Seekers’ complaint behavior in crowdsourcing: An uncertainty perspective

Xi Yang, Quanwu Zhao and Heshan Sun

Journal of Retailing and Consumer Services, 2022, vol. 68, issue C

Abstract: This research aims to understand how task descriptions on crowdsourcing platforms influence seekers’ complaint behavior, which has received little if any attention in research. From an uncertainty perspective, we develop a research model that depicts how seekers’ task description (task description uncertainty), solvers’ expertise (solver uncertainty), and task duration jointly influence seekers’ complaint behavior. The model was tested with real transaction data from ZBJ.com, a popular crowdsourcing platform in China. The results indicate that task description precision can reduce seekers’ complaint behavior while task description completeness counter-intuitively increases complaint behavior. Moreover, solvers’ expertise decreases seekers’ complaint behavior and at the same time attenuates the effects of task description on seekers’ complaint behavior. In addition, task duration negatively moderates the effect of task description completeness on complaint behavior.

Keywords: Crowdsourcing; Complaint behavior; Uncertainty; Information asymmetry; Task description (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:joreco:v:68:y:2022:i:c:s0969698922001618

DOI: 10.1016/j.jretconser.2022.103068

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