Exploring the effects of reward and competition intensity on participation in crowdsourcing contests

Dan Li () and Longying Hu ()
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Dan Li: Harbin Institute of Technology
Longying Hu: Harbin Institute of Technology

Electronic Markets, 2017, vol. 27, issue 3, No 3, 199-210

Abstract: Abstract With the growth of web 2.0 technology, crowdsourcing contests now offer task-seekers an opportunity to access expertise and resources at a lower cost. Many studies have investigated the effects of influencing factors on solvers’ participation behaviors. However, there has been scant research on the effect of competition intensity and on the relationships between competition and reward. We collect data from the Taskcn website in China to build a two-equation model based on expectation-value theory to explore the effects of task reward and competition intensity on solvers’ registration and submission behaviors. The research results verify that task reward is positively associated with the number of registrations and submissions, and competition intensity is negatively associated with solvers’ submissions. In addition, the empirical results show that competition intensity moderates the relationship between task reward and submissions. These findings provide valuable contributions to the literature on crowdsourcing contests.

Keywords: Crowdsourcing contest; Task reward; Competition intensity; Registration; Submission; Two-equation model (search for similar items in EconPapers)
JEL-codes: M (search for similar items in EconPapers)
Date: 2017
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Citations: View citations in EconPapers (11)

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DOI: 10.1007/s12525-017-0252-7

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