Models addressing sustainability and risk issues in global supply chains

Global supply chains have become increasingly complex, interconnected and interdependent, thus, managing this complexity and the associated supply chain risks is the key for a firm to gain and maintain competitive advantage. Nowadays, sustainability has introduced another layer to supply chain complexity, and addressing supply chain risks and sustainability issues together are the two greatest concerns for supply chain executives. 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 volatility risk between a buyer and a supplier in global supply chains during outsourcing. 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 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 cost in the supplier selection and order allocation problem, often encountered in outsourcing manufacturing. An integrated model that utilizes principal component analysis-based approach for evaluating supplier's sustainability performance and a bi-objective mixed integer programming model for supplier selection and order quantity allocation is developed. Then, an illustrative example of outsourcing contract manufacturers in the US apparel industry is presented to demonstrate the applicability of the proposed framework in practice. The final strategic issue examined in this dissertation is the design of an integrated production-distribution network to reduce environmental risk, which focuses on the minimization of carbon emissions from transportation activities in the entire supply chain. A mixed integer linear programming model is developed for a three-echelon supply chain network design problem, in a deterministic, multi-period, multi-product environment with a finite planning horizon. This model minimizes the total supply chain cost and solves strategic, tactical, and operational decision-making problems which include: locating distribution centers, the quantity of each product to produce, frequency of flow of delivery vehicles, as well as the allocation of inventory to each echelon of the supply chain. A numerical study is conducted through illustrative examples in order to demonstrate the applicability of this model and gain some managerial insights.