Research on Incentive Strategy of Crowdsourcing Prize Quantity Based on MOA theory

Abstract

Crowdsourcing is a new mode for enterprises to solve business problems with the help of external network intelligence resources. How to explain the behavior of participants and improve the quality of solutions is the focus of research in the field of crowdsourcing, and also the key to enterprise practice. Based on MOA theory and relying on objective second-hand data of actual transactions on a crowdsourcing platform in China, this study empirically discusses the relationship between prize quantity of task and scheme quality under the crowdsourcing mode, as well as the moderating effect of task category and prize distribution on this relationship by using RStudio software. The results show that there is a positive correlation between prize quantity and the scheme quality, and the positive promotion effect of prize is stronger in expertise-based tasks. The effect is also stronger in single winner tasks.