For many firms, particularly those operating in high technology and competitive markets, knowledge is cited as the most important strategic asset to the firm, which significantly drives its survival and success. Knowledge management (KM) impacts the firm's ability to develop process features that reduce manufacturing costs, product designs with the features and functionality to match consumer demand, and time to market. Unfortunately, many firms lack an understanding of how to develop and exploit knowledge capabilities for success. In this thesis I develop a rich and multifaceted understanding of how KM strategies lead to successful outcomes for a firm. The thesis comprises three essays, described below. The first essay (Chapter 2) examines how volume-based learning influences the relationship between a buyer and supplier in a two-period Stackelberg game. Three types of knowledge management practices are considered. First, in contrast to the literature, I recognize that knowledge accumulated from current in-house production contributes to the buyer's future product and process development efforts. Second, I allow the supplier to invest in integration process improvement (a form of knowledge development) to reduce the buyer's integration cost. Therefore, the supplier has two mechanisms to impact the buyer's demand: price and process improvement. Lastly, both the buyer and supplier benefit from volume-based learning that reduces their respective production costs. I provide conditions under which the buyer partially outsources component demand as opposed to fully outsourcing or fully producing in-house. In addition, I identify conditions for which the supplier's price and investment in integration process improvement can serve either as substitutes or complements. In the second essay (Chapter 3), I consider knowledge development (KD) strategies in a new product development (NPD) project with three stages of activities conducted concurrently: prototyping, pilot line testing, and production ramp-up. I capture the link between successive stages of engineering activities by recognizing that knowledge accumulated in one stage and transferred to another stage improves the efficiency of knowledge development in the recipient stage. A Base Model and two extensions are introduced that differ in the manner in which knowledge transfer (KT) occurs. I find that the NPD manager pursues different dynamic strategies for KD in each stage of the project. In addition, I explore how the effectiveness of KD and the returns to KT impact the optimal strategies adopted in each stage. In the third essay (Chapter 4), I introduce a dynamic model to explore the impact of KT on a manager?s pursuit of an existing product improvement project and a new product development project. These two projects consume costly knowledge development resources. A key feature of the model is the characterization of the knowledge transfer process from the new product development project to the existing product improvement project. As a result of KT, the ability of the existing product improvement project to generate new knowledge is enhanced. However, the ability of the new product to generate expected net revenue when it is released to the marketplace is reduced due to the loss of proprietary knowledge. I obtain dynamic optimal strategies of KD in both projects and the optimal strategy of KT from the new product development project to the existing product improvement project.
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