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

Omar Besbes, Vineet Goyal, Garud Iyengar, Raghav Singal
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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.Supplemental Material: The online appendix is available at https://doi.org/10.1287/msom.2022.0414 .
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具有异质时间偏好的劳动力调度:有效工资与工人供给
问题定义:在围绕 "打工经济 "中工人福利的争论的推动下,我们提出了一个评估当前做法和可能的替代方案的框架。我们研究的是这样一种情况:顾客向工人寻求服务,而平台则在一天中为这种匹配提供便利。平台使用分配政策为工人分配时间段,工人是战略代理人(关于 "何时工作"),他们的预期效用最大化取决于他们的首选工作时间、分配的时间段和总可用时间。平台的目标是确保有足够数量的工人来满足需求,而工人的目标则是最大化其工资驱动的效用。方法/结果:我们从对任何公司都至关重要的两个方面对政策进行评估:全天的工人供应和工人的有效工资。我们说明,目前采用的几种政策都有严重的局限性。我们发现,之所以存在这些局限性,是因为这些政策没有让工人充分表达他们的偏好,而且/或者无法解释这种偏好的异质性。我们提出了一种新的分配政策,并在工人供给和有效工资两方面建立了强有力的绩效保证。该政策简单易行,并能充分利用市场信息来获得更好的市场结果。我们以纽约市各种数据集校准的打车服务为背景,通过数字实验来补充我们的理论,这些数据集说明了一系列市场的表现。管理意义:我们强调了目前限制工人表达偏好能力的政策的基本低效。通过允许工人表达他们的时间偏好,以及明智地优先考虑 "全职 "工人而非 "兼职 "工人,我们可以获得潜在的显著帕累托改进,在增加工人有效工资的同时保持(甚至增加)工人的供给:在线附录见 https://doi.org/10.1287/msom.2022.0414 。
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