Operations in the On-Demand Economy: Staffing Services with Self-Scheduling Capacity
Northwestern University - Kellogg School of Management
Northwestern University - Department of Managerial Economics and Decision Sciences (MEDS)
May 4, 2015
Motivated by recent innovations in service delivery such as ride-sharing services and work-from-home call centers, we study capacity management when workers self-schedule. The service provider seeks to maximize its profit (revenue from served customers minus capacity costs) when it controls capacity only indirectly. Agents choose when to work based on the compensation offered and their individual availability. To guarantee adequate capacity, the firm must offer sufficiently high compensation. These novel service platforms provide a variety of well-understood benefits to the firm, the agents and the service's users.
Our analysis shows, however, that this flexibility brings some tradeoffs. A ''dictator" paying exactly the same wages to agents would not have only higher profits but would also provide better service levels to customers. Moreover, full flexibility is bad for agents in aggregate; the firm only offers fully flexible scheduling if it can drive agent earnings to trivial levels. If the firm has to offer a minimum compensation rate to maintain its server pool it must limit agent flexibility by restricting the number of agents that can work in some time intervals. These tradeoffs are robust to the agent-compensation mechanism and to the pricing capability of the firm.
Number of Pages in PDF File: 23
Keywords: strategic servers, on-demand economy, independent capacity, distributed systems, service operations, Uber
Date posted: October 6, 2013 ; Last revised: November 20, 2015
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