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Measuring and Analyzing the Openness of the Web2.0 Service Network for Improving the Innovation Capacity of the Web2.0 System through Collective Intelligence

Conference paper
Part of the Advances in Intelligent and Soft Computing book series (AINSC, volume 76)

Abstract

Web2.0 users can create new services by combining existing Web2.0 services that offer open programming interfaces. This system of service composition forms a network, which we call the Web2.0 service network. A node of the Web2.0 service network represents a service. A link between two nodes exists, if another Web2.0 service (i.e. mashup) uses the linked services. The Web2.0 service network can be understood as an innovation system that creates value through the composition of services, representing the collective intelligence of users. Within this paper, we analyze the openness of the Web2.0 service network. Openness, which is an indicator for the innovation potential of a network, is measured using the Enhanced-EIS-Indexes. These indexes are based on Krackhardt and Stern’s EI-Index. The analysis results of the indexes show that the Web2.0 service network is not as open as the evolutionary analysis of the Web2.0 service network suggested. The slight closeness of the Web2.0 service network has been identified by the Agent Behavior Index EIS a , which highlighted that relatively more links are created within subgroups than between subgroups. It indicates that factors such as service ownership and type of service have an impact on innovation within the network.

Keywords

Social network analysis index network science subgroup structure Web2.0 system service composition collective intelligence Web2.0 service network performance evaluation innovation empirical data analysis 

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References

  1. 1.
    O’Reilly, T.: What is Web2.0: Design Patterns and Business Models for the Next Generation of Software. Communications & Strategies 65, 17–37 (2007)Google Scholar
  2. 2.
    Ferris, C., Farrel, J.: What are Web Services? Communications of the ACM 46 (2003)Google Scholar
  3. 3.
    Gloor, P., Cooper, S.: Coolhunting: Chasing Down the Next Big Thing. AMACOM, New York (2007)Google Scholar
  4. 4.
    Hwang, J., Altmann, J., Kim, K.: The Structural Evolution of the Web2.0 Service Network. Online Information Review 33, 1040–1067 (2009)CrossRefGoogle Scholar
  5. 5.
    Castilla, E.J., Hwang, H., Granovetter, E., Granovetter, M.: Social Networks in Silicon Valley. In: Lee, C.M., Miller, W.F., Hancock, M.G., Rowan, H.S. (eds.) The Silicon Valley Edge: A Habitat for Innovation and Entrepreneurship. Stanford University Press, California (2000)Google Scholar
  6. 6.
    Chesbrough, H.W.: Open Innovation: The New Imperative for Creating and Profiting from Technology. Harvard Business School Press, Boston (2003)Google Scholar
  7. 7.
    Gawer, A., Cusumano, M.A.: Platform Leadership: How Intel, Microsoft, and Cisco Drive Industry Innovation. Harvard Business School Press, Boston (2002)Google Scholar
  8. 8.
    Henkel, J.: Selective Revealing in Open Innovation Processes: The Case of Embedded Linux. Res. Policy 35, 953–969 (2006)CrossRefGoogle Scholar
  9. 9.
    Ethraj, S.K.: Allocation of Inventive Effort in Complex Product Systems. Strategic Management Journal 28, 563–584 (2007)CrossRefGoogle Scholar
  10. 10.
    Kim, K., Altmann, J., Hwang, J.: The Impact of the Subgroup Structure on the Evolution of Networks - An Economic Model of Network Evolution. NetSciCom. In: IEEE Intl. Workshop on Network Science for Communication Networks, IEEE Infocom 2010, USA (2010)Google Scholar
  11. 11.
    Scott, J.: Social Network Analysis: A Handbook. Sage Publication, London (1991)Google Scholar
  12. 12.
    Wasserman, S., Faust, K.: Social Network Analysis: Methods and Applications. Cambridge University Press, Cambridge (1994)Google Scholar
  13. 13.
    Burt, R.S.: Brokerage and Closure: An Introduction to Social Capital. Oxford University Press, Oxford (1994)Google Scholar
  14. 14.
    Lin, N.: Social Capital: A Theory of Social Structure and Action. Cambridge University Press, Cambridge (2001)Google Scholar
  15. 15.
    Walter, J., Lechner, C., Kellermanns, F.W.: Knowledge Transfer between and within Alliance Partners: Private Versus Collective Benefits of Social Capital. Journal of Business Research 60, 698–710 (2007)CrossRefGoogle Scholar
  16. 16.
    Krackhardt, D., Stern, R.N.: Informal Networks and Organizational Crises: An Experimental Simulation. Social Psychology Quarterly 51, 123–140 (1988)CrossRefGoogle Scholar
  17. 17.
    Müller-Prothmann, T., Siegbert, A., Finke, I.: Inter-Organizational Knowledge Community Building: Sustaining or Overcoming Organizational Boundaries? Journal of Universal Knowledge Management 0, 39–49 (2005)Google Scholar
  18. 18.
    Julsrud, T.E.: Core/Periphery Structures and Trust in Distributed Work Groups: A Comparative Case Study. Structure and Dynamics: eJournal of Anthropological and Related Science 2, 1–30 (2007)Google Scholar
  19. 19.
    Flew, T.: New Media: An Introduction. Oxford University Press, Melbourne (2008)Google Scholar
  20. 20.
    Tapscott, D., Williams, A.D.: Wikinomics: How Mass Collaboration Changes Everything. Penguin Group, USA (2008)Google Scholar
  21. 21.
    Feiler, J.: How to do Everything with Web2.0 Mashups. McGraw-Hill, New York (2008)Google Scholar
  22. 22.
    Yee, R.: Pro Web2.0 Mashups: Remixing Data and Web Services. Apress (2008)Google Scholar
  23. 23.
    Lévy, P.: From Social Computing to Reflexive Collective Intelligence: The IEML Research Program. Information Sciences 180, 71–94 (2010)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  1. 1.Technology Management, Economics and Policy Program, Department of Industrial Engineering, College of EngineeringSeoul National UniversitySeoulSouth-Korea

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