Integration of product architecture and supply chain under currency exchange rate fluctuation

Abstract

Various studies have discussed the coordination of product and supply chain design decisions for global supply chain management. However, the impact of currency exchange rate uncertainty on the selection of product architectures and their suppliers has not been sufficiently addressed. As a response, this study proposes a two-stage stochastic optimization model in which the first stage determines the product architecture, and the second stage identifies suppliers for the modules and components in an optimal fashion based on the product architecture and uncertain currency exchange rates. The overall objective of twostage stochastic programming is to determine the optimal product architecture that minimizes the expected total supply chain cost over uncertain currency exchange rate scenarios. The proposed model is applied to a bicycle supply chain case study for three global marketplaces associated with multiple currency exchange rates. The results demonstrate that optimal product architecture and its suppliers should be varied based on currency exchange rates and their uncertain fluctuation levels. Also, a product architecture for the supply chain of each marketplace maintains its optimality in the total supply chain cost, up to a specific exchange rate. The findings show the importance of joint integration between product and supply chain design when considering currency exchange rates. Additionally, the benefit of stochastic modelling is demonstrated by comparing the solution quality of the model with its deterministic counterpart.

A Concurrence Optimization Model for Low-Carbon Product Family Design and the Procurement Plan of Components under Uncertainty

“…In the model, we assumed that the purchase price is stable. However, if the international supply chain is considered, the purchase prices may fluctuate due to uncertain currency exchange rates (Gunay et al [37]). In the model, the production cost was considered as a crisp value, and it can be extended to consider the fuzzy production cost (Kumar et al [38]).…”