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研究生: 褚喻欣
Yu-Shin Chu
論文名稱: 學習導向、資訊科技、知識基礎動態能力與組織績效間之關係探討
The Impacts of Learning Orientation, IT Infrastructure, and Knowledge-based Dynamic Capability on Firm Performance
指導教授: 王存國
Tswen-Gwo Wang
口試委員:
學位類別: 碩士
Master
系所名稱: 管理學院 - 資訊管理學系
Department of Information Management
畢業學年度: 92
語文別: 英文
論文頁數: 78
中文關鍵詞: 組織績效知識基礎動態能力資訊科技對知識管理支援學習導向資訊科技基礎建設
外文關鍵詞: Learning Orientation, IT support for KM, IT infrastructure capability, Knowledge-based dynamic capability, Firm performance
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  • 在競爭激烈的環境之下,企業要如何透過快速調整資源,以維持或創造良好的組織績效,一直是企業界及學術界關心的議題。本研究從知識的觀點來探討組織的學習導向、資訊科技基礎建設能力及知識基礎動態能力對組織績效的影響。而組織學習導向及其資訊科技基礎建設能力,會影響組織調整其各領域知識基礎的速度;因此,也欲了解學習導向及資訊科技基礎建設能力經由動態能力作為中介變數,對組織績效的影響效果。此外,資訊科技對知識管理的支援程度,也和組織知識的動態調整息息相關;故本研究亦將資訊科技對知識管理的支援作為一中介變數,探討組織的學習導向及其資訊科技基礎建設能歷經由資訊科技對知識管理支援的中介,對組織知識基礎動態能力的影響效果。
    本研究以台灣地區的製造業及服務業為研究對象,研究結果顯示:(1)知識基礎動態能力對組織績效有正向的影響效果;(2)學習導向會經由知識基礎動態能力的中介,而對組織績效產生正向的影響效果;(3)學習導向與資訊科技對知識管理的支援對知識基礎動態能力皆有正向的影響效果;(4)學習導向對資訊科技對知識管理的支援有正向的影響效果;(5)資訊科技基礎建設能力對於知識管理的支援、知識基礎動態能力以及組織績效的影響未獲支持。研究結果、限制及管理上的意涵在論文中皆有詳述。


    With the coming of global competition, it is an important issue for firms to create and sustain competitive advantage by responding to the rapidly changing environment. This study takes a knowledge perspective to examine the relationships between variables, such as learning orientation, IT infrastructure capability, and knowledge-based dynamic capability, and firm performance. Besides, learning orientation and IT infrastructure capability can have effects on the speed for firms to adjust their knowledge base; therefore, this study also explore whether learning orientation and IT infrastructure capability may influence firm performance through the mediation of knowledge-based dynamic capability. Moreover, IT support for KM is also related to the adjustment of firm’s knowledge; thus, this study also treats IT support for KM as a mediator to examine whether learning orientation and IT infrastructure capability have influences on knowledge-based dynamic capability.
    This study was conducted with firms from manufacturing industries and service industries in Taiwan. Results indicate that: (1) knowledge-based dynamic capability has positive influence on firm performance; (2) learning orientation has positive influence on firm performance through the mediation of knowledge-based dynamic capability; (3) learning orientation and IT support for KM both have positive influence on knowledge-based dynamic capability; (4) learning orientation has positive influence on IT support for KM; (5) the influences of IT infrastructure capability on IT support for KM, knowledge-based dynamic capability and firm performance are not supported. The results, implications and limitations of this study are also discussed.

    Contents 1. Introduction 1 2. Literature review 4 2.1 Learning Orientation 4 2.2 IT Infrastructure Capability 7 2.3 IT Support for KM 10 2.4 Knowledge-based Dynamic Capabilities 14 2.5 Firm Performance 18 3. Research model and hypotheses 19 3.1 Research model 19 3.2 Hypotheses 21 3.2.1 Learning orientation and firm performance 21 3.2.2 Learning orientation and knowledge-based dynamic capabilities 23 3.2.3 Learning orientation and IT support for KM 25 3.2.4 IT infrastructure capability and firm performance 27 3.2.5 IT infrastructure capability and knowledge-based dynamic capabilities 29 3.2.6 IT infrastructure capability and IT support for KM 31 3.2.7 IT support for KM and knowledge-based dynamic capabilities 32 3.2.8 Knowledge-based dynamic capabilities and firm performance 34 4. Methodology 36 4.1 Research design 36 4.2 Procedure of questionnaire design 37 4.3 The instrument 38 4.3.1 Learning orientation 38 4.3.2 IT infrastructure capability 38 4.3.3 IT support for KM 40 4.3.4 Knowledge-based dynamic capability 40 4.3.5 Firm performance 41 4.3.6 Control variables 42 4.4 Data analysis methods 44 4.4.1 Descriptive statistics 44 4.4.2 Stability test 44 4.4.3 Instrument quality analysis 44 4.4.4 Hypothesis testing 44 5. Data analysis 46 5.1 Response rate 46 5.2 Descriptive statistics 46 5.3 Stability test 48 5.4 Instrument quality analysis 50 5.4.1 Content validity 50 5.4.2 Convergent validity and unidimensionality 50 5.4.3 Reliability analysis 56 5.4.4 Discriminant validity analysis 57 5.5 Hypothesis tests 59 5.5.1 Direct influence effects 60 5.5.2 Indirect influence effects 62 6. Conclusion 66 6.1 Summary and discussion 66 6.2 Research contribution 68 6.3 Implication 69 6.4 Limitations and future research 70 Reference 72 Appendix: Questionnaire 79

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