{"title":"全球招聘中的监督和家庭偏见:来自在线劳务平台的证据","authors":"Chen Liang, Yili Hong, Bin Gu","doi":"10.1287/isre.2021.0526","DOIUrl":null,"url":null,"abstract":"Online labor platforms increasingly use monitoring systems to manage remote workers. This study assesses whether and how these systems mitigate employer bias in hiring foreign versus domestic workers. 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 on mitigating employers’ tendency to bias against hiring foreign workers (home bias). Results indicate a significant reduction in home bias, along with a 15% increase in the hiring of foreign workers following the introduction of the monitoring system. The mitigation effect is notably stronger 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. Moreover, employers no longer exhibit a stronger home bias in scenarios of lower moral hazard risk or coordination costs. These findings lend support to the effectiveness of monitoring systems in mitigating employers’ home bias through facilitating contractual control and coordination. Our study offers important implications for the design of online labor platforms and policymaking.","PeriodicalId":48411,"journal":{"name":"Information Systems Research","volume":null,"pages":null},"PeriodicalIF":5.0000,"publicationDate":"2024-06-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Monitoring and Home Bias in Global Hiring: Evidence from an Online Labor Platform\",\"authors\":\"Chen Liang, Yili Hong, Bin Gu\",\"doi\":\"10.1287/isre.2021.0526\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Online labor platforms increasingly use monitoring systems to manage remote workers. This study assesses whether and how these systems mitigate employer bias in hiring foreign versus domestic workers. 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 on mitigating employers’ tendency to bias against hiring foreign workers (home bias). Results indicate a significant reduction in home bias, along with a 15% increase in the hiring of foreign workers following the introduction of the monitoring system. The mitigation effect is notably stronger 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. Moreover, employers no longer exhibit a stronger home bias in scenarios of lower moral hazard risk or coordination costs. These findings lend support to the effectiveness of monitoring systems in mitigating employers’ home bias through facilitating contractual control and coordination. Our study offers important implications for the design of online labor platforms and policymaking.\",\"PeriodicalId\":48411,\"journal\":{\"name\":\"Information Systems Research\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":5.0000,\"publicationDate\":\"2024-06-12\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Information Systems Research\",\"FirstCategoryId\":\"91\",\"ListUrlMain\":\"https://doi.org/10.1287/isre.2021.0526\",\"RegionNum\":3,\"RegionCategory\":\"管理学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"INFORMATION SCIENCE & LIBRARY SCIENCE\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Information Systems Research","FirstCategoryId":"91","ListUrlMain":"https://doi.org/10.1287/isre.2021.0526","RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"INFORMATION SCIENCE & LIBRARY SCIENCE","Score":null,"Total":0}
Monitoring and Home Bias in Global Hiring: Evidence from an Online Labor Platform
Online labor platforms increasingly use monitoring systems to manage remote workers. This study assesses whether and how these systems mitigate employer bias in hiring foreign versus domestic workers. 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 on mitigating employers’ tendency to bias against hiring foreign workers (home bias). Results indicate a significant reduction in home bias, along with a 15% increase in the hiring of foreign workers following the introduction of the monitoring system. The mitigation effect is notably stronger 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. Moreover, employers no longer exhibit a stronger home bias in scenarios of lower moral hazard risk or coordination costs. These findings lend support to the effectiveness of monitoring systems in mitigating employers’ home bias through facilitating contractual control and coordination. Our study offers important implications for the design of online labor platforms and policymaking.
期刊介绍:
ISR (Information Systems Research) is a journal of INFORMS, the Institute for Operations Research and the Management Sciences. Information Systems Research is a leading international journal of theory, research, and intellectual development, focused on information systems in organizations, institutions, the economy, and society.