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Some owners of small-farm wineries have moved to direct and alternative revenue management strategies to generate revenue and create brand awareness because of increased competition and regulatory changes. Research has revealed that owners of small-farm wineries remain financially reliant on direct-to-consumer sales through tasting rooms that represent an estimated 70% of their total revenue generated. This qualitative multiple case study was an exploration of how revenue management decisions of small-farm winery owners may contribute to long-term survival in a regulated industry. Dynamic capabilities concept was the conceptual framework for this study. The study population consisted of 3 small-farm winery owners in Connecticut who have operated a winery with Connecticut Grown designation for at least 10 years. Data were collected through semistructured interviews, organizational documents, observation notes, and review of each winery's website. Three themes emerged from data analysis: focus on brand and customer base, constraints consideration, and competitors' impact. The findings and recommendations from this study may further small-farm winery owners' understanding of revenue management strategies they can use to overcome constraint challenges and mitigate competitors' impact. As small-farm winery owners improve profitability and sustain long-term survival, subsequent positive social change, such as small business development and increased employment opportunities, may lead to economic prosperity for the local community and financial stability of community residents.

Lowering the degree of component commonality may yield a higher type-II service level for a periodic review assemble-to-order system that aims to maximize reward. This is achieved via separating inventories of all the shared components for different products. We investigate the optimal bill-of-materials structure for two-product assemble-to-order systems with arbitrary number of components. The inventory of a shared component can be separated or common between different products. We show that an optimal bill-of-materials can be characterized between the following two extremal configurations: either two products share all common components, or they do not share any common component. / Thesis / Doctor of Philosophy (PhD)

Manufacturing outsourcing in the U.S. has never been stronger than it is today. Increased outsourcing has led to significant changes in the design of the retail distribution network. While the traditional distribution network had the manufacturing plants supplying goods to the retail stores directly, the off-shore manufacturing has increased the network's demand for transportation and warehousing to deliver the goods. Thus, most companies have a complex distribution network with several import and regional distribution centers (RDC). In this thesis, we study an integrated facility location and inventory allocation problem for designing a distribution network with multiple national (import) distribution centers (NDC) and retailers. The key decisions are where to locate the RDCs and how much inventory to hold at the different locations such that the total network cost is minimized under a pre-defined operational rule for the distribution of goods. In particular, the inventory cost analysis is based on the continuous review batch ordering policy and the base-stock policy. Both Type-I (probability of stock-outs) and Type-II (fill-rate) service level measures are used in the analysis. Two different models are presented in this thesis for solving the integrated facility location-inventory allocation problem. The first model, continuous approximation (CA), assumes the distribution network to be located in a continuous region and replaces the discrete store locations with a store density function. The second model is a discrete representation of the problem as a mixed integer programming problem. Both the models take a nonlinear form and solution techniques are developed using the theory of nonlinear programming and linear reformulation of nonlinear problems. The goal of the first part of the thesis is to model the problem using a modified CA approach and an iterative solution scheme is presented to solve it. The main contribution of this work lies in developing a refined CA modeling technique when the discrete data cannot be modeled by a continuous function. In addition, the numerical analysis suggests that the total network cost is significantly lower in the case of the integrated model as compared with the non-integrated model. It is also shown that the regular CA approach leads to a solution which is inferior to the solution obtained by the modified CA approach. Our analysis shows that the type of service measure used affects the network design. In the second part of the thesis, the problem is modeled as a nonlinear mixed integer program and a linear reformulation solution technique is proposed to obtain a lower bound on the original problem. Computational results are presented for small problem instances. We conclude this part of the thesis by presenting an integrated model when a base stock inventory policy is used. A drop-decomposition heuristic is proposed to solve this problem.