Workforce Scheduling with Heterogeneous Time Preferences: Effective Wages and Workers’ Supply

Omar Besbes (), Vineet Goyal (), Garud Iyengar () and Raghav Singal ()
Additional contact information
Omar Besbes: Graduate School of Business, Columbia University, New York, New York 10027
Vineet Goyal: Department of IEOR, Columbia University, New York, New York 10027
Garud Iyengar: Department of IEOR, Columbia University, New York, New York 10027
Raghav Singal: Tuck School of Business, Dartmouth College, Hanover, New Hampshire 03755

Manufacturing & Service Operations Management, 2024, vol. 26, issue 5, 1768-1786

Abstract: Problem definition : Motivated by the debate around workers’ welfare in the gig economy, we propose a framework to evaluate current practices and possible alternatives. We study a setting in which customers seek service from workers and a platform facilitates such matches over the course of the day. The platform allocates time slots to workers using an allocation policy, and the workers are strategic agents (with respect to “when to work”) who maximize their expected utility that depends on their preferred times to work, the allocated slots, and the total availability time. The platform seeks to ensure that a sufficient number of workers is available to satisfy demand, whereas the workers aim to maximize their wage-driven utility. Methodology/results : We evaluate policies on two dimensions critical to any firm: the supply of workers across the day, and the effective wages of workers. We illustrate that several families of currently deployed policies have serious limitations. We find these limitations exist because the policies do not let workers fully express their preferences and/or cannot account for heterogeneity in such preferences. We propose a new allocation policy and establish strong performance guarantees with respect to both the workers’ supply and effective wages. The policy is simple and fully leverages the market information to reach better market outcomes. We supplement our theory with numerical experiments in the context of ride-hailing calibrated on various New York City data sets that illustrate performance across a range of markets. Managerial implications : We highlight a fundamental inefficiency of policies currently deployed that limit workers’ ability to express their preferences. By allowing workers to express their temporal preferences, and by judiciously prioritizing “full-time” workers over “part-time” workers, we can obtain a potentially significant Pareto improvement, maintaining (or even increasing) workers’ supply while increasing their effective wages.

Keywords: on-demand services; scheduling; workers’ supply; gig-economy wages (search for similar items in EconPapers)
Date: 2024
References: Add references at CitEc
Citations:

Downloads: (external link)
http://dx.doi.org/10.1287/msom.2022.0414 (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:ormsom:v:26:y:2024:i:5:p:1768-1786

Access Statistics for this article

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