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ItemSynchronizing exploration and exploitation: knowledge creation challenges in innovation(Georgia Institute of Technology, 2013-11-18) Bailey, JenniferInnovation requires an ambidextrous knowledge creation strategy, which is defined as the simultaneous pursuit of both exploration and exploitation. A temporal ambidexterity strategy is one in which an organizational unit dynamically balances its investments in exploration and exploitation over time. This thesis provides new insights on various factors which should be considered when developing and executing a temporal ambidexterity strategy. In the Essay 1, I empirically examine the impact of exploration, exploitation and learning from cumulative innovation experience on the likelihood of successfully versus unsuccessfully generating a breakthrough innovation. The data sample, based on patents in the biomedical device industry, is drawn from the National Bureau of Economic Research patents database. I demonstrate three important tenets for developing a theory of temporal ambidexterity. First, I confirm, as conceptually expected, that when pursued independently, exploration and exploitation have opposing variance-generating versus variance-reducing impacts on innovation performance, respectively. Second, I find that when pursued jointly exploration and exploitation have a negative interaction effect on innovation performance. Third, I show that the benefits of ambidexterity accrue in the long-term, as a result of learning from prior failure experience. However, I demonstrate that prior failure experience and exploitation are jointly necessary, but not independently sufficient, for learning from failure to occur. In Essay 2, I introduce a dynamic optimization model of temporal ambidexterity. I examine the optimal sequencing of exploration and exploitation knowledge creation activities throughout the innovation process. I consider how an innovation manager’s optimal dynamic investments in exploration and exploitation are driven by the innovation team’s knowledge creation capabilities and prior innovation experience, and by the manager’s short-term and long-term innovation risk objectives. The results demonstrate the conditions under which various temporal ambidexterity strategies endogenously arise. Finally, in Essay 3, I extend the single firm model introduced in Essay 2, to develop a model of temporal ambidexterity for two firms jointly pursuing knowledge creation and knowledge-sharing under co-opetition. Here, I consider how co-opetition, that is, cooperative knowledge-sharing with a competitor, impacts a firm’s optimal ambidextrous knowledge creation strategy. I consider two-way knowledge sharing, and I assume that each firm freely reveals its knowledge to its competitor, without receiving compensation. The dynamic analytical results contribute to the open questions regarding optimal knowledge-sharing strategies under co-opetition, by demonstrating under what conditions knowledge-sharing with a co-opetitive partner is beneficial. Importantly, I also analytically examine the factors which drive empirically observed alliance dysfunctions, wherein organizations delay knowledge-sharing and withhold information from their alliance partners.
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ItemEssays on knowledge management(Georgia Institute of Technology, 2013-01-04) Xiao, WenliFor 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.