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研究生: 胡郁如
Yu-Ju Hu
論文名稱: 大數據分析能力對組織意會能力與創新能力之影響
The Effect of Big Data Analysis Capability on Sensemaking and Innovation Capability
指導教授: 魏小蘭
Hsiao-Lan Wei
口試委員: 魏小蘭
Hsiao-Lan Wei
黃世禎
Sun-Jen Huang
朱宇倩
Yu-Qian Zhu
學位類別: 碩士
Master
系所名稱: 管理學院 - 資訊管理系
Department of Information Management
論文出版年: 2018
畢業學年度: 106
語文別: 中文
論文頁數: 95
中文關鍵詞: 大數據大數據分析能力吸收能力組織意會能力組織創新能力
外文關鍵詞: Big Data, Big Data Analysis Capability, Absorptive Capability, Organizational Sensemaking, Organizational Innovation Capability
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  • 隨著資訊科技發展與市場環境變動快速,大數據已逐漸受到各產業以及政府的重視,巨量資料有數量多、生成速度快、資料多樣化等特性,將會對企業之組織吸收能力與意會能力有所影響。企業可以透過大數據分析提升學習能力、協同合作能力、獲取更多新知識,並讓組織有更好的市場洞悉力來加速創新,以維持競爭力。但是關於要如何提升大數據分析的效益以提升組織創新力,一直是仍需探討的問題,因大數據分析常需要跨部門團隊協作,本研究選擇了組織吸收能力與組織意會能力來研究其對組織創新能力的影響。
    本研究之研究對象為2016年《天下兩千企業調查排名資料庫》所評選出之台灣六百大製造業、三百大服務業與一百大金融業的資訊部門主管,以郵寄及線上問卷方式進行調查。研究結果顯示:(1) 大數據分析與基礎建設的能力與組織吸收能力及組織意會能力無顯著之影響;大數據分析管理的能力與組織吸收能力及組織意會能力有顯著且正向的影響;大數據分析人員能力對組織吸收能力及組織意會能力有顯著且正向的影響 (2)組織吸收能力與組織意會能力對組織創新能力有顯著且正向的影響。


    With the rapid development of information technology and the rapid changes in the market environment, big data has gradually been valued by various industries and governments. Big Data break into four dimensions: volume, variety, velocity and veracity, and will have a huge impact on absorptive capacity and organizational sensemaking. Enterprises can enhance their learning ability, collaborative collaboration capabilities, and acquire more new knowledge through big data analysis, and allow organizations to have better market insights to create innovation and maintain competitiveness. However, how to improve the effectiveness of big data analysis to enhance organizational innovation has always been a problem that needs to be explored. Because big data analysis often requires cross-departmental teamwork, this study selects organizational absorptive capacity and organizational sensemaking ability to study the impact on organizational innovation capabilities.
    This study is investigates the top600 Taiwanese manufacturers, top300 service industries and top100 financial industry issued by CommonWealth Magazine of Taiwan in 2016. The research results reveal that: (1)BDA infrastructure capabilities have a nonsignificant impact on Absorptive Capability and Organizational Sensemaking. BDA management capability has a significant and positive impact on Absorptive Capability and Organizational Sensemaking. BDA personnel capability has a significant and positive impact on Absorptive Capability and Organizational Sensemaking. (2)Absorptive Capability and Organizational Sensemaking has a significant positive impact on Organizational Innovation.

    第一章 緒論 1 第一節 研究背景 1 第二節 研究動機 2 第三節 研究目的 3 第四節 研究流程 5 第五節 論文架構 6 第二章 文獻探討 7 第一節 大數據 7 2.1大數據分析 8 2.1.1 大數據分析能力 9 2.1.2大數據分析基礎建設能力 10 2.1.3 大數據分析管理能力 11 2.1.4大數據分析人員能力 12 第二節 組織吸收能力 13 2.2.1吸收能力 13 2.3.2 吸收能力相關研究 14 第三節 組織意會能力 15 2.3.1意會 15 2.3.2 組織意會能力 16 2.3.3 組織意會能力相關研究 17 第四節 組織創新能力 18 2.4.1組織創新能力 18 2.4.3 組織創新能力相關研究 19 第三章 研究模型 20 第一節 研究架構 20 第二節 研究假說 21 3.2.1大數據分析基礎建設能力與組織吸收能力 21 3.2.2大數據分析基礎建設能力與組織意會能力 21 3.2.3大數據分析管理能力與組織吸收能力 22 3.2.4大數據分析管理能力與組織意會能力 22 3.2.5大數據分析人員能力與組織吸收能力 23 3.2.6大數據分析人員能力與組織意會能力 24 3.2.7組織吸收能力與創新能力 25 3.2.8組織意會能力與創新能力 26 第四章 研究方法 27 第一節 研究設計 27 第二節 問項設計方法 27 4.2.1 大數據分析基礎建設能力 28 4.2.2 大數據分析管理能力 29 4.2.3 大數據分析人員能力 31 4.2.4 組織吸收能力 33 4.2.5 組織意會能力 34 4.2.6 組織創新能力 35 第三節 資料分析方法 35 4.3.1 敘述性統計分析 36 4.3.2 驗證性因素分析 36 4.3.3.假說檢定 37 第五章 資料分析 39 第一節 樣本敘述性統計分析 39 5.1.1 樣本回收 39 5.1.2 樣本特徵 39 第二節 樣本無回應偏差(Non-response bias) 46 第三節 驗證性因素分析 46 5.3.1 信度 46 5.3.2 效度 48 第四節 研究假說之檢定 54 第五節 檢定分析結果說明 57 第六章 研究結論與建議 58 第一節 研究結論與發現 58 第二節 研究貢獻 61 第三節 研究限制 62 第四節 未來研究方向與建議 64 參考文獻 65 附錄1:正式問卷(基本資料-製造業) 74 附錄2:正式問卷(基本資料-服務業) 75 附錄3:正式問卷(基本資料-金融業) 76 附錄4:正式問卷(問卷內容-製造業、服務業、金融業) 77 附錄5:一階因素負荷量(first order loading) 81 附錄6:二階因素負荷量(second order loading) 84

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    《天下兩千企業調查排名資料庫》
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