Disentangling the Effects of Client- vs. Rival-Oriented Strategies on Bidding Performance: Evidence from a Crowdsourcing Platform

Authors

Chaofan Yang, Wuhan UniversityFollow
Bingqing Xiong, University of Science and Technology of China-City University of Hong KongFollow
Eric Lim, University of New South WalesFollow
Yongqiang Sun, Wuhan UniversityFollow
Chee-Wee Tan, Copenhagen Business SchoolFollow

Paper Type

FP

Paper Number

474

Abstract

Crowdsourcing empowers clients with specific demands for customized services to recruit skilled workers through competitive bidding. Although prior research has investigated bidders’ participating motivations and clients’ selection criteria, knowledge about how bidders could leverage appropriate bidding strategies to boost their performance is limited. Synthesizing extant literature on auction and crowdsourcing, we advance skill, spatial, and proposal differentiations as client-oriented strategies, which when combined with their rival-oriented counterparts, will dictate bidders’ performance on crowdsourcing platforms. To validate our hypotheses, we collected secondary data from a leading crowdsourcing platform in China. Bidder-level analysis revealed that skill differentiation positively affected bidding performance. Conversely, spatial differentiation exerted a negative impact while the effects of proposal differentiation turned out to be mixed. Moreover, bid sequence and category concentration were found to moderate the effect of client-oriented strategies partially. Theoretical and practical implications are further discussed.

Recommended Citation

Yang, Chaofan; Xiong, Bingqing; Lim, Eric; Sun, Yongqiang; and Tan, Chee-Wee, "Disentangling the Effects of Client- vs. Rival-Oriented Strategies on Bidding Performance: Evidence from a Crowdsourcing Platform" (2021). PACIS 2021 Proceedings. 80.
https://aisel.aisnet.org/pacis2021/80