運用德爾菲法探討巨量資料分析成功之影響因素－以全民健保資料庫為例;Using Modified Delphi Method to Investigate Successful Factors of Big Data Analysis: An Example of the National Health Insurance Database in Taiwan

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Title:	運用德爾菲法探討巨量資料分析成功之影響因素－以全民健保資料庫為例;Using Modified Delphi Method to Investigate Successful Factors of Big Data Analysis: An Example of the National Health Insurance Database in Taiwan
Authors:	陳盈融;CHEN, YING-RONG
Contributors:	資訊管理學系碩士在職專班
Keywords:	德爾菲法研究;全民健保資料庫;巨量資料分析;成功因素;Modified Delphi Method;National Health Insurance Database;Big Data Analysis;Success Factors
Date:	2017
Issue Date:	2019-07-17
Publisher:	資訊管理學系碩士在職專班
Abstract:	巨量資料分析的相關研究與應用，近幾年在學界和業界已愈顯重要。台灣全民健保資料庫(National Health Insurance Research Database, NHIRD)的建置，無疑為醫學研究注入新元素。如何利用巨量資料加強統計支援決策功能及增進學術研究能量，提供政府決策制定與評估之依據已成為近年熱門研究議題。本研究以巨量資料分析專家作為研究對象，針對NHIRD此議題的成功影響因素進行探討，協助各界瞭解進行巨量資料分析研究時應注重之成功影響因素。本研究結合巨量資料分析、資訊系統和商業智慧成功的影響因素，發展出研究模式，以巨量資料特性6V及科技組織環境理論(TOE Framework)三構面等共四大構面，共計14個評估層面及55個問項。本研究採用修正式德爾菲法(modified Delphi)作為本研究的研究方法，遴選國內熟悉巨量資料分析領域的學術界和醫療界、產業專家及政府部門等專家學者參與本研究的修正式德爾菲法進行。本研究共進行二回合問卷，第一回合有30名專家，共計回收23份問卷；第二回合以第一回合回收的23位專家作為問卷發放的對象，此回合最後則回收21份，回覆率則為91%。經過一致性和穩定性檢定後，研究結果顯示出前九大巨量資料分析成功影響因素依序為：定義問題、具價值的資料、資料來源端與組織間的信任、資料解釋的偏見、具備對資料庫熟悉度、資料授權和軟體工具、客戶(個人)隱私、維護資料品質的能力、高度熟練技術的人力資源。而測量的基本問題和結構資料中的有效性與可靠性、安全資料共享、培訓相關職能的人員、擁有必要的工具、及培訓與支持等因素則併列第十名。 The applications of big data analysis have become one of most important topics in academia and industry. However, successful factors of big data analysis effectively support decision making is still unknown. Additionally, the establishment of the National Health Insurance Research Database (NHIRD) undoubtedly injects new elements into the medical research. Therefore, this study aims to investigate the successful factors of big data analysis with an example of the NHIRD.This study develops the research model based on the 6V characteristics of big data and technology-organization-environment framework. Fourteen assessment levels and 55 factors were selected to examine. The modified Delphi method was used in this study. Scholars, industry and government experts in the BDA field were recruited to participate in the study.Twenty-three respondents were received from 30 experts in the first round. Twenty-three experts who responded in the first round were contacted in the second round and finally 21 respondents returned. The response rate was 91%. After the consistency and stability tests, the analytical results indicated that the critical success factors include: clear problem definition, valuable information, trust between the source and the organization, appropriate data interpretation, sufficient database familiarity, data authorization and software tools, customer (personal) privacy, the ability to maintain data quality, highly skilled human resources, measurements of variables, validity and reliability, data security, staff training and resource sufficiency.
Appears in Collections:	[資訊管理系研究所] 學位論文

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