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

Chaofan Yang, Bingqing Xiong, Eric T.K. Lim, Yongqiang Sun, Chee-Wee Tan

Publikation: Bidrag til bog/antologi/rapportKonferencebidrag i proceedingsForskningpeer review


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.
TitelPACIS 2021 Proceedings
RedaktørerDoug Vogel, Kathy Ning Shen, Pan Shan Ling, M.N. Ravishankar , Xi (Jacky) Zhang
Antal sider14
UdgivelsesstedAtlanta, GA
ForlagAssociation for Information Systems. AIS Electronic Library (AISeL)
StatusUdgivet - 2021
BegivenhedThe 25th Pacific Asia Conference on Information Systems. PACIS 2021 - Virtual
Varighed: 12 jul. 202114 jul. 2021
Konferencens nummer: 25


KonferenceThe 25th Pacific Asia Conference on Information Systems. PACIS 2021


  • Crowdsourcing
  • Bidding strategies
  • Client demands
  • Competitive differentiation
  • Bidding performance