Dynamic incentive problems in operations management

The principal-agent paradigm, in which a principal has a primary stake in the performance of some system but delegates operational control of that system to an agent, has many natural applications in operations management (OM). However, existing principal-agent models are of limited use to OM researchers because they lack the rich dynamic structure required of OM models. This thesis formulates a novel dynamic model that overcomes these limitations by combining the principal-agent framework with the physical structure of a Markov decision process. In this model one has a system moving from state to state as time passes, with transition probabilities depending on actions chosen by an agent, and a principal who pays the agent based on state transitions observed. The principal seeks an optimal payment scheme, striving to induce the actions that will maximize her expected discounted profits over a finite planning horizon. Although dynamic principal-agent models similar to the one proposed here are considered intractable, a set of assumptions are introduced that enable a systematic analysis, using a dynamic programming recursion to derive an optimal payment scheme. This method is applied to a principal-agent variant of the classical make-to-stock production system. Production is modeled by a single server queue with exponential service times, in which the agent dynamically controls the production rate and incurs a convex production cost. The principal incurs linear holding and backorder inventory costs, and pays the agent according to observed job completions and inventory levels, striving to induce actions that will minimize her expected total discounted cost. The principal's optimal incentive payment scheme is proven to consist of a differential piece rate and a delay penalty.; The most onerous assumption needed to support the dynamic programming analysis is that the principal knows the agent's cost structure and productive capabilities. Unfortunately, information asymmetry abounds in many OM problems, such as the outsourcing of a new product. In a simple two-period model, we investigate how a buyer's uncertainty about a supplier's capabilities will affect the rate of process improvement, the level of capacity investment, and the structure of optimal incentive contracts.