial Electronics, Nagoya, Japan: 2000:2738-2743
[42]Henmi, S., Iwashita, S., Takagi, H. Interactive evolutionary computation with evaluation characteristics of Multi-IEC users[C].2006 IEEE International Conference on Systems, Man, and Cybernetics, Vols 1-6, Proceedings, Taipei,China:2006:3475-3480
[43]Hensher, D.A., Rose, J.M., Greene, W.H. Combining RP and SP data:biases in using the nested logit'trick'-contrasts with flexible mixed logit incorporating panel and scale effects [J]. Journal of Transport Geography,2008(16):126-133
[44]Hensher, D.S., Bradley, M. Using stated response choice data to enrich revealed preference discrete choice models [J]. Marketing Letters, 1993.4(2):139-151
[45]Herstatt, C., Von Hippel, E. From Experience:Development New Product Concept Via the Lead User Method:A Case Study in a "Low" Field[J]. The Journal of Product Innovation Management,1992,9(3):213-221
[46]Hienerth, C., Keinz, P., Lettl, C. Exploring the Nature and Implementation Process of User-Centric Business Models [J]. Long Range Planning 2011.44 344-374
[47]Holland, J. Adaptation in natural and artificial systems:an introductory analysis with application to biology, control, and artificial intelligence [M]. Cambridge:MIT Press,1992
[48]Hyvarinen, A. Survey on independent component analysis [J]. Neural Computing Surveys,1999.2:94-128
[49]Ichijo, K. Knowledge exploitation and knowledge exploration:twostrategies for knowledge creating companies. In C. Choo & N. Bontis (Eds.),The Strategic Management of Intellectual Capital and Organizational Knowledge. New York:Oxford University Press.2002:477-483
[50]Ingwersen, P. The calculation of Web Impact Factors [J]. Journal of Documentation.1998.54(2):236-243
[51]Inselberg, A., Dimsdale, B. Multi-dimensional lines I:representation and multi-dimensional lines II:proximity and applications [J]. SIAM Journal of Application Math,1994.54(2):559-596
[52]Jackson, M.O., Wolinsky, J. A strategic model of social and economic networks[J]. Journal of Economic Theory.1996.71(1):44-74
[53]Jin, Y., Branke, J. Evolutionary optimization in uncertain environments-A survey[J]. IEEE Transactions on Evolutionary Computation,2005,9(3): 303-317.
[54]Joseph, A. Schumpeter. The theory of economic development[M]. Havard University Press, (1921)1961
[55]Joshi, M., Kumar, V, Agarwal, R. Evaluating boosting algorithms to classify rare classes:comparison and improvements [C]. Proceedings of the 1st IEEE international conference on Data mining. Washington DC:IEEE Computer Society,2001:257-264
[56]Kamalian, R., Yeh, E., Zhang, Y., Agogino, A.A., Takagi, H. Reducing human fatigue in Interactive Evolutionary Computation through fuzzy systems and machine learning systems[C].2006 IEEE International Conference on Fuzzy Systems,2006:678-684
[57]Kamalian, R., Zhang, Y, Takagi, H., Agogino, A.M. Reduced human fatigue interactive evolutionary computation for micromachine design [C]. IEEE,2005:5666-5671
[58]Karacapilidis, N., Papadias, D. Computer support argumentation and collaborative decision making:the HERMES system [J]. Information Systems,2001(26):259-277.
[59]Kay, J., Kummerfeld, B., Lauder, P. Personis:A server for user models [C]. Proceedings of Adaptive Hypermedia and Adaptive Web-based Systems. London,UK:Springer-Verlag,2002
[60]Kennedy, J., Eberhart, R. Particle swarm optimization [C]. Proceedings of IEEE International Conference on Neural Networks, Piscataway:IEEE Service Center,1995:1942-1948
[61]Kennedy, J., Mendes, R. Population structure and particles swarm performance [C]. Proceedings of the IEEE Congress on Computation Intelligence,2002:1671-1675
[62]Kim, H.J. Motivations for hyperlinking in scholarly electronic articles:A qualitative study [J]. Journal of the American Society for Information Science, 2000.51(10):887-899
[63]Kim, HS, Cho, SB. Supporting serendipity:Using ambient intelligence to augment user exploration for data mining and Web browsing[J]. International Journal of Human-Computer Studies,2007.65 (5):421-433
[64]Knott, A. Exploration and exploitation as complements. In C. Choo & N.Bontis (Eds.), The Strategic Management of Intellectual Capital and OrganizationalKnowledge. New York:Oxford University Press.2002:339-358
[65]Kobsa, A. Generic user modeling systems[J]. User Modeling and User-Adapted Interaction Journal,2001.11 (1/2):49-63
[66]Kohonen,T. The self-organizing map [J]. Proceedins of the IEEE, 1990.78(9):1464-1480
[67]Kumar, M., Krishna Rao, K.V. A stated preference study for a car ownership model in the context of developing countries [J]. Transportation Planning and Technology,2006.29(5):409-425
[68]Lane, D.A, et al. Complexity Perspectives in innovation and Social Change [M]. Springer, Berlin:2009
[69]Lee, JH, Cho, SB. Analysis of direct manipulation in interactive evolutionary computation on fitness landscape [C].2002,IEEE:460-465s
[70]Lee, JY, Cho, SB. Sparse fitness evaluation for reducing user burden in interactive genetic algorithm[C]. Proc of FUZZ—IEEE'99. Seoul,1999,2: 998-1003.
[71]Lerner, J. Tirole, J. Some simple economics of open source [J]. Journal of Industrial Economics 2002.50(2):197-234
[72]Lett, C., Herstatt, C., Gemuenden, H.G. Users'Contributions to Radical Innovation:Evidence from Four Cases in the Field of Medical Equipment Technology[J]. R & D Management,2006.36 (3):251-272
[73]Lewis, T.G. Network Science:Theory and Applications [M]. John Wiley & Sons, Inc.2009:199-225
[74]Loomis, J. An investigation into the reliability of intended visitation behavior [J]. Environmental and Resource Economics,1993.3(2):183-191
[75]Loureiro, M.L., McCluskey, J.J., Mittelhammer, R.C. Are stated preferences good predictors of market behavior? [J]. Land Economics, 2003.82(4):623-640
[76]Luethje, C. Characteristics of Innovating Users Consumer Goods Field:An Empirical Study of Sport2related Product Consumer[J]. Technovation, 2004,24 (9):683-695.
[77]Lutton, E., Pilz, M., Vehel, J.L. The Fitness Map Scheme Application to interactive multifractal image denoising [J]. IEEE,2005:2278-2285
[78]Magnusson, P.R.. Exploring the contributions of involving ordinary users in ideation of technology-based services[J]. Journal of Product Innovation Management,2009 (26):578-593
[79]Mahr, D., Lievens, A. Virtual lead user communities:Drivers of knowledge creation for innovation [J]. Research Policy,2012(41):167-177
[80]Mark, J., Clayton, J., Kunz, C., Martin, A. Rapid Conceptual Design Evaluation Using a Virtual Product Model. EngngApplic. Artif lntelL, 1996.9(4):439-451
[81]Masthoff, J. Group modeling:Selecting a sequence of television items to suit a group of viewers [J]. User Modeling and User-Adapted Interaction, 2004.14(1):37-85
[82]Matsubara, Y; Nagamachi, M. Hybrid Kansei Engineering System and design support[J]. International Journal of Industrial Ergonomics,1997.19 (2):81-92
[83]Merton, R. The sociology of science [M]. Theoretical and empirical investigations. Chicago:Univeristy of Chicago Press.1973
[84]Miki, M., Hiroyasu, T., Ogawa, Y., Nagaya, Y, Yoshida, S. Effectiveness of parallel distributed model in interactive genetic algorithm [C]. The Japanese Society for Artificial Intelligence,2002
[85]Miki, M., Hiroyasu, T., Tomioka, H. Validity of the consensus building system using the parallel distributed interactive genetic algorithm [J]. Transactions of The Japanese Society for Artificial Intelligence,2005.20:289-296.
[86]Miki, M., Yamamoto,Y, Wake, S., et al. Global asynchronous distributed interactive genetic algorithm [C]. IEEE International Conference on Systems, Man and Cybernetics. Taipei,2006:3481-3485.
[87]Miles, R.E., Miles,G., Snow, C.C. Collaborative Entrepreneurship:How Communities of Networked Firms Use Continuous, Innovation to Create Economic Wealth[M]. Stanford, C.A. Stanford University Press,2005
[88]Moed, H.F. The impact-factor debate:The ISI's uses and limits [J]. Nature, 2002.415:731-732
[89]Morikawa, T. Correcting stated dependence and serial correlation in the RP/SP combined estimation method [J]. Transportation,1994.21:153-165
[90]Morrison, P.D., Roberts, J.H, von Hippel, E. Determinants of User Innovation and Innovation Sharing in a Local Market[J]. Management Science, 2000,46 (12):1513-1527.
[91]Morrison, P.D., Rorbert, J.H.,Midgley, D.F. The nature of lead users and measurement of leading edge status [J].Research Policy,2004 (33):351-362
[92]Mukhtar, M., Ismail, M.N., Yahya, Y. A hierarchical classification of co-creation models and techniques to aid in product or service design [J]. Computers in Industry,2012.63:289-297
[93]Nagamachi, M. Kansei engineering as a powerful consumer-oriented technology for product development[J]. Applied Ergonomics,2002.33 (3): 289-294
[94]Nam Pyo Suh.公理设计——发展与应用[M].北京：机械工业出版社,2004
[95]Nelson, R.R., Winter, S.G. An evolutionary theory of economic change [M]. Canbridge, Mass.:Havard University Press,1982
[96]Nojima, Y., Kojima, F., Kubota, N. Trajectory generation for human-friendly behavior of partner robot using fuzzy evaluating interactive genetic algorithm [C]. Proceedings of 2003 IEEE International Symposium on Computational Intelligence in Robotics and Automation,2003:306-311
[97]Nonaka, I. A dynamic theory of organizational knowledge creation [J]. Organization Science,1994.5(1):14-37
[98]Nonoka, I. The knowledge-creating company [J]. Harvard Business Review, 1991.69(6)
[99]Nonoka, I., Konno, N. The concept of "Ba":building a foundation for knowledge creation [J]. California Management Review,1998.40(3)
[100]Ogawa, S. Does sticky information affect the locus of innovation? Evidence from the Japanese convenience-store industry [J]. Research Policy, 1998.26:777-790
[101]Ogawa, Y., Miki, M., Hiroyasu, T., Nagaya, Y. A New Collaborative Design Method Based on Interactive Genetic Algorithms[C]. eurogen,2001
[102]Ohsaki, M, Takagi, H, Ohya, K. An input method using discrete fitness values for interactive GA[J]. J of Intelligent and Fuzzy Systems,1998,6(1):131-145.
[103]Olson, M. The logic of collective action [M]. Harvard University Press,1967
[104]Packham, I.S.J. An interactive visualisation system for engineering design using evolutionary computing [D]. PhD Thesis, University of Plymouth, December; 2003
[105]Pijl, G.J., Boven, H.P. Knowledge management as a full-grown discipline:a framework for a universal approach to knowledge management [C]. In Buhalis,D., Tjoa, A., Jafari, J. eds. Information and communication technologies in Tourism,1998:Proceedings of the international conference in Istanbul, Turkey,1998. New York:Springer-Verlalg,1998
[106]Polanyi, M. Study of man [J]. Chicago:The university of Chicago Press,1958
[107]Raymond, E. The cathedral and the bazaar [M]. O'Reilly,1999
[108]Ren, J.J. Consumptive Innovation Oriented R&D Strategy for Jewelry Industry's Product Design Techniques [J]. Communications in Computer and Information Science,2012.96:142-146
[109]Reynolds,R. G. An introduction to cultural algorithms[C]. Proceedings of the 3rd Annual Conference on Evolutionary Programming,.New Jersey: 1994:131-139
[110]Reynolds, C. Flocks, herds, and schools:a distributed behavioral model [J]. Computer Graphics,1987.21(4):25-34
[111]Reynolds, R.G., Michalewicz Z.,Cavaretta M., Using cultural algorithms for constraint handling in GENOCOP[C]. Proceedings of the 4th Annual Conference on Evolutionary Programming.1995:298-305
[112]Rothwell, R. Towards the fifth-generation Innovation Process [J]. International Marketing Review,1994.11(1):7-31
[113]Roweis, S.T., Saul, L.K. Nonlinear dimensionality analysis by locally linear embedding [J]. Science,2000.290(12):2323-2326
[114]Sanchez-Gonzalez, G., Gonzalez-Alvarez, N., Nieto, M. Sticky information and heterogeneous needs as determining factors of R&D cooperation with customers [J]. Research Policy,2009.38:1590-1603
[115]Sano, Y., Kita, H. Optimization of noisy fitness functions by means of genetic algorithms using history of search with test of estimation[C]//Proceedings of IEEE Congress on Evolutionary Computation (CEC2002). New York:Morgan Kaufmann,2002:360-365.
[116]Sawhney, M.,Verona, G, Prandelli, E. Collaborating to create:Theinternet as a platform for customer engagement in product innovation[J]. Journal of Interactive Marketing,2005.19(4):4-17
[117]Shannon, C. E. A mathematical theory of communication [J]. Bell System T echnology Journal,1948.27:379-429,623-656
[118]Shapley, L.S. A value for n-person games [J]. Annals of Mathematics Studies, 1953(28):307-317
[119]Sheth, J.N. Book Reviews:The Sources of Innovation [J] Journal of Marketing,1990,54 (1):139-141
[120]Sidney, G., Winter, S. Knowledge and Competence as Strategic Management Assets, in David J. Teece (ed), The Competitive Challenge:Strategies for Industrial Innovation and Renewal, Chapter 8, MA:Ballinger Publishing Company,1987:171-173
[121]Simonin, B.L. Ambiguity and the process of knowledge transfer in strategic alliances [J]. Strategic Management Journal,1999.20:595-623
[122]Simonin, B.L. Transfer of marketing know-how in international strategic alliances:an empirical investigation of the role and antecedents of knowledge ambiguity [J]. Journal of International Business Studies.1999.30(3):463-490
[123]Slonim, T.Y., Schneider, M. Design issues in fuzzy case-based reasoning [J]. Fuzzy Set s and Systems,2001.117(2):251-267
[124]Stewart, T.J. A critical survey on the status of multiple criteria decision making theory and practice [J]. Omega,1992.20(5/6):569-586
[125]Stigler, G. The economics of information [J]. Journal of Political Economy, 1961.69(3):213-225
[126]Sun, Y., Wang, WL., Lv, RM., Liu, XJ. Fatigue-Decreasing Oriented Study on the Evaluation Precision of IGA in Product Design Optimization [C]. Asian Conference on Design and Digital Engineering 2011(ACDDE 2011), Shanghai: 2011:103-107
[127]Szulanski, G. Exploring internal stickiness:Impediments to the transfer of best practice within the firm [J]. Strategic Management Journal, Winter Special Issue,1996.17:27-43
[128]Szulanski, G.The process of knowledge transfer:A diachronic analysis of stickiness [J]. Organizational Behavior and Human Decision Process, 2000.82(1):9-27
[129]Takagi, H. Interactive evolutionary computation:Fusion of the capabilities of EC optimization and human evaluation[C]. Proceedings of the IEEE,2001.89 (9):1275-1296
[130]Tallman, S. Global strategic management. In M. Hitt, R. Freeman,& J.Harrison (Eds.), Handbook of Strategic Management. Malden, MA: Blackwell,2001
[131]Teece, D.J. Profiting from technological innovation:Implications fro integration, collaboration, licensing and public policy [J]. Research Policy, 1986.15(6):285-305
[132]Tenenbaum, J.B., Vin de Silva, Langford, J.C. A global geometric framework for nonlinear dimensionality reduction [J]. Science,2000.290(12):2319-2323
[133]Thelwall, M. Link Analysis:An Information Science Approach[M]. Elsevier Inc.2004
[134]Thomke, S. Enlighted Experimentation:The New Imperative for Innovation[J]. Harvard Business Review,2001,79 (2):67-75
[135]Thomke, S., Von Hippel, E. Customers as innovators[J]. Harvard Business Review,2002,80(4):74-84
[136]Todoroki, Takagi, H. User interface of an interactive evolutionary computation for speech processing[C].6th Int Conf on Soft Computing. Iizuka,2000: 112-118.
[137]Torgerson, W.S. Multidimensional scaling Ⅰ:theory and method [J]. Psychometrika,1952.17:401-419
[138]Urban, G.L., Von Hippel, E., Lead User Analyses for the Development of New Industrial Products [J]. Management Science,1988.34(5):569-582
[139]URL:http://baike.baidu.com/view/48146.htm
[140]URL:http://baike.baidu.com/view/729695.htm
[141]URL:http://secondlife.com/
[142]URL:http://Threadless.com
[143]URL:http://www.Fluevog.com
[144]URL:http://www.zhubajie.com
[145]URL:http://www.avant-lab.com/GUCI.html
[146]URL:http://www.scriptspot.com
[147]URL:http://www.threadless.com
[148]URL: http://zh.wikipedia.org/wiki/%E4%BA%91%E8%AE%A1%E7%AE%97
[149]Van Raan, A.F.J. The Pandora's box of citation analysis:Measuring scientific excellence the last evil? In:Cronin,B.& Atkins, H.B. (Eds). The web of knowledge:a festschrift in honor of Eugene Garfield. Metford, NJ: Information Today Inc. ASIS Monograph Series,2000:301-319
[150]Verhoef, P.C., Franses, P.H., Combining revealed and stated preferences to forecast customer behavior:three case studies [J]. International Journal of Market Research,2003.45:467-474
[151]Von Hippel, E. "Sticky Information"and the Locus of Problem Solving: Implications for Innovation [J], Management Science,1994,40 (4):429-439
[152]Von Hippel, E. Democratizing Innovation [M]. Cambridge:MIT Press,2005.
[153]Von Hippel, E. Economics of Product Development by Users:The Impact of Sticky"Local Information[J]. Management Science,1998.44(5):629-644
[154]Von Hippel, E. Perspective:User Toolkits for Innovation [J]. The Journal of Product Innovation Management,2001,18:247-257
[155]Von Hippel, E., Democratizing Innovation Cambridge[M]. MA:MIT Press, 2005.
[156]Von Hippel, E., Katz, R. Shifting innovation to users via toolkits[J]. Management Science,2002,48 (7):821-833
[157]Von Hippel, E., The Dominant Role of the Users in Semiconductor and Electronic Subassembly Process Innovation [J]. IEEE Transactions on Engineering Management,1977.24(2):60-71
[158]Von Hippel, E., The Sources of Innovation [M]. Oxford University Press, New York,1988.
[159]Von Hippel, E., Thomke, S., Sonnack, M., Creating Breakthroughs at 3M[J]. Health Forum Journal,2000,43 (4):20-26
[160]Von Hippel, E.,. Lead Users:A Source of Novel Product Concepts [J]. Management Science,1986(32):791-805
[161]Von Hippel,E.,The Dominant Role of Users in the Scientific Instrument Innovation Process [J]. Research Policy,1976.5(3):212-239
[162]Wang, YM. On fuzzy multi attribute decision making models and methods with incomplete preference information [J]. Fuzzy Sets and Systems, 2005,151(2):285-301
[163]Williams, K. O'Reilly C. The complexity of diversity:A review of forty years of research[J]. Research in Organizational Behavior,1998,20:77-140.
[164]敖成龙,苏英,龚元明.基于相似度的复杂数据对象比较[J].北京理工大学学报,2003,23(5)：593-595
[165]柏格森,亨利.创造进化论[M].凤凰出版传媒集团,2011
[166]保罗.拉索.图解思考——建筑表现技法[M].北京：中国建筑工业出版社,2002
[167]鲍尔,P.预知社会：群体行为的内在法则[M].当代中国出版社,2010
[168]伯特,R.结构洞：竞争的社会结构[M].格致出版社,上海人民出版社,2008：34-35
[169]博伊索特,M.H.知识资产：在信息经济中赢得竞争优势[M].上海：上海人民出版社,2004
[170]布坎南,M.隐藏的逻辑[M].The Garamond Agency, Inc,2007
[171]布瓦索,M.H.信息空间：认识组织、制度和文化的一种框架[M].上海：上海译文出版社,2000
[172]曹毅,贺卫红.基于用户兴趣的混合推荐模型[J].系统工程,2009.27(6)：68-72
[173]曹振飞.网络社会生态系统中信息流动的模型研究[J].技术与创新管理,2010.31(6)：684-688
[174]常宝,储雪林,李红艳.试论粘滞知识及其管理对策[J].科学学研究,2005.23(2)：23-26
[175]陈劲,龚焱,雍灏.技术创新信息源新探：领先用户研究[J].中国软科学,2001(1)：86-88
[176]陈劲,王鹏飞.选择性开放式创新---以中控集团为例[J].软科学,2011.25(2)：112-115
[177]陈劲,阳银娟.协同创新的理论基础与内涵[J].科学学研究,2012.30(2)：161-164
[178]陈钰芬,陈劲.开放式创新：机理与模式[M].科学出版社,2008
[179]陈钰芬,陈劲.用户参与创新：国外相关理论文献综述[J].科学学与科学技术管理,2007(2)：52-56
[180]崔志华,曾建潮.微粒群优化算法[M].北京：科学出版社,2011
[181]戴凌燕,陈劲.产品创新的新范式：用户创新[J].经济管理,2003(12)：16-20
[182]董艳,张大亮,徐伟青.用户创新的条件和范式研究[J].浙江大学学报(人文社会科学版),2009.39(4)：43-54
[183]董艳,张大亮,徐伟青.基于创新方式的用户创新资源开发策略研究[J].科技进步与对策,2010.27(9)：22-25
[184]冯.希普尔,E.技术创新的源泉[M].柳卸林译.北京：科学技术文献出版社,1997
[185]冯.希普尔,E.民主化创新[M].北京：知识产权出版社,2007
[186]高忠义,王永贵.用户创新及其管理现状与展望[J].外国经济与管理,2006.28(4)：40-47
[187]耿新,彭留英.企业知识的分类、分布于转化机制研究[J].管理科学,2004(4)：43-48
[188]龚艳冰,丁德臣,何建敏.一种基于直觉模糊集相似度的多属性决策方法[J].控制与决策,2009,24(9)：1398-1401
[189]巩敦卫,郝国生,严玉若.交互式遗传算法基于用户认知不确定性的定向变异[J].控制与决策,2010.25(1)：74-78
[190]巩敦卫,郝国生,周勇,郭一楠.交互式遗传算法原理及其应用[M].北京：国防工业出版社,2007
[191]巩敦卫,任洁,孙晓燕.区间适应值交互式遗传算法神经网络代理模型[J].控制与决策,2009.24(10)：1522-1525
[192]巩敦卫,孙晓燕,任洁.基于联赛评价和知识提取的交互式遗传算法[J].山东大学学报(工学版),2009.39(2)：1-7
[193]巩敦卫,孙晓燕.协同进化遗传算法理论及应用[M].北京：科学出版社2009
[194]巩敦卫,周勇,郭一楠.基于多近似模型的交互式遗传算法[J].控制理论与应用,2008.25(3)：434-438
[195]古斯塔夫.勒庞.乌合之众[M].新世界出版社,2011
[196]古斯塔夫.勒庞.心理学统治世界[M].金城出版社,2011
[197]关庆珍,周竹荣.基于Ontology的用户模型研究[J].计算机应用,2007.27(10)：2504-2507
[198]哈肯,H.信息与自组织[M].成都：四川教育出版社,1988
[199]郝国生,史有群,黄永青等.交互式进化计算的适应值噪声及收敛鲁棒性[J].软件学报,2007.18(9)：2183-2193
[200]何国正,陈荣秋.消费品行业领先用户识别方法研究[J].统计与决策,2009(4)：15-17.
[201]何国正.基于领先用户的顾客参与新产品研发研究[D].武汉：华中科技大学博士论文,2008
[202]亨利·切萨布鲁夫,维姆·范哈佛贝克,乔·韦斯特.开放创新的新范式[M].北京：科学出版社,2010
[203]黄永青,张祥德.交互式进化计算研究进展[J].控制与决策,2010.25(9)：1281-1286
[204]蒋姗姗,曹先彬,王煦法.基于IGA的用户Agent模型与设计[J].模式识别与人工智能,2004.17(2)：244-249.
[205]蒋占四,陈立平,罗年猛.最近邻实例检索相似度分析[J].计算机集成制造系统,2007,13(6)：1165-1168
[206]杰夫.豪.众包[M].北京：中信出版社,2011
[207]金英,苏萌.消费者自述偏好与实际选择的矛盾：中国汽车市场的实证研究[J].管理世界,2010(1)：98-106
[208]卡尔.波普尔.客观知识：一个进化论研究[M].上海：上海译文出版社,2001
[209]科林.F.凯莫勒,乔治.罗文斯坦,马修.拉宾.行为经济学新进展[M].北京：中国人民大学出版社,2010
[210]莱昂.瓦尔拉斯.纯粹经济学要义：或社会财富论[M].北京：商务印书馆,1989
[211]李德毅.云计算技术发展报告[M].北京：科学出版社,2011
[212]李刚,刘益.国内外企业知识转移的研究现状分析[J].情报杂志,2007(9)：10-13
[213]李红玲,廖建桥.从Shannon-Weaver到Boisot:解读国外若干典型知识转移模型[J].科技管理研究,2008(4)：243-249
[214]李景峰.企业知识运动研究——创新视野中的企业知识协同演化[D].太原：山西大学管理学院博士学位论文,2008
[215]李兆军.资本市场信息空间的路径选择[D].天津：天津财经大学博士学位论文,2008
[216]梁昌勇,蔡美菊,陆青.面向隐性目标优化的改进小生境遗传算法及其在汽车造型设计中的应用[J].中国管理科学,2011.19(1)：126-134
[217]刘合翔.“信息空间”理论视角下的信息服务产业界定与划分[J].图书情报工作,2010.54(22)：47-50
[218]刘树林,席酉民.年龄与群体创建决策方案数量和质量的实验研究[J].控制与决策,2002,17卷增刊：798-801.
[219]刘潇,孙强,王秀坤.一种改进的最优保存人机交互遗传算法[J].辽宁师范大学学报(自然科学版),2004.27(2)：168-171
[220]刘肖健.机电产品计算机辅助形态设计中的人机工程设计方法研究[D].西安：西北工业大学博士学位论文,2005
[221]路易斯(Lewis, T.G.).网络科学——原理与应用[M].北京：机械工业出版社,2011
[222]马峻.创新设计的系统与决策技术[M].北京：科学出版社,2008
[223]马克.格兰诺维特.找工作：关系人与职业生涯的研究[M].上海：上海人民出版社,2008
[224]玛格丽特.博登.人工智能哲学[M].上海：上海译文出版社,2001
[225]马修·O·杰克逊(Jackson, M.O.).社会与经济网络[M].北京：中国人民大学出版社,2011
[226]彭冬梅,刘肖健,孙守迁.信息视角：非物质文化遗产保护的数字化理论[J].计算机辅助设计与图形学学报,2008.20(1)：119-125
[227]齐岩,卢德唐.交互式遗传算法在基于内容的图像检索中的应用[J].中国图象图形学报,2004.9(1)：46-55
[228]任晓,杨锡怀,邹家兴.基于组合相似度的混合多指标信息聚类分析方法[J].东北大学学报(自然科学版),2010,31(11)：1657-1660
[229]芮明杰,李鑫,任红波.高技术企业知识创新模式研究[J].外国经济与管理,2004(5)：8-12
[230]瑞萨电子与Morpho公司共同开发出可通过手势操控家电的人机交互技术[J].中国电子商情,2010(7)：74
[231]萨缪尔森,保罗.经济分析基础[M].大连：东北财经大学,2006
[232]上海财经大学高等教育研究所.诺贝尔经济学奖之路[M].上海财经大学出版社,2010
[233]盛小平,吴菁.知识管理流派浅析[J].国家图书馆学刊,2007.1：55-61
[234]盛小平,吴菁.知识管理流派浅析(续)[J].国家图书馆学刊,2007.2：53-57
[235]施蒂格勒,J.乔治.施蒂格勒回忆录：一个自由主义经济学家的自白[M].北京：中信出版社,2006
[236]宋东明,朱耀琴,,吴慧中.基于交互式遗传算法模型的群体论证方法[J]. 中国工程科学,2009.11(11)：64-69
[237]宋媛媛,孙坦.个性化推荐系统中的用户模型问题[J].图书馆杂志,2004.23(12)：53-56
[238]孙晓燕,巩敦卫.自适应分区多代理模型交互式遗传算法[J].控制与决策,2009.24(2)：170-175
[239]孙晓燕,王煦法,巩敦卫.分布协同交互式遗传算法及其在群体决策中的应用[J].信息与控制,2007.36(5)：557-561
[240]孙艳,刘肖健,王万良.创新性与满意度融合的用户创新方法及其在产品外观优化中的应用[J].计算机辅助设计与图形学学报,2012.24(7)：954-960
[241]孙艳,刘肖健.研发团队与产品创新的协同进化机制研究[J].科技与管理,2006.40(6)：113-119
[242]泰普斯科特,D.维基经济学[M].中国青年出版社,2011
[243]托夫勒,A.,托夫勒,H.财富的革命[M].中信出版社,2006
[244]托夫勒,A.第三次浪潮[M].中信出版社,2005
[245]瓦茨,D.J.六度分隔：一个相互连接的时代的科学[M].中国人民大学出版社,2011
[246]汪丁丁.知识社会与知识资产问题in财富的革命[M].中信出版社,2006
[247]王毅.粘滞知识转移研究评述[J].科研管理,2005.26(2)：71-75
[248]王永贵,姚山季,司方来,马双.组织顾客创新、供应商反应性与项目绩效的关系研究：基于组织服务市场的实证分析[J].南开管理评论,2011.14(2)：4-13
[249]王志伟.企业外部知识网络嵌入性对破坏性创新绩效的影响机制研究[D].浙江大学,2010
[250]魏学成,李文涛.基于改进Shapley值法的供应链联盟利益分配研究[J].决策参考,2010(23)：53-55
[251]文卡特.托马斯瓦米,弗朗西斯.高哈特.众包：群体创造的力量[M].北京：中信出版社,2011
[252]吴贵生,谢伟.用户创新概念及其运行机制[J].科研管理,1996(5)：14-19
[253]武瑞娟,周兴社,王海鹏,王柱.普适环境下的群体用户建模机制研究[J].计算机科学,2009.36(5)：225-228
[254]西蒙,H.管理行为(第四版)[M].北京：机械工业出版社,2007
[255]熊励,孙友霞,蒋定福,刘文.协同创新研究综述——基于实现途径视角[J].科技管理研究,2011(14)：15-18
[256]许海玲,吴潇,李晓东,阎保平.互联网推荐系统比较研究[J].软件学报,2009.20(2)：350-362
[257]姚山季,来尧静,唐娟.用户创新工具箱的研究现状与展望[J].科技管理研究,2009(2)：88-90
[258]野中郁次郎,绀野登.知识经营的魅力：知识管理与当今时代[M].中信出版社,2012
[259]雍灏,陈劲,郭斌.技术创新中的领先用户研究[J].科研管理,1999.20(3)：57-61
[260]尤海峰,王煦法.锦标赛选择交互式遗传算法及其应用[J].小型微型计算机系统,2009.30(9)：1824-1827
[261]于明玖,刘肖健,叶军,陆长德.一种基于设计空间的产品开发CAD工具分析[J].中国机械工程,2006.17(17)：1803-1806
[262]袁志发.群体遗传学、进化与熵[M].北京：科学出版社,2011：29-31
[263]曾楚宏,林丹明,朱仁宏.基于信息空间的组织学习与知识转化[J].商业经济与管理,2006(9)：29-34
[264]曾楚宏,王斌.基于信息空间的知识流动过程研究[J].情报科学,2011.29(1)：19-23
[265]张美香,陈俊杰,赵栓柱.信息过滤中用户兴趣模型的表示[J].电脑开发与应用,2005.18(5)：2-4
[266]张青山,田庆军.企业供应链的结构类型研究[J].商业研究,2002(5)：80-81
[267]张绍娟,贾存良,郭一楠.基于知识迁移的多用户交互式遗传算法[J].控制理论与应用,2007.26(10)：14-16
[268]张爽.企业内部员工知识共享动机的实证研究[D].大连：大连理工大学博士学位论文,2010
[269]张文莉,左洪福,Dieter Roller.基于自适应交互进化的设计意图驱动造型[J].中国机械工程,2006.17(4)：350-353
[270]张兴学,张朋柱.研讨群体创新及其绩效的研究评述与展望[J].系统管理学报,2009.18(1)：89-95
[271]张学龙,王道平.信任链对知识扩散的影响研究——基于二维信息空间理论[J].中科技论坛,2010(12)：93-98
[272]张永.“学习型社会”界定的反思：基于信息空间理论的视角[J].教育学报,2011.7(2)：21-27
[273]张玉臣,郭丽.基于三维空间构架的知识转移机理研究[J].情报杂志,2008(2)：104-107
[274]赵南元.认知科学与广义进化论[M].北京：清华大学出版社,1994
[275]周海燕.网络经济的信息空间理论分析[D].合肥：中国科学技术大学博士学位论文,2011
[276]周勇,巩敦卫.交互式遗传算法的噪声及降噪策略[J].控制理论与应用,2008.25(2)：223-227
[277]朱朝晖,陈劲.开放式创新的技术学习模式[M].北京：科学出版社,2008
[278]竹内弘高,野中郁次郎.知识创造的螺旋：知识管理理论与案例研究[M].知识产权出版社,2006
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