Author
Listed:
- Ni Huang
(Department of Business Technology, Miami Herbert Business School, University of Miami, Coral Gables, Florida 33146)
- Gordon Burtch
(Department of Information Systems, Questrom School of Business, Boston University, Boston, Massachusetts 02215)
- Pei-yu Chen
(Department of Information Systems, W. P. Carey School of Business, Arizona State University, Tempe, Arizona 85287)
- Ao Huang
(Department of Business Technology, Miami Herbert Business School, University of Miami, Coral Gables, Florida 33146)
Abstract
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.
Suggested Citation
Ni Huang & Gordon Burtch & Pei-yu Chen & Ao Huang, 2026.
"Evaluating the Efficacy of Application Costs for Managing Congestion in Online Matching Markets,"
Management Science, INFORMS, vol. 72(6), pages 4909-4934, June.
Handle:
RePEc:inm:ormnsc:v:72:y:2026:i:6:p:4909-4934
DOI: 10.1287/mnsc.2021.03495
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