4.7 Article

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

Journal

MANAGEMENT SCIENCE
Volume -, Issue -, Pages -

Publisher

INFORMS
DOI: 10.1287/mnsc.2022.4624

Keywords

team; contest; organization identity; gig economy; ride sharing

Ask authors/readers for more resources

The gig economy offers autonomy and flexibility to workers, but it may lead to a loss of work identity and coworker bonds. This study conducted a field experiment on a ride-sharing platform to explore the impact of team formation and interteam contests. The findings show that team identity and contests can increase revenue and worker engagement in a gig economy.
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 hometownsimilar teams are more likely to communicate with each other, whereas those in agesimilar 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.

Authors

I am an author on this paper
Click your name to claim this paper and add it to your profile.

Reviews

Primary Rating

4.7
Not enough ratings

Secondary Ratings

Novelty
-
Significance
-
Scientific rigor
-
Rate this paper

Recommended

No Data Available
No Data Available