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Modeling and optimizing the motivation of workers and managers for knowledge-sharing: a game-theoretic analysis

机译：建模和优化工人和管理者共享知识的动机：博弈论分析

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Knowledge management (KM) is especially difficult to implement for project-based work. Tacit knowledge gained during projects diffuses when project teams disband and reform. Organizations are increasingly focusing on managing their knowledge flows, developing or investing in KM systems. Knowledge-sharing (KS) behaviors are the main input to KM systems, so we aim to optimize knowledge input to magnify the usefulness of KM systems. We adopt game-theoretic models to analyze workers' knowledge-sharing dynamics under different KM strategies, taking managers' viewpoints. We will solve Nash Equilibria by identifying associated conditions on each equilibrium path, and derive implications from these condition for KM strategies. We will explore: (1) types of knowledge that deserve sharing; (2) types of employees that possess different knowledge; (3) incentives that cause the right individuals to share useful knowledge; and (4) costs and benefits associated with alternative company KM strategies. We plan to validate these theoretical results via an empirical study. This paper lays out the problem, discusses the key points of departure, and presents our initial version of a game tree for employees' decisions about knowledge sharing. Interviews will subsequently be conducted to validate the game tree, Nash Equilibria, and implications for knowledge management in project-based firms.
机译：对于基于项目的工作，知识管理（KM）尤其难以实施。当项目团队解散和改革时，在项目期间获得的隐性知识会扩散开来。组织越来越关注于管理知识流，开发或投资KM系统。知识共享（KS）行为是KM系统的主要输入，因此我们旨在优化知识输入以扩大KM系统的实用性。我们采用博弈论模型来分析不同知识管理策略下工人的知识共享动态，并采用管理者的观点。我们将通过确定每个平衡路径上的关联条件来解决纳什均衡，并从这些条件中得出对KM策略的含义。我们将探索：（1）值得分享的知识类型； （2）具有不同知识的员工类型； （3）促使适当的个人分享有用知识的激励措施； （4）与替代公司KM策略相关的成本和收益。我们计划通过一项实证研究来验证这些理论结果。本文列出了问题所在，讨论了离职的关键点，并提出了我们的初始版本的博弈树，供员工做出有关知识共享的决策。随后将进行访谈，以验证博弈树，纳什均衡以及对基于项目的公司中知识管理的影响。

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