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, we employ the difference-in-difference model to show that the home bias does exist in online employment, and at least 54.0% of home bias is driven by statistical discrimination.
| Original language | English (US) |
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| DOIs | |
| State | Published - 2018 |
| Externally published | Yes |
| Event | 38th International Conference on Information Systems: Transforming Society with Digital Innovation, ICIS 2017 - Seoul, Korea, Republic of Duration: Dec 10 2017 → Dec 13 2017 |
Other
| Other | 38th International Conference on Information Systems: Transforming Society with Digital Innovation, ICIS 2017 |
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| Country/Territory | Korea, Republic of |
| City | Seoul |
| Period | 12/10/17 → 12/13/17 |
Keywords
- Employment
- Gig economy
- Home bias
- Quasi-natural experiment
- Statistical discrimination
- Taste-based discrimination
ASJC Scopus subject areas
- Computer Science Applications
- Information Systems