Gbemileke Ogunranti, PhD Candidate at Drexel University

Title: Models Addressing Sustainability and Risk Issues in Global Supply Chains

Abstract: Global supply chains have become increasingly complex, interconnected and interdependent, thus, managing this complexity and associated supply chain risks are key for a firm to gain a competitive advantage. While managing supply chain risks are very important to firms, sustainability has introduced another layer to supply chain complexity. Nowadays, two greatest concerns for supply chain executives is how to address supply chain risks and sustainability issues together. Thus, this dissertation explores three important strategic issues in global supply chains. The first strategic issue deals with the design of contracts to mitigate the exchange rate risk between a buyer and a supplier in global supply chains. Two types of currency exchange rate flexibility contracts are proposed to explore the characteristics of exchange rate risk mitigation policies for the buyer and the supplier. Furthermore, the effects of the contract structures on the optimal order quantity, as well as the expected profits of both supply chain members are investigated. The second major issue addressed focuses on the trade-off between supply chain sustainability-related risks and low-cost in supplier selection and order allocation problem, often encountered in outsourcing contract manufacturing. An integrated model that utilizes principal component analysis based approach for evaluating a supplier’s sustainability performance and bi-objective mixed integer programming model for suppliers’ selection and order quantity allocation was developed. Then, an illustrative example of outsourcing contract manufacturers in the US apparel industry was presented to demonstrate the applicability of the proposed framework in practice. Finally, the last strategic issue examined in this dissertation is the design of an integrated production-distribution network to reduce environmental risk, particularly minimizing carbon emissions from transportation in the entire supply chain. A mixed integer linear programming model was developed for a three-echelon supply chain network design problem in a deterministic, multi-period, multi-product within a finite planning horizon. The model minimizes the total supply chain cost and solves strategic, tactical, and operational decision-making which includes locating distribution centers, how much quantity of each product to produce, the frequency of flow of delivery truck, as well as the allocation in each echelon of the supply chain. A numerical study was conducted through example problems to demonstrate the applicability of this model and gain some managerial insights.