Work

Home Bias in Online Employment

Year: 2018

Type: conference-paper

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.

Source: Hawaii International Conference on System Sciences (HICSS)

DOI: 10.24251/hicss.2018.437

Authors: Chen Liang, Yili (Kevin) Hong, Bin Gu

Institution: Arizona State University

Language: English

Topic: Names, Identity, and Discrimination Research

Subfield: Sociology and Political Science

Field: Social Sciences

Domain: Social Sciences

SDGs: Decent work and economic growth, Reduced inequalities, Gender equality, Peace, justice, and strong institutions

Open Access status: hybrid

OpenAlex ID: W2771037556