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Dynamic perspectives on social characteristics and sustainability in online community networks

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  • Peter Otto
  • Martin Simon

Abstract

Online community networks can help organizations improve collaboration. However, in spite of their potential value, there has been little empirical research into two important network factors that determine their success: social characteristics of users and changes in operations that result from network evolution. Our research addresses these deficiencies by using a cultural framework. Derived from anthropology, it extends previous system dynamics research on online community networks. The framework acts as a lens, enabling a better understanding of the effects that changes in these factors bring to online community networks. Using data collected from Wikipedia for model calibration, our findings suggest that, contrary to conventional wisdom, removing policies that focus on building group commitment does not lower performance. The results also show that online networks need structural control, otherwise their attractiveness, credibility and, subsequently, content value might all decrease. To ensure sustainability the network must be monitored, especially during the early stages of its evolution, so that rules and regulations that ensure value and validity can be selectively employed. Copyright © 2008 John Wiley & Sons, Ltd.

Suggested Citation

  • Peter Otto & Martin Simon, 2008. "Dynamic perspectives on social characteristics and sustainability in online community networks," System Dynamics Review, System Dynamics Society, vol. 24(3), pages 321-347, September.
    • Handle: RePEc:bla:sysdyn:v:24:y:2008:i:3:p:321-347
    DOI: 10.1002/sdr.403
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    References listed on IDEAS

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    Cited by:

    1. Stanislava Mildeová & Martin Dalihod, 2017. "Systems Approach to Scientific Investigation in Informatics [Systémový přístup k vědeckému zkoumání v informatice]," Acta Informatica Pragensia, Prague University of Economics and Business, vol. 2017(1), pages 60-69.
    2. Nicolas Jullien, 2012. "What We Know About Wikipedia: A Review of the Literature Analyzing the Project(s)," Post-Print hal-00857208, HAL.
    3. Li, Libo & Yu, Huan & Kunc, Martin, 2024. "The impact of forum content on data science open innovation performance: A system dynamics-based causal machine learning approach," Technological Forecasting and Social Change, Elsevier, vol. 198(C).

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