Paper Number

2174

Paper Type

CRP

Abstract

The proliferation of crowdsourcing platforms grants freelancers unprecedented opportunities to monetize their expertise by bidding for specific tasks. Despite lowering freelancers’ participation costs, the bidding mechanism induces intense competition, rendering it difficult for freelancers to submit competitive bids. Although prior research has yielded several bidding strategies, scant attention was paid to whether and how freelancers should learn to adjust their bidding strategies through participating in multiple tasks. To bridge this knowledge gap, we contextualize a set of bidding strategies from auction literature. Next, subscribing to the theoretical lens of vicarious learning, we advance that freelancers’ learning from winners on bidding strategies will bolster their bidding competitiveness, which in turn is contingent on task complexity. Analytical results based on linear growth modeling reveal a significant relationship between strategic learning and bidding competitiveness, along with the moderating effect of task complexity. Finally, theoretical implications and future research directions are discussed.

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Jun 14th, 12:00 AM

Unraveling Learning on Winner Strategies and Bidding Competitiveness: Evidence from a Crowdsourcing Platform

The proliferation of crowdsourcing platforms grants freelancers unprecedented opportunities to monetize their expertise by bidding for specific tasks. Despite lowering freelancers’ participation costs, the bidding mechanism induces intense competition, rendering it difficult for freelancers to submit competitive bids. Although prior research has yielded several bidding strategies, scant attention was paid to whether and how freelancers should learn to adjust their bidding strategies through participating in multiple tasks. To bridge this knowledge gap, we contextualize a set of bidding strategies from auction literature. Next, subscribing to the theoretical lens of vicarious learning, we advance that freelancers’ learning from winners on bidding strategies will bolster their bidding competitiveness, which in turn is contingent on task complexity. Analytical results based on linear growth modeling reveal a significant relationship between strategic learning and bidding competitiveness, along with the moderating effect of task complexity. Finally, theoretical implications and future research directions are discussed.

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