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How to facilitate knowledge collaboration in OCs: An integrated perspective of technological and institutional measures

Author

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  • Yang, Wei
  • Zhou, Qing
  • Yu, Xianyun
  • Wang, Dongpeng
  • Li, Hui

Abstract

Knowledge collaboration in online communities (OCs) is popular and important for companies who are aiming to survive in the digital age, but it has a high failure rate. Most of the existing research and practice have focused only on facilitating knowledge collaboration in OCs through institutional measures, neglecting the role of technological measures. This paper aims to fill this gap by employing a differential equation model as well as case analyses. The research results indicate that increasing knowledge sharing by institutional measures does not lead to knowledge collaboration without continuously advancing technology. It is necessary to simultaneously employ technological and institutional measures. Companies can select a technology-oriented strategy or institution-oriented strategy according to their available resources and strategic positioning. These research results are helpful for remedying the imbalance of existing research and some shortages in practice.

Suggested Citation

  • Yang, Wei & Zhou, Qing & Yu, Xianyun & Wang, Dongpeng & Li, Hui, 2019. "How to facilitate knowledge collaboration in OCs: An integrated perspective of technological and institutional measures," Technological Forecasting and Social Change, Elsevier, vol. 138(C), pages 21-28.
    • Handle: RePEc:eee:tefoso:v:138:y:2019:i:c:p:21-28
    DOI: 10.1016/j.techfore.2018.10.030
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    References listed on IDEAS

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    1. Stam, Wouter, 2009. "When does community participation enhance the performance of open source software companies?," Research Policy, Elsevier, vol. 38(8), pages 1288-1299, October.
    2. Zeng, Michael A., 2018. "Foresight by online communities – The case of renewable energies," Technological Forecasting and Social Change, Elsevier, vol. 129(C), pages 27-42.
    3. Samer Faraj & Sirkka L. Jarvenpaa & Ann Majchrzak, 2011. "Knowledge Collaboration in Online Communities," Organization Science, INFORMS, vol. 22(5), pages 1224-1239, October.
    4. Chen, Peng-Ting & Kuo, Shu-Chen, 2017. "Innovation resistance and strategic implications of enterprise social media websites in Taiwan through knowledge sharing perspective," Technological Forecasting and Social Change, Elsevier, vol. 118(C), pages 55-69.
    5. Bonaccorsi, Andrea & Rossi, Cristina, 2003. "Why Open Source software can succeed," Research Policy, Elsevier, vol. 32(7), pages 1243-1258, July.
    6. Yan Chen & F. Maxwell Harper & Joseph Konstan & Sherry Xin Li, 2010. "Social Comparisons and Contributions to Online Communities: A Field Experiment on MovieLens," American Economic Review, American Economic Association, vol. 100(4), pages 1358-1398, September.
    7. David, Paul A. & Shapiro, Joseph S., 2008. "Community-based production of open-source software: What do we know about the developers who participate?," Information Economics and Policy, Elsevier, vol. 20(4), pages 364-398, December.
    8. Allen, Robert C., 1983. "Collective invention," Journal of Economic Behavior & Organization, Elsevier, vol. 4(1), pages 1-24, March.
    9. Lauto, Giancarlo & Valentin, Finn, 2016. "The knowledge production model of the New Sciences: The case of Translational Medicine," Technological Forecasting and Social Change, Elsevier, vol. 111(C), pages 12-21.
    10. Olivier Toubia & Andrew T. Stephen, 2013. "Intrinsic vs. Image-Related Utility in Social Media: Why Do People Contribute Content to Twitter?," Marketing Science, INFORMS, vol. 32(3), pages 368-392, May.
    11. Muñoz, Pablo & Cohen, Boyd, 2017. "Mapping out the sharing economy: A configurational approach to sharing business modeling," Technological Forecasting and Social Change, Elsevier, vol. 125(C), pages 21-37.
    12. Soumya Ray & Sung S. Kim & James G. Morris, 2014. "The Central Role of Engagement in Online Communities," Information Systems Research, INFORMS, vol. 25(3), pages 528-546, September.
    13. Paulo B. Goes & Chenhui Guo & Mingfeng Lin, 2016. "Do Incentive Hierarchies Induce User Effort? Evidence from an Online Knowledge Exchange," Information Systems Research, INFORMS, vol. 27(3), pages 497-516, September.
    14. Sims, Julian M., 2018. "Communities of practice: Telemedicine and online medical communities," Technological Forecasting and Social Change, Elsevier, vol. 126(C), pages 53-63.
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    Cited by:

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    2. Zhang, Xi & Cheng, Yihang & Chen, Aoshuang & Lytras, Miltiadis & de Pablos, Patricia Ordóñez & Zhang, Renyu, 2022. "How rumors diffuse in the infodemic: Evidence from the healthy online social change in China," Technological Forecasting and Social Change, Elsevier, vol. 185(C).
    3. Xiao Yu & Yangfeng Dai & Qian Xu & Qilin Ye, 2024. "Knowledge Collaboration and Benefits of Standard Implementation of Enterprise in Technology Standard Alliance," Journal of the Knowledge Economy, Springer;Portland International Center for Management of Engineering and Technology (PICMET), vol. 15(2), pages 8534-8562, June.

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