Supply Chain Network Competition in Time-Sensitive Markets

We develop a game theory model for supply chain network competition in time-sensitive markets in which consumers respond to the average delivery time associated with the various firms’ products. The firms’ behavior is captured, along with the supply chain network topologies, with the governing equilibrium concept being that of Nash equilibrium. We derive the variational inequality formulation of the equilibrium conditions and provide illustrative examples. We also identify special cases for distinct applications. An algorithm is proposed, and the framework further illustrated through a case study in which we explore varying sensitivities to the average time delivery with interesting results

Research on closed-loop supply chain network equilibrium with two-type suppliers, risk-averse manufacturers and capacity constraints

Purpose: the aim of this paper is to investigate the closed-loop supply chain (CLSC) network equilibrium wiht the consideration of three practical factors: two complementary types of suppliers, risk-averse character of the manufacturer and capacity constraints of the suppliers. Design/methodology/approach: The equilibrium of various decision makers including the suppliers, the manufacturers, the retailers, the collectors and the demand markets are modeled via finite-dimensional variational inequality, respectively. Then the governing CLSC network equilibrium model is established. The logarithmic-quadratic proximal prediction-correction algorithm is designed to solve the variational inequality model. Numerical examples are given to analyze the impact of return rate, risk-averse degree and capacity constraints on the network equilibrium under different product BOMs. Findings: with the increase of return rate, the profits of various channel members and the performance of the CLSC system will improve. There is a contradiction between profit maximization and risk minimization for the manufacturers. Moreover, the economic behavior of the CLSC is likely to be limited by the capacity constraints of the suppliers. Originality/value: Prior to this paper, few papers have addressed with the CLSC network equilibrium considering some practical factors. They assume all the suppliers are identical and all the decision-makers are risk neutral. Furthermore, the production capacities of all suppliers are assumed to be infinite or large enough. To fill the gap, this paper examines the influences of two-type suppliers, risk aversion and capacity constraints upon the CLSC network equilibrium.Peer Reviewe

ESSAYS ON COMPETITIVE PERISHABLE FOOD SUPPLY CHAIN NETWORKS: FROM THE IMPACTS OF TARIFFS AND QUOTAS TO INTEGRATION OF QUALITY

Food, in the form of fresh produce, meat, fish, and/or dairy, is necessary for maintaining life. In this dissertation, I focus on the modeling and analysis of some of the inherent issues in competitive perishable food supply chain networks. I investigate the impacts of trade policies such as tariffs, quotas, and their combination – tariff-rate quotas, as well as the integration of food quality deterioration into food supply chains. The research is especially timely given the prevalence of trade wars and tariffs in todays global political environment. The work is multidisciplinary with constructs from food science integrated into the economics of supply chain networks. The first part of the dissertation overviews the methodological foundations including game theory, network and optimization theory, and variational inequality theory used for the construction and solution of the supply chain network models. In the second part of the dissertation, I first focus on perfectly competitive problems and develop a unified variational inequality framework for spatial price network equilibrium problems with tariff-rate quotas. The accompanying case study on the dairy industry is based on trade between the United States and France. The computational results reveal that tariff-rate quotas may protect domestic producers from foreign competition, but at the expense of higher demand prices for consumers. This work is based on the paper by Nagurney, Besik, and Dong (2019). I then develop an oligopolistic supply chain network equilibrium model with differentiated products consisting of multiple firms, production sites, and demand markets, in which firms compete on product quantities and also quality. I provide a case study on soybeans, an important agricultural product, and investigate different scenarios. Insights as to firm profits and trade volumes, the average product quality, and consumer welfare, are also delineated. Specifically, I find that, although firms may benefit from the imposition of a quota or tariff, the welfare of consumers in the country imposing the quota or tariff declines. This work is based on the paper by Nagurney, Besik, and Li (2019). In the third part of my dissertation, I demonstrate how to incorporate quality deterioration of fresh produce into perishable supply chain network models. I construct an explicit equation for fresh produce quality deterioration based on time and temperature of different pathways in supply chain networks. I first incorporate this feature into local markets in the form of farmers’ markets, which serve as examples of direct to consumer channels and shorter supply chain networks. I also provide a case study of apples in western Massachusetts, under various scenarios, including production disruptions, due to negative weather conditions, resulting in an increase in apple prices at farmers’ markets, a decrease in quality, and a decrease in profits for the apple orchards. These results can be used to inform food firms, policy makers, and regulators. This work is based on the paper by Besik and Nagurney (2017). Subsequently, I develop a competitive food supply chain network model in which the profit-maximizing producers decide not only as to the volume of fresh produce, but they also decide on the initial quality of fresh produce, with associated costs. I incorporate quality deterioration of the fresh produce explicitly with chemical functions depending on time, temperature, and the initial quality of the food product. I then present a case study on peaches, with supply chain disruptions to reveal valuable insights. I find that the disruptions in production result in higher demand prices, and lower initial quality. This is the first such general supply chain network model constructed to include the initial quality of fresh produce. This part of the dissertation is based on the paper by Nagurney, Besik, and Yu (2018)

Blood Supply Chain Networks in Healthcare: Game Theory Models and Numerical Case Studies

A crucial component of every healthcare system is the safe and steady supply of the life-saving product, blood. In order to meet the demand for blood consistently, it is imperative to maintain a robust supply chain. The blood banking industry in the United States, faced with emerging challenges, which include, an increase in operating costs, rise in competition among blood centers, insufficient reimbursement from payers such as insurance companies and government programs, in addition to inherent challenges such as donor motivation, seasonal shortages, perishability, is trying to adapt to the changing dynamics to sustain itself economically. The altruistic nature of this industry and the financial implications for its various stakeholders, makes the efficient management of blood supply chains an important and interesting area of study. In this dissertation, I contribute to the existing literature on blood banking by modeling the operational and economic challenges throughout the blood supply chain in the context of competition using game theory. I develop a model for blood service organizations competing for donations where they use service quality levels at collection sites as their strategic variables to increase their collection of blood from voluntary donors. I further construct a competitive blood supply chain network model that captures all major activities as well as perishability along the supply chain from collection of blood to distribution to hospitals. As a crucial extension to the study on blood supply chains, I develop a network framework with multiple tiers of decision-makers including payers, that captures the decentralized nature of the blood banking system in the United States. The solutions from this multi-objective decision-making problem include quantities of blood to be supplied and transfused, given demand is known, as well as the financial transactions between the different tiers of stakeholders. For each model the governing equilibrium conditions are derived, and equivalent variational inequality formulations presented. The models and their relevance are further illustrated through simulated case studies. The results obtained provide valuable insights that can inform healthcare policy makers and regulators