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題名:探究人工智慧驅動的知識管理對組織績效的影響:以數位化轉型過程中的銀行業為實證研究案例
作者:呂沛
作者(外文):LYU PEI
校院名稱:實踐大學
系所名稱:管理學院創意產業博士班
指導教授:謝明宏
學位類別:博士
出版日期:2024
主題關鍵詞:組織績效知識管理知識流動人工智慧隱性知識Organizational PerformanceKnowledge ManagementKnowledge FlowsArtificial IntelligenceTacit Knowledge
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本研究討論了當今數位經濟時代,數位轉型過程中的銀行業如何利用人工智慧科技提升員工工作能力與服務質量,進而提升組織績效。本研究的核心問題是,人工智慧科技如何協助「知識管理」提升「組織績效」。本研究採用案例研究的方法,對一家全球領先的中國國有銀行引入人工智慧知識管理系統的個案進行了調查。本研究結果表明,人工智慧科技可透過提升知識流動(Knowledge Flows, KF)有效性正向影響組織績效。此外,本研究也指出,目前組織知識流動(KF)範圍的限制阻礙組織績效進一步提升。本研究透過銀行實務案例與知識流動(KF)、知識螺旋(SECI)理論的對話,為運用知識管理科技(Knowledge Management Technologies, KMT)提升組織績效的策略方法提供建議。同時,本研究豐富了人工智慧對隱性知識管理的操作方法,對其他產業的知識管理實務也有一定的指導意義。最後,本研究也從組織績效視角,揭示了現有知識管理科技面臨的問題與挑戰,同時提出限制以及未來研究方向的建議。
This study discusses how the banking industry, in the process of digital transformation during the current digital economy era, can utilize artificial intelligence technology to enhance employee work capabilities and service quality, thereby improving the Organizational Performance. The core issue of this study is how artificial intelligence technology can assist in "Knowledge Management" to enhance "Organizational Performance". This study uses the Case Study Method to investigate a case of a leading Chinese state-owned bank with a global presence, implementing an artificial intelligence Knowledge Management System. The results of this study indicate that artificial intelligence technology can positively impact Organizational Performance by enhancing the effectiveness of Knowledge Flows. Furthermore, this study also points out that the current limitations of organizational Knowledge Flows impede further improvement in Organizational Performance. This study, through the dialogue between banking practice cases and theories of Knowledge Flow and the SECI model (Socialization, Externalization, Combination, Internalization), offers suggestions for strategy to enhance Organizational Performance by utilizing Knowledge Management Technologies (KMT). At the same time, this study enriches the operational methods of artificial intelligence for Tacit Knowledge Management, which also has certain guiding significance for Knowledge Management practices in other industries. Lastly, from the perspective of Organizational Performance, this study reveals the problems and challenges faced by current Knowledge Management technologies, while also suggesting limitations and directions for future research.
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