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Home Bias in Online Employment

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Item Summary

Title: Home Bias in Online Employment
Authors: Liang, Chen
Hong, Yili (Kevin)
Gu, Bin
Keywords: Crowd-based Platforms
home bias online hiring gig-economy discrimination quasi-natural experiment
Issue Date: 03 Jan 2018
Abstract: 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.
Pages/Duration: 10 pages
ISBN: 978-0-9981331-1-9
DOI: 10.24251/HICSS.2018.437
Rights: Attribution-NonCommercial-NoDerivatives 4.0 International
Appears in Collections:Crowd-based Platforms

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