Virtual Teams in a Gig Economy
Yan Chen
The gig economy provides workers with the benefits of autonomy and flexibility, but it does so at the expense of work identity and co-worker bonds. Among the many reasons why gig workers leave their platforms, an unexplored aspect is the organization identity. In this study, we develop a team formation and inter-team contest field experiment at a ride-sharing platform. We assign drivers to teams either randomly or based on homophily in age, hometown location, or productivity. Having these teams compete for cash prizes, we find that:
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Compared to those in the control condition, treated drivers work longer hours and earn 12% higher revenue during the contest, with a larger effect (19%) for teams comprised of drivers who are more communicative and responsive; and
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Drivers in responsive teams continue to work longer hours and earn higher revenue during the two weeks after the contest ends.
In a follow-up study, we explore the effects of virtual teams without monetary incentives. Teams are randomly assigned to one of three experimental conditions. Treated drivers receive either their team ranking or individual ranking, whereas those in the control condition receive individual performance information without social comparison. We find that treated drivers are significantly more productive than those in the control condition. We further find that drivers in the team leaderboard treatment continue to work longer hours on the platform three months after the end of the experiment. Lastly, we find that those identified as laggards within a virtual team benefit the most from a team contest.
Together, our results show that platform designers can leverage team identity and team contests to increase revenue and worker engagement in a gig economy.
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Yan Chen is the Daniel Kahneman Collegiate Professor in the School of Information at the University of Michigan. She also holds an appointment as a research professor with the U-M Institute for Social Research. Her research interests are in behavioral and experimental economics, market and mechanism design, information economics, and public economics. She conducts both theoretical and experimental research. Chen has published in leading economics and management journals, such as the American Economic Review, Journal of Political Economy, Journal of Economic Theory, and Management Science. She has also published in conference proceedings in computer and information science, such as CHI and WSDM, and general interest journals such as the Proceedings of the National Academy of Sciences. She served as the president of the Economic Science Association from 2015 to 2017. She serves as a department editor at Management Science.
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