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

Information Systems Research (Forthcoming)

71 Pages Posted: 13 Sep 2016 Last revised: 2 Feb 2024

See all articles by Chen Liang

Chen Liang

University of Connecticut - School of Business

Yili Hong

University of Miami Herbert Business School

Bin Gu

Boston University - Questrom School of Business

Multiple version iconThere are 2 versions of this paper

Date Written: January 30, 2024

Abstract

Many online labor platforms employ reputation systems and monitoring systems to mitigate moral hazard. While reputation systems have the potential to reduce moral hazard, they suffer from the cold-start problem, where 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 dataset 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, where the monitoring system is accessible, and fixed-price projects, where it is not. Employing a difference-in-differences (DID) 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.

Keywords: cold-start problem, online platforms, monitoring systems, entry barrier, reputation systems

JEL Classification: D82, J41

Suggested Citation

Liang, Chen and Hong, Yili and Gu, Bin, Monitoring and the Cold Start Problem in Digital Platforms: Theory and Evidence from Online Labor Markets (January 30, 2024). Information Systems Research (Forthcoming), Available at SSRN: https://ssrn.com/abstract=2838045 or http://dx.doi.org/10.2139/ssrn.2838045

Chen Liang

University of Connecticut - School of Business ( email )

2100 Hillside Road, Unit 1041
UConn School of Business OPIM
Storrs, CT Connecticut 06269
United States
06269 (Fax)

Yili Hong (Contact Author)

University of Miami Herbert Business School ( email )

P.O. Box 248126
Florida
Coral Gables, FL 33124
United States

Bin Gu

Boston University - Questrom School of Business ( email )

595 Commonwealth Avenue
Boston, MA MA 02215
United States

Do you have negative results from your research you’d like to share?

Paper statistics

Downloads
151
Abstract Views
1,034
Rank
167,430
PlumX Metrics