Transfer of intellectual property (IP) is vulnerable to hidden actions (such as drastic adaptations in licensed content, patent infringement, or unauthorized use) that can severely erode IP commercial values. While laws and regulations prohibit overtly reckless behaviour, our focus is on mitigating unproductive actions that fall beyond the reach of such rules. We study the design of incentive contracts for IP transfer when the IP owner cannot foresee all possible actions that other parties might take. Employing a robust moral hazard framework, we characterize the robust optimal contract taking a simple linear form. Methodologically, we depart from the standard support line approach and instead apply the primal-dual theory. This method yields a more efficient proof, and more importantly, it provides a unifying framework for analysing related problems, including team moral hazard, common agency, dynamic moral hazard, and risk aversion (whereby the support line method fails due to nonlinear preferences). It also unlocks data-driven methods that deliver surplus to the IP owner exceeding predictions made by theoretical economists. Our findings offer actionable guidance for managers and technology transfer offices seeking to protect IP values under unforeseen actions.
Erick Li is an Associate Professor in the School of Business Analytics and Marketing at the University of Sydney. He holds a PhD in Business Administration from Pennsylvania State University and a Bachelor of Engineering from Shanghai Jiao Tong University. His academic career includes roles at the University of Sydney (since 2009) and City University of Hong Kong (2005–2008). His research applies robust optimization and contract theory to solve problems in project, operations, and supply chain management.
His research achievements include: