Principal-Agent Models of Decision Delegation during Systems Design: Integrating Modeling and Behavioral Approaches

现代系统工程项目可能涉及分布在数千个独立组织中的数万名工程师。例如，空军的F-35闪电II由1,400多家供应商提供的30多万个零件组成。同样，波音787梦想飞机的开发涉及2，000多家供应商，分为三级责任。关于如何在这些组织内部和之间委派设计权限的决策可能会对项目度量（进度和预算）以及最终工程系统的性能产生重大影响。糟糕的设计授权决定被认为是大型系统工程项目出现问题的原因。然而，在系统工程中，设计委托的不同方法的影响并没有得到很好的理解，在一个基本的水平。提高对系统工程中设计授权的理解将提高系统工程项目的效率和有效性，并导致更好的工程系统。本研究的目的是创建一个新的行为知情的建模框架的决策过程中发生的系统工程项目的设计阶段。该研究将联合收割机的数学委托代理理论与新的实证结果有关的人的判断和决策行为。这将使各种决策委托策略的分析方式，是由数据支持的工程决策者如何行为，但在一个规模不切实际的通过人类研究。预计新的建模框架将使研究人员能够回答有关设计委托方法的重要问题，例如在特定情况下，一种方法是否上级于另一种方法，以及方法的性能对问题上下文的敏感程度。这项研究将有助于工程师如何解释和响应激励措施，在他们的决策，以及如何众所周知的方法进行设计授权相互比较的新知识。

Modern systems engineering projects can involve tens of thousands of engineers spread across thousands of independent organizations. For example, the Air Force's F-35 Lightning II consists of more than 300,000 individual parts delivered by more than 1,400 suppliers. Similarly, development of the Boeing 787 Dreamliner involved over 2,000 suppliers organized into three tiers of responsibility. Decisions about how to delegate design authority within and among these organizations can have significant impact on project metrics (schedule and budget) as well as the performance of the resulting engineered systems. Poor design delegation decisions have been cited as an explanation for problems on large systems engineering projects. However, the impact of different approaches to design delegation in systems engineering is not well understood at a fundamental level. Improved understanding of design delegation in systems engineering will improve the efficiency and effectiveness of systems engineering projects and result in better-performing engineering systems. The objective of this research is to create a new behaviorally-informed modeling framework for decisions that occur during the design stages of a systems engineering project. The research will combine the mathematics of principal-agent theory with new empirical results about human judgment and decision-making behavior. This will enable the analysis of various decision delegation strategies in a manner that is supported by data about how engineering decision makers behave but at a scale impractical via human studies. It is anticipated that the new modeling framework will enable researchers to answer important questions about design delegation approaches, such as whether one method is superior to another under particular circumstances and the degree to which the performance of a method is sensitive to problem context. The research will contribute new knowledge about how engineers interpret and respond to incentives in their decision making and about how well-known methods for design delegation compare to one another.