LAUSR

Systems engineering processes (SEPs) coordinate the effort of different individuals to generate a product satisfying certain requirements. As the involved engineers are self-interested agents, the goals at different levels of the systems engineering hierarchy may deviate from the system-level goals, which may cause budget and schedule overruns. Therefore, there is a need of a systems engineering theory that accounts for the human behavior in systems design. As experience in the physical sciences shows, a lot of knowledge can be generated by studying simple hypothetical scenarios, which nevertheless retain some aspects of the original problem. To this end, the objective of this article is to study the simplest conceivable SEP, a principalagent model of a one-shot, shallow SEP. We assume that the systems engineer (SE) maximizes the expected utility of the system, while the subsystem engineers (sSE) seek to maximize their expected utilities. Furthermore, the SE is unable to monitor the effort of the sSE and may not have complete information about their types. However, the SE can incentivize the sSE by proposing specific contracts. To obtain an optimal incentive, we pose and solve numerically a bilevel optimization problem. Through extensive simulations, we study the optimal incentives arising from different system-level value functions under various combinations of effort costs, problem-solving skills, and task complexities. Our numerical examples show that, the passed-down requirements to the agents increase as the task complexity and uncertainty grow and they decrease with increasing the agents' costs.