Is self-knowledge the ultimate prize? A quantitative analysis of participation choice in online ideation crowdsourcing contests

Online crowdsourcing contests are a nascent but rapidly growing method among marketers and retailers to generate and solicit creative ideas. In two studies – a dynamic model with scraped data from a well-known crowdsourcing platform using Python (study 1) and a survey among real participants in online contests with conjoint analysis (study 2) – we explore how multiple design parameters influence participation in online contests. Our empirical results support the notion that both extrinsically (i.e., prize money) and intrinsically (i.e., feedback) motivating parameters can generate value for participants (i.e., expected utility). Comparatively, however, we find evidence that intrinsically motivating design parameters that provide self-relevant feedback (i.e., feedback from organizer) can be more impactful than extrinsically motivating design parameters (i.e., award size). We also show novel time-dependent effects: as a contest nears its end, important design parameters shift in their effects on participation rates— their role over time is non-monotonic. In particular, the effect of award size becomes non-significant, but feedback remains impactful. Our findings contribute to the crowdsourcing literature, especially regarding how self-knowledge (e.g., self-efficacy) affects utility and consumer co-creation through contest participation over time; the findings also can help retail managers and marketers enhance participation in idea contests.