Putting Teams into the Gig Economy: A Field Experiment at a Ride-Sharing Platform

Wei Ai (), Yan Chen (), Qiaozhu Mei (), Jieping Ye () and Lingyu Zhang ()
Additional contact information
Wei Ai: College of Information Studies, University of Maryland, College Park, Maryland 20742
Yan Chen: School of Information, University of Michigan, Ann Arbor, Michigan 48109; Department of Economics, School of Economics and Management, Tsinghua University, Beijing 100084, China
Qiaozhu Mei: School of Information, University of Michigan, Ann Arbor, Michigan 48109
Jieping Ye: Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, Michigan 48109
Lingyu Zhang: School of Computer Science and Technology, Shandong University, Qingdao 266237, China

Management Science, 2023, vol. 69, issue 9, 5336-5353

Abstract: The gig economy provides workers with the benefits of autonomy and flexibility but at the expense of work identity and coworker bonds. Among the many reasons why gig workers leave their platforms, one unexplored aspect is the lack of an organization identity. In this study, we develop a team formation and interteam contest field experiment at a ride-sharing platform. We assign drivers to teams either randomly or based on similarity in age, hometown location, or productivity. Having these teams compete for cash prizes, we find that (1) compared with those in the control condition, treated drivers work longer hours and earn 12% higher revenue during the contest; (2) the treatment effect persists two weeks postcontest, albeit with half of the effect size; and (3) drivers in hometown-similar teams are more likely to communicate with each other, whereas those in age-similar teams continue to work longer hours and earn higher revenue during the two weeks after the contest ends. Together, our results show that platform designers can leverage team identity and team contests to increase revenue and worker engagement in a gig economy.

Keywords: team; contest; organization identity; gig economy; ride sharing (search for similar items in EconPapers)
Date: 2023
References: Add references at CitEc
Citations:

Downloads: (external link)
http://dx.doi.org/10.1287/mnsc.2022.4624 (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:inm:ormnsc:v:69:y:2023:i:9:p:5336-5353

Access Statistics for this article

More articles in Management Science from INFORMS Contact information at EDIRC.
Bibliographic data for series maintained by Chris Asher ().