Psychological Game Analysis for Crowdsourcing with Reciprocity

Abstract

Incentive mechanism design in crowdsourcing is a trending topic. Advanced research attempts to tackle this issue from a game-theory perspective, modeling workers’ and requestor’s material utility functions. Besides material benefits, studies have shown that the intrinsic rewards (psychological factors) were also part of the workers’ non-negligible motivation. However, previous works only mention this discovery textually, rather than quantifying their models’ psychological factors. To fill this blank, we utilize the psychological game theory to analyze the crowdsourcing process. With mathematical ways, we first show that the requestor could reduce the cost of compensation via psychology methods, substituting partial monetary rewards with psychological payoffs. Furthermore, when workers are reciprocal and risk-neutral about expected earnings, we prove that the related incentive plan is requestor’s optimal choice. In particular, we find the workers’ psychological payoffs and requestor’s cost in equilibrium. Finally, we conduct a simulation to illustrate our findings intuitively. Therefore, our unique psychological crowdsourcing model provides a promising detour for incentive mechanism design in crowdsourcing scenarios.