Integrated operational and financial approaches in supply chain risk management

Abstract

Like other relatively more established sub-areas of Supply Chain Management, Supply Chain Risk Management (SCRM) is an emerging field that mostly lacks integrative approaches across disciplines. This study attempts to narrow this gap by developing an integrated approach to SCRM using operational tools and financial instruments. The conceptualization of SCRM is examined with reference to the broader literature on risk management. A SCRM framework is developed based on our taxonomies of risk and risk management approaches. Our unit of analysis is a supply chain composed of an aluminum can supplier, a brewery and a distributor. We develop a (base) stochastic optimization model that incorporates operational and financial features of the aforementioned supply chain. The supply chain is exposed to aluminum price fluctuation and demand uncertainty. Through simulation based optimization, we compare the performance of the integrated model (under which operational and financial hedging decisions are made simultaneously) to a sequential model (under which the financial decisions are made after the operational decisions are finalized, a common practice for many supply chains even today). Using experimental designs and statistical analyses, we analyze the performance of the two models in minimizing the expected total opportunity cost of the supply chain. We examine the supply chain performance in different business environments defined by iv three factors, each at three levels: risk aversion, demand variability and aluminum price volatility. We find that the integrated model outperforms the sequential model in most cases. The results also shed light on significant variations in supply chain performance under changing business environments. Managerial insights are offered based on optimization results and statistical analyses. The base model developed is then extended in two directions. First, we incorporate lead time variability as a fourth factor and study the effects of this variability. For the second extension, we introduce exchange rate risk into our base model. We examine the variations in the benefits of hedging exchange rate risk under two risk aversion levels and different exchange rate volatilities. Managerial insights on the findings of both extensions are provided. The thesis concludes with a summary of overall findings. Areas for further research are also highlighted.