Attracting High-Quality Contestants to Contest in the Context of Crowdsourcing Contest Platform

• 成果类型: Article
• 署名作者: Chen, Pei-Yu; Pavlou, Paul; Wu, Shinyi; Yang, Yang
• 署名单位: Arizona State University; Arizona State University-Tempe; University of Houston System; University of Houston
• 刊物名称: PRODUCTION AND OPERATIONS MANAGEMENT
• ISSN/ISSBN: 1059-1478
• DOI: 10.1111/poms.13340
• 发表日期: 2021
• 页码: 1751-1771
• 关键词: open contests; contest platform; crowdsourcing; contestant quality; contest design

摘要

Contests have long existed to source ideas and solutions. The emergence of crowdsourcing contest platforms greatly reduces the costs and broadens the reach of running contests by facilitating access to a large pool of labor, making contests a cost-efficient approach to procure ideas/solutions even for employers of limited resources. As a result, the use of contests surges and there is a flux of small-to-medium size contests to these platforms. This study focuses on these new waves of small-to-medium-size contests on crowdsourcing contest platforms and extends the literature in several ways: First, prior literature focuses extensively on contest prize, we also consider the effect of contest duration, which plays salient role on contest platforms. Our findings provide evidence that contest duration affects both the number and the quality of contestants attracted to a contest. Second, prior literature assumes contests exist independently and that the quality distribution of contestants is exogenous; accordingly, the number of contestants can be regarded as a proxy of contest performance. We show that contest design parameters have direct effects on the quality distribution of contestants. Specifically, increasing contest duration, while attracting more contestants, results in a downward shift on the quality distribution of the contestants attracted to the contest. Third, recognizing that each contest does not exist independently on crowdsourcing contest platforms, we also incorporate the number of competing contests in our model. Our results provide practical recommendations on how to set up successful contests and attract high-quality contestants to a contest on a crowdsourcing contest platform.