| My dissertation topic lies under the general theme of supply chain risk management. Over the past decade, firms have observed more supply chain vulnerability than ever due to the extensiveness and complexity of today's supply chains. I explore risk management strategies that maintain firms' profitability while allowing them to avoid severe supply chain disruption. More specifically, I am interested in strategies that utilize quantity flexible contracts and multiple supply sources for risk mitigation. My dissertation consists of three separate essays. A summary of each essay follows.;In the first essay, I develop a set of decision rules for a buying firm to develop the optimal sourcing strategy when facing demand and supply risks. The study is motivated by a buyer who seeks to minimize expected sourcing costs by diversifying to address its supply and demand risks. The firm makes use of quantity flexible contracts and sources from a combination of outsourcing, offshoring, and/or in-house production. Quantity flexible contracts introduce multiple stages that allow the buyer to postpone certain decisions to reduce risk impacts.;The second essay is a numerical study follow-up to the first essay. The analysis attempts to determine when the assumed forms of the probability distributions for sourcing risk and demand significantly impact the buyer's sourcing strategy. And when they do, by how much? I explore the characteristics of the optimal sourcing policy with respect to various demand distributions and logistics risk distributions via simulation.;The third essay investigates how to apply a technique called "predictive global sensitivity analysis" to operational hedging. Operational hedging is different from traditional financial hedging that involves purchasing currency options. Operational hedging establishes excess capacity around the world and then shifts production to favorable countries as exchange rate fluctuations dictate. The predictive global sensitivity analysis creates a set of structural equations, and these equations enable managers to recommend production reallocation levels while remaining accurate enough to make sound decisions. . |
