The rapid growth of crowdsourcing grants freelancers unprecedented opportunities to materialize their expertise by bidding in specific tasks. Despite lowering freelancers’ participation costs, the bidding mechanism meanwhile induces intense competition, rendering it difficult for freelancers to submit competitive bids. Although previous research has disentangled several bidding strategies, scant attention was paid to whether and how freelancers should learn to adjust their bidding strategies and improve bidding competitiveness during the journey of participating in multiple tasks. To fill in this gap, we adapt a set of bidding strategies from auction literature into the crowdsourcing context. Leveraging the lens of vicarious learning, we advance that freelancers’ learning from winners on bidding strategies will enhance their bidding competitiveness, which is moderated by task complexity. Our preliminary results suggest a significant relationship between strategic learning and bidding competitiveness, along with the moderating effect of task complexity. Expected contributions and future schemes are discussed finally.
Yang, Chaofan; Xiong, Bingqing; Lim, Eric; Sun, Yongqiang; and Tan, Chee-Wee, "Learning from Winners: A Strategic Perspective of Improving Freelancers’ Bidding Competitiveness in Crowdsourcing" (2024). SIGHCI 2023 Proceedings. 14.