Effects of IT-enabled Monitoring Systems in Online Labor Markets

This paper investigates how IT-enabled monitoring systems mitigate moral hazard in an online labor market and their effect on market competition. We exploit a quasi-experiment at Freelancer when it introduced enhanced offline tracking features in 2015. Using a large dataset including 17,827 fixed-price projects and 8,563 hourly projects, we use a difference-in-differences (DID) approach to identify the treatment effect of the implementation of IT-enabled monitoring systems on employer contractor choice, employer surplus and market competition. We found that the IT-enabled monitoring system lowers the employers’ preference for high-reputable bidders, and thus reduces the reputation premiums. Meanwhile, comparing the trend of fixed-price projects, the implementation of the monitoring systems increased the number of bids by 17.4% and increased employer surplus in hourly projects by 21.5%. Our result suggests that IT-enabled monitoring systems have a significant effect on alleviating moral hazards, reducing agency costs, and facilitating market competition

Moral Hazards and Effects of IT-enabled Monitoring Systems in Online Labor Markets

This paper investigates how IT-enabled monitoring systems mitigate moral hazard in an online labor market and their effect on market competition. We exploit a quasi-experiment at Freelancer when it introduced an IT-enabled monitoring system in 2015. We use a difference-in-differences (DID) approach to identify the treatment effect of the monitoring system on employer contractor choice, market competition, and employer surplus. We found that the IT-enabled monitoring system lowers the employers’ willingness to pay the reputation premiums. Meanwhile, comparing the trend of the control group, the IT-enabled monitoring system raised the employer surplus in hourly projects and increased the number of bids. Our result suggests that IT-enabled monitoring systems have a significant effect on alleviating moral hazards, reducing agency costs, and facilitating market competition

Home Bias in Hiring: Evidence from an Online Labor Market

We study the nature of home bias in online employment, wherein the employers prefer workers from their own home countries. Using a unique large-scale dataset from a major online labor market containing employers’ consideration set of workers and their ultimate selection of workers, we first estimate employers’ home bias in their online employment decisions. Moreover, we find that employers from countries with high traditional values, lower diversity, and smaller user base (or population size), tend to have a stronger home bias. Further, we disentangle two types of home bias, i.e., statistical and taste-based, using a quasi-natural experiment wherein the platform introduces a monitoring system to facilitate employers to easily observe workers’ progress in time-based projects. After matching comparable fixed-price projects as a control group using coarsened exact matching, our difference-in-difference estimations show that the home bias in online employment is primarily driven by statistical discrimination

Home Bias in Online Employment

We study the nature of home bias in online employment, wherein the employer prefers workers from his/her own home country. Using a unique large-scale dataset from one of the major online labor platforms, we identify employers’ home bias in their online employment decisions. Moreover, we investigate the cause of employers’ home bias using a quasi-natural experiment wherein the platform introduces a monitoring system to facilitate employers to keep track of workers’ progress in time-based projects. After matching comparable fixed-price projects as a control group using propensity score matching, our difference-in-difference estimations show that the home bias does exist in online employment, and at least 54.0% of home bias is driven by statistical discrimination