Evaluating the Efficacy of Application Costs for Managing Congestion in Online Matching Markets

• 成果类型: Article; Early Access
• 署名作者: Huang, Ni; Burtch, Gordon; Chen, Pei-yu; Huang, Ao
• 署名单位: University of Miami; Boston University; Arizona State University; Arizona State University-Tempe
• 刊物名称: MANAGEMENT SCIENCE
• ISSN/ISSBN: 0025-1909
• DOI: 10.1287/mnsc.2021.03495
• 发表日期: 2025
• 关键词: matching platforms; frivolous bidding; market congestion; application costs; Quasi-experiment

摘要

Matching platforms seek to facilitate market clearing, but congestion arises with imbalances in supply and demand. In online labor markets, when workers can apply to jobs without restriction, they may apply to an excessive volume of positions to maximize their likelihood of securing work, overwhelming employers and making screening difficult if not altogether unmanageable. Prior research has theoretically argued that imposing application costs on workers can mitigate this issue. However, the efficacy of such a solution has yet to be evaluated empirically in matching platforms where employers incur significant screening costs. We address that gap here, considering a prominent online labor market that imposed application costs on workers. We report evidence that application costs successfully improved matching outcomes via at least two channels. First, the application costs reduced bid volumes, lowering employer screening costs in turn. Second, the application costs led workers to become more selective in their applications, focusing on the employers and jobs that they were best suited for and putting greater effort into differentiating themselves, including actively reaching out to employers via direct messages. These worker-side, secondary responses enhance the first-order benefit of the application costs (i.e., constraining application volumes). Finally, the workers' increased selectivity comes paired with risk aversion among workers, who become more likely to apply for jobs requiring familiar skills and less likely to apply for jobs posted by employers in different time zones or speaking a different language. We discuss the implications of our findings for workers' longer-term career trajectories and market sustainability generally.