Crowdsourcing contest platforms have become a popular approach to solving organizational problems through access to global knowledge and expertise. The basis for crowdsourcing being generative of the high-quality solution is the value of expertise diversity from the participants. However, whether the incentive effect of peer recognition will still work in crowdsourcing “co-opetition” remains unclear. In response to the call for unpacking the co-opetition paradox, we conducted our research on the basis of crowdsourcing “co-opetition” and considered both the competitive and cooperative attributes of co-opetition. Our research extends the current understanding of knowledge exchange from a collaborative community further to a “co-opetitive” community with the consideration of competitive features and sheds light on the intrinsic and extrinsic motivators for knowledge exchange that works under a competitive environment.
Wang, Xin; Hou, Wanfang; and XUE, Yiwen, "Antecedents of Knowledge Sharing & Seeking Binary Behaviour in Crowdsourcing Contest" (2022). PACIS 2022 Proceedings. 275.
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