Abstract
Capacity planning and incentive contract design have always been challenging strategic decisions, especially for companies operating in a stochastic service demand and delivery environment. Such service facilities often must make capacity decisions long before observing demand, so a practical approach is to make the decision based on the expected demand distribution. Due to stochastic demand and capacity constraints, service centers often incur delays and delay-related costs when the actual demand is high. When the actual demand is low, however, centers have to bear high idle capacity costs. Economics literature on principal-agent issue has mostly focused on designing salesforce compensation plans so as to motivate the agent and manage risk-sharing. However, in a typical principal-agent model setting, the principal faces no capacity limit and incurs no delay-related costs. Furthermore, the capacity decision and the compensation decision are usually treated as two separate decision processes both in practice and in research. This suboptimal decision process leads to suboptimal results: the principal either incurs high delay costs or high idle capacity costs. To tackle service facility capacity planning and incentive contract issue, we propose instead an integrated approach. That is, we integrate a firm's decision regarding capacity investment with its decision regarding the design of a compensation contract. We outline this integrated decision approach and illustrate its benefits with numerical examples. We show that following our decision methodology the firm can achieve significantly higher profits. Several cases in the paper depict that the firm can achieve profit increments ranging from 10% to 42% by properly integrating contract design with its capacity decision process early on.