Capacity planning and performance contracting for service facilities

Market demand uncertainty and time‐based competition make capacity investment and managerial incentive decisions for service facilities such as high‐end diagnostic medical imaging centers, modern IT services, or contract manufacturing shops particularly challenging. These facilities compete on service quality, short queuing times and speed. Therefore, having insufficient capacity can be economically devastating for them. Given the high up‐front costs involved, firms want to make sure that they neither over‐ nor under‐invest in service capacity. These problems get exasperated by the fact that typically firms are unfamiliar with the local market conditions and do not closely observe the demand‐generating efforts of the hired managers. Most prior studies of cost allocation methodologies, contract design, and service resource management tend to address these aspects of the problem separately. They ignore the interaction effects between the capacity decisions and the managerial adverse selection and moral hazard issues, which are crucial elements for successfully running services with fixed capacity, random arrivals, and stochastic service times. Our paper instead focuses on the development of an integrated‐approach to the simultaneous design of efficient managerial contracts and of capacity planning for capital intensive service facilities. We derive optimal linear contracting structures under information asymmetry between the firms and management, and analyze their impact on capacity decisions, service levels, service volumes, and the allocations of costs. Surprisingly, we prove that even though a franchise (charge‐back) contract induces the first‐best effort from the manager, it is not always the best choice for the firms as it may lead to inferior profits for them. In fact, our results explain why a firm's eventual contract choice should be a function of its prior on the probability distribution of the local market demand. We also explain when it may be optimal (for both the firm and the manager) to charge the manager up front a fixed franchising fee that is even greater than the total costs of capacity. Our study applies to many capital‐intensive and congestion‐prone service systems, where the success of significant up‐front capacity investments also hinges on the daily operations of those facilities run by hired managers–who typically possess specific knowledge–that gives them a significant information advantage.