A Joint Optimization Approach to Robust Inventory and Moral Hazard Problems

Dr. Zhaolin (Erick) Li received his Ph.D. in Business Administration from The Pennsylvania State University, a Master of Commerce in Accounting from The University of New South Wales, and a Bachelor of Engineering in Materials Science and Industrial Engineering from Shanghai Jiao Tong University. He has been a faculty member at The University of Sydney Business School since January 2009. Prior to his academic career in Sydney, Dr. Li worked at Ernst & Young LLP and City University of Hong Kong.

This presentation synthesizes two distinct yet methodologically connected research programs in operations and economics: one on robust optimization for inventory management and another on incentive design for moral hazard.

In the first part, we develop a joint optimization framework that circumvents numerous intermediate steps in the standard two-stage analysis. By imposing a unifying set of first-order conditions, we derive closed-form solutions for a broad class of inventory models, including the single-product-multi-sourcing problem and the W-shaped assemble-to-order system, revealing elegant symmetries and useful managerial insights.

The second part addresses a moral hazard problem in which an agent may fail to truthfully implement a stated action, instead taking a hidden and unproductive action that undermines the principal's payoff. This phenomenon is illustrated through poorly executed adaptations in the media publishing industry. Departing from the support line approach popular in theoretical economics, we reframe the problem using a primal-dual method, transforming it as a zero-sum game between the principal and nature, where nature selects an incentive-compatible hidden action that minimizes the principal's surplus. The tools of semi-infinite program not only predict the structure of the optimal contract but also extend naturally to a range of practical settings, including risk aversion, common agency, and team-based moral hazard.