Monitoring and Home Bias in Global Hiring: Evidence from an Online Labor Platform

The increasing prevalence of remote work has accelerated the adoption of monitoring systems to keep track of worker behavior, especially on online labor platforms. In contrast to the existing literature that predominantly focuses on the effect of monitoring on productivity, this study investigates the impact of monitoring from the perspective of contractual governance. In principle, by enabling the detailed real-time observation of worker progress, the deployment of monitoring systems has the potential to improve contractual control and coordination, thereby reducing employers' preferences for domestic workers (home bias). Leveraging the exogenous introduction of a monitoring system for time-based projects on a leading online labor platform, we employ a difference-in-differences model to estimate the impact of monitoring systems in reducing home bias. Our findings reveal that following the monitoring system's introduction, the bias against foreign workers becomes substantially weaker and statistically insignificant, highlighting the overlooked role of monitoring systems in fostering a more level playing field for global workers. Our further analysis indicates that monitoring leads to a notable 15% increase in the hiring of foreign workers. Moreover, the decrease in home bias is more pronounced in high-routine projects or when employers lack prior positive experiences with foreign workers, two scenarios characterized by low external uncertainty and high internal uncertainty, respectively. Additionally, employers no longer exhibit a stronger home bias when workers have higher ratings, where the expected moral hazard risk is lower, nor when workers reside in the same time zone, where expected coordination costs are lower. These findings lend support to the effectiveness of monitoring systems in mitigating employers' home bias through enhancing contractual control and coordination. Our findings provide important managerial implications for the design of online labor platforms.