This dissertation focuses on three cases of the following two stage problem in the context of multi-product inventories of vertically differentiated products. In Stage 1 of the problem, the manager determines the optimal production quantities of different products when the demands are uncertain. In Stage 2 of the problem, the demands for different products are observed. Now, the manager meets the demand of each product using the inventory of the product or by carrying out a downward substitution from the inventories of higher performance products. The manager’s objective is to maximize the expected revenue from the decisions made at the two stages collectively. The first problem addressed in this dissertation focuses on the case when different products are produced simultaneously on the same set of machines due to random variations in the manufacturing process. These systems, referred to as co-production systems, are very common in the semi- conductor industry, the textile industry and the agriculture industry. For this problem, we provide an analytical solution to the two stage problem, and discuss managerial insights that are specific to co-production systems and are not extendible to multi-item inventories of products that can be ordered or manufactured independently. The second problem addressed in this dissertation focuses on the case when different products can be ordered or manufactured independently, and no constraints to meet minimum fill rate requirements or to restrict the total inventory below a certain level are present. We present an analytical solution to this problem. The third problem addressed in this dissertation focuses on the case when different products can be ordered or manufactured independently and fill rate constraints and total inventory constraints are present. When the demands are multivariate normal, we show that this two stage problem can be reduced to a non-linear program using some new results for the determination of partial expectations. We also extend these results to higher order moments of the multivariate distribution and discuss their applications in solving some common operations management problems. / text

Optimization of materials supply and inbound logistic operations has become increasingly important as firms have continued to pursue outsourcing options. Further, the proliferation of products and advances in information technology have greatly impacted retailers’ marketing strategies in the past decade. In this dissertation, we address how to optimally develop integrated sourcing and delivery planning, and how to optimally offer vertically differentiated products and bundles. In the first essay, we address a combined sourcing and delivery planning optimization problem, which is motivated by a practical problem facing materials and supply planners for construction projects in a leading corporation. We develop a decision support model and an effective solution approach for integrated sourcing and delivery planning for bulk materials. This approach, implemented and currently in use at the company to support material delivery planning for track maintenance projects, has yielded significant savings of millions of dollars annually. In the second essay, we study the problem of a retailer managing a category of vertically differentiated products. We consider two settings: the exogenous prices case and the endogenous prices case. In the former case, the selling prices are exogenously determined and the retailer’s only decision is to determine the set of products to offer. In the latter case, the retailer also determines the selling prices. We develop efficient methods to identify the optimal solutions for both cases and provide valuable insights and guidelines for practitioners. In the third essay, we study how to choose the optimal bundling strategy for a retailer offering vertically differentiated information goods. We characterize conditions under which pure bundling and mixed bundling strategies are optimal respectively. We provide efficient methods to identify which individual components to offer, whether or not to offer a bundle containing all the components and how to price the offered individual components and the bundle in order to maximize the retailer’s profit. / text

Doctor of Philosophy / Department of Agricultural Economics / Tian Xia / This dissertation presents the development of a new approach to include the interaction of vertically differentiated products, a subject that has been largely ignored in previous studies, to analyze the market power of exporters and importers in the world markets of agricultural commodities. Three theoretical models, a residual demand elasticity (RDE) model, a residual supply elasticity (RSE) model, and a two-country partial equilibrium trade model, are developed, and the corresponding empirical models are specified for U.S.-Japan soybean trade. Genetically modified (GM) and non-genetically modified (non-GM) soybeans are vertically differentiated products in the sense that GM soybeans are largely defined as an inferior substitute to non-GM soybeans. I compare two versions of these models: a new approach in which the interaction between non-GM and GM soybeans is taken into account and the traditional approach in which the interaction is ignored. In each of the three models (the RDE model, the RSE model, and the partial equilibrium trade model), the traditional approach overestimates the market margin of U.S. non-GM soybean exporters and that of Japanese non-GM soybean importers. By considering the interaction between non-GM and GM soybeans, the new approach greatly reduces the estimates of the corresponding market margins of U.S. exporters and Japanese importers to improve the accuracy of such estimates. The statistical significance of the coefficient estimate of the interaction term, the U.S. GM soybean price or the Japanese GM soybean price, in all three models suggests that the new approach, which includes the interaction between non-GM and GM soybeans, is necessary and preferred. The partial equilibrium trade model includes both an RDE equation and an RSE equation in a system to address the possible contemporaneous cross-equation correlation. Thus, the estimation results of the partial equilibrium trade model are further improved, compared to those of the RDE model and the RSE model. Using the traditional approach to estimate the partial equilibrium trade model, I find that the U.S. non-GM soybean exporters’ market margin is 56.5% and the Japanese non-GM soybean importers’ market margin is 16.1%. However, the results obtained by using the new approach show that the market margins of U.S. exporters and Japanese importers are 33.2% and 6%, respectively. By taking into account the interaction between non-GM and GM soybeans, the new approach improves the accuracy of the estimates of market margins of soybean exporters and importers. U.S. non-GM soybean exporters do have a significant market margin in international markets, but it is not as large as the one suggested by the traditional approach. Although Japanese non-GM soybean importers enjoy some market margin, it is relatively small. The theoretical and empirical models and results in this dissertation provide new and more accurate estimates of residual demand and supply elasticities and market power and improve the understanding on world soybean markets. These results can be useful for industry participants in international soybean markets, academic researchers, and policy makers.