By Violet Chen
The Tuesday afternoon session on Operations and Economics Interface consisted of four talks; each integrates some economic concepts in operations questions. I am the first presenter of this session. My talk is based on a joint project with Dr. John Hooker titled “Combining Leximax Fairness and Utilitarianism in a Mathematical Programming Model.” The primary purpose of our work is to develop a new modeling approach to characterize a trade-off between equity and efficiency. Extending previous work on combining Rawlsian maximin fairness and utilitarianism, we define a sequence of social welfare functions as a combined measure of leximax fairness and utilitarianism. The definition follows the key principle to be equitable until equity sacrifices too much efficiency. Using these functions, we propose a sequential optimization procedure to select optimal outcome with respect to equity-efficiency trade-off. For practical implementation, we give MILP representation for each iteration’s optimization model.
Dr. Parinaz Naghizadeh, Assistant Professor in Integrated Systems Engineering and Electrical and Computer Engineering at The Ohio State University, shared her work on “Relational Contracts with Prediction.” In this joint project with Dr. Thanh Nguyen and Dr. Shai Vardi, they study relational contracts between supplier and retailer. Their work addresses uncertainty in production value of the contract by extending the classical model of relational contracts to consider the case, where the retailer receives prediction of the supply quality. When a retailer is informed that next period’s production quality from the partnering supplier will be low, the retailer may be incentivized to break contract and look for a better supply match; namely, prediction may undermine long-term commitment. Motivated by this observation, they study the trade-off between prediction and commitment, and conclude that relational contracts “incentivize suppliers for lower effort, reducing the production quality,” but retailer may prevent quality decrease by promising bonuses to a supplier when predicted quality is high.
The third presentation was given by Dr. Houcai Shen, Professor in Management Science and Engineering from Nanjing University. He presented “Inventory Risk Management in Supply Chain: Pricing and Contracts,” joint work with Dr. Weili Xue. Their problem studies a supply chain consisting of a single supplier selling a single product to an independent retailer. The retailer faces price-dependent stochastic demands. The supplier has two options for distribution contracts: push contract, where the retailer orders before market uncertainty realization; and pull contract, where orders are placed after uncertainty realization. The retailer has two pricing strategies: committed pricing strategy, where price is chosen before demand realization; and responsive pricing strategy, where price is chosen afterward. They conduct extensive comparative analysis of operational decisions from the supplier and the retailer. Their results answer the following: effects of wholesale contracts and retail pricing strategies on supply chain operations, interaction between supplier wholesale contract and retailer pricing decisions, and supply chain’s strategic equilibrium in terms of contract and pricing.
Laharish Guntuka, PhD student in Supply Chain Management from the University of Maryland, concluded this session by presenting his research on “The Impact of Supply Chain Complexity on a Plant’s Recovery Time.” In this joint work with Dr. David Cantor and Dr. Thomas Corsi, they examine how supply chain complexity can impact the supply chain’s resilience to disruption, whether the relationship is affected by product complexity, as well as differential impacts of internal and external disruptions. Their work aims to fill a gap in literature by theorizing the relationship and empirically examining various hypothesized relationships with manufacturing plant level data. Three dimensions of supply chain complexity are captured in their hypotheses: upstream, internal, and downstream. Additionally, they study how factors like exogenous vulnerability risks, revenue at risk, and the plant characteristics moderate the complexity-resilience relationship.