Published in Manufacturing & Service Operations Management, 2023
The Impact of Behavioral and Economic Drivers on Gig Economy Workers
Gad Allon, Maxime C. Cohen, Wichinpong Park Sinchaisri
In brief
Uses ride-hailing data to model when on-demand drivers start and stop working. Pay matters, but so do habits such as quitting after reaching an earnings goal and staying on once a shift has momentum; incentives that account for both can add capacity without extra cost.
Abstract
Problem definition. Gig economy companies benefit from labor flexibility by hiring independent workers in response to real-time demand. However, workers’ flexibility in their work schedule poses a great challenge in terms of planning and committing to a service capacity. Understanding what motivates gig economy workers is thus of great importance. In collaboration with a ride-hailing platform, we study how on-demand workers make labor decisions; specifically, whether to work and work duration. Our model revisits competing theories of labor supply regarding the impact of financial incentives and behavioral motives on labor decisions. We are interested in both improving how to predict the behavior of flexible workers and understanding how to design better incentives.
Methodology/results. Using a large comprehensive data set, we develop an econometric model to analyze workers’ labor decisions and responses to incentives while accounting for sample selection and endogeneity. We find that financial incentives have a significant positive influence on the decision to work and on the work duration—confirming the positive income elasticity posited by the standard income effect. We also find support for a behavioral theory as workers exhibit income-targeting behavior (working less when reaching an income goal) and inertia (working more after working for a longer period).
Managerial implications. We demonstrate via numerical experiments that incentive optimization based on our insights can increase service capacity by 22% without incurring additional cost, or maintain the same capacity at a 30% lower cost. Ignoring behavioral factors could lead to understaffing by 10%–17% below the optimal capacity level. Lastly, our insights inform the design of platform strategy to manage flexible workers amidst an intensified competition among gig platforms.
Funding. This study was supported by The Jay H. Baker Retailing Center, The William and Phyllis Mack Institute for Innovation Management, The Wharton Risk Management and Decision Processes Center, and The Fishman-Davidson Center for Service and Operations Management.
Supplemental material. The online appendices are available at https://doi.org/10.1287/msom.2023.1191 .
From Manufacturing & Service Operations Management, via Crossref
Details
- Status
- Published
- Venue
- Manufacturing & Service Operations Management
- Online
- 2023-03
- Research areas
- Platform Work
Cite
Allon, G., Cohen, M. C., & Sinchaisri, W. P. (2023). The Impact of Behavioral and Economic Drivers on Gig Economy Workers. Manufacturing & Service Operations Management, 25(4), 1376–1393. https://doi.org/10.1287/msom.2023.1191
@article{allon2023impact, title = {The Impact of Behavioral and Economic Drivers on Gig Economy Workers}, author = {Allon, Gad and Cohen, Maxime C. and Sinchaisri, Wichinpong Park}, journal = {Manufacturing & Service Operations Management}, volume = {25}, number = {4}, pages = {1376--1393}, year = {2023}, doi = {10.1287/msom.2023.1191} }
