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    政大典藏 > College of Commerce > Department of MIS > Theses >  Item 140.119/118937


    Please use this identifier to cite or link to this item: https://nccur.lib.nccu.edu.tw/handle/140.119/118937


    Title: 從大數據創造價值 : 金融產業的多個案研究
    Generating Value from Big Data: A Multiple Case Study in Financial Industry
    Authors: 蔡佑晟
    Tsai, Yu-Chen
    Contributors: 尚孝純
    Shang, Shari S. C.
    蔡佑晟
    Tsai, Yu-Chen
    Keywords: 大數據
    商業價值
    數據導向決策
    Big data
    Business value
    Data-driven decision-making
    Date: 2018
    Issue Date: 2018-07-27 11:37:40 (UTC+8)
    Abstract: 隨著社群和分析技術的快速發展，大數據已經成為許多產業中的熱門議題。眾多知名跨國公司都從大數據應用中獲得了巨大的價值，如: Google、Walmart、和Amazon等。然而除了這些具有代表性的成功例子之外，在大數據上進行大量的投入並不一定能帶來實質的收益，商業決策者們仍然對大數據科技的回報持懷疑態度。

    本研究對數據導向決策的案例和大數據應用進行了系統化的文獻回顧，並歸納出大數據可能創造的效益，以及一些可能影響大數據創造價值的相關關鍵因素。之後，此研究將與金融公司的高階資訊主管進行深度的訪談與了解。最後，本研究透過對金融產業的跨個案橫向分析，期望能為大數據的應用提供相關的發現與見解。
    With rapid advances in social and analytics technology, Big Data has become a popular subject in many industries. Numerous well-known multinational companies, such as Google, Walmart, and Amazon, reported deriving enormous value from Big Data applications. However, except for these emblematic examples, there is no promise that large investments in Big Data can result in material benefits. Business decision-makers remain doubtful as to returns from Big Data technologies.

    Performing a systematic literature review of data-driven decision-making cases and Big Data applications, this study identified several possible benefits that may be generated from Big Data, and identified several Big Data-related key factors that may affect value creation. Then, this study conducted in-depth interviews with senior IT managers from selected financial companies. Finally, by a cross-sectional analysis of financial industry, this study intends to provide insights into Big Data implementation.
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    Description: 碩士
    國立政治大學
    資訊管理學系
    105356002
    Source URI: http://thesis.lib.nccu.edu.tw/record/#G0105356002
    Data Type: thesis
    DOI: 10.6814/THE.NCCU.MIS.006.2018.A05
    Appears in Collections:[Department of MIS] Theses

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