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Monitoring and the Cold Start Problem in Digital Platforms: Theory and Evidence from Online Labor Markets

Author

Listed:
  • Chen Liang

    (School of Business, University of Connecticut, Storrs, Connecticut 06269)

  • Yili Hong

    (Miami Herbert Business School, University of Miami, Coral Gables, Florida 33146)

  • Bin Gu

    (Questrom School of Business, Boston University, Boston, Massachusetts 02215)

Abstract

Many online labor platforms employ reputation systems and monitoring systems to mitigate moral hazard. Whereas reputation systems have the potential to reduce moral hazard, they suffer from the cold-start problem, in which new entrants without an established reputation face a high entry barrier as employers predominantly select workers based on their existing reputation. Monitoring systems, providing employers with direct oversight of workers’ actions, offer a different approach. By tracking and reporting workers’ effort levels, monitoring systems reduce ex post information asymmetry and, thus, lower employers’ expected moral hazard risk from workers. However, unlike reputation systems, monitoring systems do not directly address ex ante information asymmetry, failing to assist employers in identifying the right workers. This inherent limitation raises questions about their effectiveness in resolving the cold-start problem. In this paper, we first propose a stylized theoretical model that characterizes worker entry in the presence of reputation and monitoring systems. Based on a unique data set from a leading online labor platform, we then empirically investigate the effect of monitoring systems on the entry barriers by examining the change in workers’ entry behaviors after the introduction of the monitoring system along with associated project outcomes, which include employers’ hiring preferences, hiring prices, and project performance. We exploit the differential availability of the monitoring system across two project types: time-based projects, for which the monitoring system is accessible, and fixed-price projects, for which it is not. Employing a difference-in-differences estimation with a sample including 9,344 fixed-price projects and 3,118 time-based projects, we report that the introduction of the monitoring system increases the number of bids on time-based projects by 27.8%, and the incremental bids predominantly originate from inexperienced workers who lack platform reputation. We further find that, following the introduction of the monitoring system, employers’ preference for experienced workers diminishes, accompanied by an average reduction of 19.5% in labor costs, whereas we observe no significant decrease in project completion and review rating. Our results collectively suggest that monitoring systems alleviate the cold-start problem in online platforms.

Suggested Citation

  • Chen Liang & Yili Hong & Bin Gu, 2025. "Monitoring and the Cold Start Problem in Digital Platforms: Theory and Evidence from Online Labor Markets," Information Systems Research, INFORMS, vol. 36(1), pages 600-620, March.
  • Handle: RePEc:inm:orisre:v:36:y:2025:i:1:p:600-620
    DOI: 10.1287/isre.2021.0146
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