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Impact of Crowdsourcee’s Vertical Fairness Concern on the Crowdsourcing Knowledge Sharing Behavior and Its Incentive Mechanism

ZHU Binxin · LEON Williams · PAUL Lighterness · GAO Peng   

  1. ZHU Binxin
    School of Management, Jiangsu University, Zhenjiang 212013, China; Centre for Competitive Creative Design,Cranfield University, Bedfordshire MK43 0AL, UK. Email: zhubinxin44@163.com.
    LEON Williams (Corresponding author) · PAUL Lighterness
    Centre for Competitive Creative Design, Cranfield University, Bedfordshire MK43 0AL, UK.
    Email: l.williams@cranfield.ac.uk; paul.lighterness@cranfield.ac.uk.
    GAO Peng
    School of Business, Jiangsu University of Technology, Changzhou 213001, China. Email: gaopeng@jsut.edu.cn.
  • Online:2021-06-25 Published:2021-03-11

ZHU Binxin · LEON Williams · PAUL Lighterness · GAO Peng. Impact of Crowdsourcee’s Vertical Fairness Concern on the Crowdsourcing Knowledge Sharing Behavior and Its Incentive Mechanism[J]. Journal of Systems Science and Complexity, 2021, 34(3): 1102-1120.

This paper examines in detail the impact of the crowdsourcee’s vertical fairness concern on the knowledge sharing incentive mechanism in crowdsourcing communities. The conditions for the establishment of the incentive mechanism are analyzed and the impact of fairness concern sensitivity on expected economic revenues of both sides as well as the crowdsourcing project performance is studied by game theory and computer simulation. The results show that the knowledge sharing incentive mechanism can only be established if the ratio between the performance improvement rate and the private cost reduction rate caused by shared knowledge is within a certain range. The degree of the optimal linear incentives, the private solution efforts, and the improvement of knowledge sharing level are positively correlated with the sensitivity of vertical fairness concern. In the non-incentive mode, the ratio between the performance conversion rate of private solution effort and the performance conversion rate of knowledge sharing effort plays an important role in moderating a crowdsourcing project’s performance. The authors find that the number of participants is either conducive or nonconducive to the improvement of performance. The implementation of knowledge sharing incentive can achieve a win-win situation for both the crowdsourcer and the crowdsourcee.

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