If You Love Your Agents, Set Them Free: Task Discretion in Online Workplaces

灵活性(工程) 自由裁量权 计算机科学 任务(项目管理) 利润(经济学) 付款 运筹学 风险分析(工程) 微观经济学 业务 经济 工程类 万维网 政治学 管理 法学
作者
Vasiliki Kostami
出处
期刊:Management Science [Institute for Operations Research and the Management Sciences]
卷期号:70 (3): 1787-1809 被引量:1
标识
DOI:10.1287/mnsc.2023.4773
摘要

In manufacturing and service operations, flexibility is beneficial for matching supply with demand, but it comes at a cost. In modern digital workplaces, agents have different skills associated with corresponding and variable task preferences. Some are inclined to give up part of their payment to avoid unfavorable matches, and the platform manager, in turn, gains extra freedom in allocating tasks by possibly charging servers for favorable assignments. Innovative marketplaces facilitate task discretion and seek novel and beneficial implementations in the platform design. This naturally leads to the problem of exploring and optimizing the task allocation process. We introduce an innovative mechanism for task assignment in the workplace and compare it to the traditional mechanism in which task routing is solely the platform’s decision. To improve the welfare of all users, agents are allowed some task discretion in exchange for a fee. In a multiserver system, a server may request flexibility and, considering the other agents’ behavior, choose the costly to the platform option, which may or may not be beneficial for the platform when the agents’ and the platform’s preferences are misaligned. We model different working environments and server preferences via different distributions and study how the agents’ preferences, task costs, and flexibility fee affect the equilibrium assignment. In every case, through pricing and offering flexibility, the platform can do at least as well as a scheme with no flexibility. An important conclusion is that pricing task discretion can often improve the agents’ welfare and the labor platform’s profit. This paper was accepted by Victor Martínez-de-Albéniz, operations management.
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