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| Research on the Impact of Participant's Fairness Preference on Incentive Mechanism of Collaborative Crowdsourcing Innovation Performance |
| Huang Ting,Zhu Binxin,Ma Zhiqiang |
| (School of Management, Jiangsu University, Zhenjiang 212013, China) |
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Abstract Collaborative crowdsourcing innovation is a crowdsourcing model that aims to maximize innovation performance, and relevant practice cases have emerged nowadays. However, the efforts of the participants in the collaborative crowdsourcing innovation process are often influenced by their fairness preference. In response to this problem, the principal-agent theory is used to design two incentive mechanisms based on individual innovation performance (AR) and total innovation performance (TR) to improve the performance of collaborative crowdsourcing innovation, and to explore the value of fairness preference to incentive mechanism. The results show that participants in the AR mechanism are unlikely to have altruistic efforts, while self-interested efforts and altruistic efforts under the TR mechanism are negatively correlated with fairness preferences;under the two incentive mechanisms, the performance of crowdsourcing innovation decreases with the increase of the sensitivity of fairness preference, whether the increase in the number of participants is conducive to the improvement of crowdsourcing innovation performance depends on the degree of fairness preference;the TR mechanism will certainly produce higher crowdsourcing performance than the AR mechanism and the economic benefits of the crowdsourcer, but this value effect will be weakened by the participants' fairness preference.
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Received: 28 May 2019
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