| Summary: | Supply chains for time-sensitive products, and, in particular, for perishable products, pose specific and unique challenges. By definition, a perishable product has a limited lifetime during which it can be used, after which it should be discarded (Federgruen, Prastacos, and Zipkin (1986)). In this dissertation, I contribute to the analysis, design, and management of supply chain networks for perishable products with applications to healthcare. Specifically, I construct generalized network frameworks to capture perishable product supply chains in healthcare operating under either centralized or decentralized decision-making behavior. The dissertation is motivated by applications ranging from blood supply chains to pharmaceuticals, such as vaccines and medicines. The novelty of the modeling and computational framework includes the use of arc multipliers to capture the perishability of the healthcare product(s), along with waste management costs, and risk. The first part of the dissertation consists of a literature review of perishable product supply chains with a focus on healthcare along with an overview of the relevant methodologies. The second part of the dissertation formulates supply chains in healthcare operating under centralized decision-making behavior. In this part, I focus on both the operations management of and the sustainable design of blood supply chains and construct models for regionalized blood banking systems as belonging to the Red Cross. The third part of the dissertation considers competitive behavior, with a focus on the pharmaceutical industry. I construct an oligopoly supply chain network model, with differentiated brands to capture the competition among producers of substitutable drugs using game theory and variational inequality theory. Furthermore, using a case study based on real-world scenarios of a highly popular cholesterol-reducing branded drug, the impact of patent rights expiration of that brand is explored which coincides the time when its equivalent generic emerges into the markets. The calculated results are then compared to the observations from the real-word problem. Finally, the projected dynamical system formulation of the pharmaceutical network oligopoly model is derived. This dissertation is based on the following papers: Nagurney, Masoumi, and Yu (2012), Nagurney and Masoumi (2012), and Masoumi, Yu, and Nagurney (2012) as well as additional results and conclusions.
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