Coordinating the Scheduling of Subcontracted Operations: Centralization, Competition and First-Come-First-Served Processing

Coordinating the Scheduling of Subcontracted Operations: Centralization, Competition and First-Come-First-Served Processing

Authors

Published

Decision Sciences Journal, 4 ed., vol. 48, pp. 657-690, August 2017

Abstract

Subcontracting has become a prominent business practice across many industries. Subcontracting of industrial production is generally based on short-term need for additional processing capacity, and is frequently employed by manufacturers to process customer orders more quickly than using only in-house production. In this article, we study a popular business model where multiple manufacturers, each capable of processing his entire workload in-house, have the option to subcontract some of their operations to a single third party with a flexible resource. Each manufacturer can deliver customer orders only after his entire batch of jobs, processed in-house and at the third party, is completed. The third party facility is available to several manufacturers who compete for its use. Current business practice of First-Come-First-Served (FCFS) processing of the subcontracted workloads as well as the competitive Nash equilibrium schedules developed in earlier studies result in two types of inefficiencies; the third party capacity is not maximally utilized, and the manufacturers incur decentralization cost. In this article, we develop models to assess the value created by coordinating the manufacturers’ subcontracting decisions by comparing two types of centralized control against FCFS and Nash equilibrium schedules. We present optimal and/or approximate algorithms to quantify the third party underutilization and the manufacturers’ decentralization cost. We find that both inefficiencies are more severe with competition than they are when the third party allocates capacity in an FCFS manner. However, in a decentralized setting, a larger percentage of the players prefer Nash equilibrium schedules to FCFS schedules. We extend our analysis to incomplete information scenarios where manufacturers reveal limited demand information, and find that more information dramatically benefits the third party and the manufacturers, however, the marginal benefit of additional information is decreasing. Finally, we discuss an extension wherein each manufacturer’s objective takes into account asymmetries in subcontracting, in-house processing, and delay costs.