基於專家共識與多準則決策法構建大數據治理成熟度模型

Abstract

在現代全球經濟中，數據是驅動業務效率、提升公共服務和提供消費者利益的重要元素。然而，大數據的管理因其規模、多樣性、高速度和真實性而變得非常複雜，帶來了顯著的挑戰。大數據治理已成為一個關鍵議題，許多組織在建立有效的框架以管理和利用數據方面面臨困難。儘管大數據治理的重要性顯而易見，過去研究針對大數據治理及其成熟度模型的關注卻有限。 本研究旨在填補這一空白，通過開發一個綜合的大數據治理成熟度模型來解決這一問題。該模型整合了現有學術及業界之模型，並利用修正式德菲法（Modified Delphi Method）以獲得專家共識，後使用模糊層級分析法（FAHP, Fuzzy Analytic Hierarchy Process）為模型中不同的構面及因素分配相對權重。通過應用這些權重，該模型能夠準確反映每個構面和因素的重要性，使組織能夠精確地識別需要改進的領域。此模型使組織能夠評估其當前的大數據治理成熟度水平，並識別改進的領域，確保更好的戰略規劃和資源分配從而增強其大數據治理能力。 本研究的主要貢獻包括：開發了一個大數據治理成熟度模型，通過專家共識進行實證驗證，以及應用模糊層級分析法對構面及因素進行加權評估。這一模型讓組織能對其大數據治理能力進行精確評估，從而制定針對性的改進計畫及更有效的治理策略，以迎接大數據時代的挑戰。

In the modern global economy, data is a foundational element driving business efficiency, enhancing public services, and delivering consumer benefits. However, the complexities of managing big data, characterized by its volume, variety, velocity, and veracity, present significant challenges. Big Data governance has emerged as a critical issue, with organizations struggling to establish effective frameworks to manage and leverage data. Despite the importance of big data governance, existing research has paid limited attention to big data governance and its maturity models. This study addresses this gap by developing a comprehensive Big Data Governance Maturity Model. This model integrates insights from various existing models and utilizes the Modified Delphi Method to gather expert consensus and the Fuzzy Analytic Hierarchy Process (FAHP) to assign relative weights to different dimensions and factors. By applying weights, the model can accurately reflect the importance of each dimension and factor, allowing organizations to pinpoint specific areas needing improvement. This weighted approach ensures that organizations can prioritize resources effectively, enhancing their big data governance capabilities. The proposed model allows organizations to assess their current level of big data governance maturity and identify areas for improvement, helping them navigate the complexities of big data, ensuring better strategic planning and resource allocation. Key contributions of this research include the development of a Big Data Governance Maturity Model, the introduction of specific dimensions and detailed factors to enhance model practicality, empirical validation through expert consensus, and the application of FAHP for a weighted assessment approach. This innovative model offers a precise evaluation of organizational capabilities, facilitating targeted improvement recommendations and more effective governance strategies in the era of big data.