交通部在2020運輸政策白皮書中提及有關智慧運輸政策相關規劃，說明我國未來交通運輸之政策目標為結合雲端運算、資通訊技術、物聯網科技、大數據分析、數位匯流、人工智慧等新興科技之數位轉型，冀望改善交通意外事故與壅塞，而建立智慧交通環境。因此數位轉型成熟度之相關研究遂成為近年來熱門研究課題之一。運輸領域中已出現航空公司數位化能力之研究文獻，然而，軌道運輸相關領域之數位轉型研究尚在起步階段，亦是本研究之研究動機所在。
多數研究使用多評準決策結合績效評估方法來建立評估架構，傳統使用之AHP方法常面臨填答費時、結果一致性不高、備選方案無法排序與無法選取最佳方案等問題，因此本研究結合BWM與Modified VIKOR之研究方法，以臺北捷運、桃園捷運作為實證對象。首先經過數位轉型相關文獻彙整評估準則，提出捷運數位轉型成熟度之評估架構，再由修正式德爾菲法確立各項準則指標，最終藉由BWM與Modified VIKOR方法計算出指標權重以及營運機構數位轉型績效表現。
研究結果顯示「數位營運資訊平臺」為最重要構面，以反映捷運營運機構在發展數位轉型時，應優先以基礎設施建置為主，權重前三高之評估準則為「發展數位轉型專責單位」、「數位化資源投入與整合」、「數位資通訊基礎設施」。總體而言，臺北捷運之數位轉型成熟度領先於桃園捷運，兩機構都應當針對「數位企業組織創新及整合能力」、「員工數位化教育及培訓」、「發展數位轉型專責單位」、「數位化資源投入與整合」、「旅客旅運服務資訊平臺」、「營運緊急應變與復原能力」、「數位平臺的資料來源與輸出」、「數據資料安全擷取與風險評估管理」、「數據品質監督」、「行中車站/列車資通訊多元顧客服務」進行改善。本研究成果可供我國各捷運營運機構作為改善提升都市大眾捷運營運機構數位轉型成熟度之參考，以提昇服務水準及管理效率。

Ministry of Transportation and Communications (MOTC) published 2020 Transportation Policy White Paper which policy goals relating to smart transportation will focus on integrating emerging digital technologies such as cloud computing, information and communication technologies, the Internet of Things, big data analytics, digital convergence, and artificial intelligence for digital transformation in order to reduce traffic accidents and congestion and to establish an intelligent transportation environment.
Research tasks on digital transformation maturity have been conducted in areas such as national defense, industry, and small and medium enterprises. In the transportation area,   the digital capabilities of airlines have been studied by many researchers. However, there are few researchers to study digital transformation maturity in the railway transportation area. That is the reason why this study is motivated.
Previous studies used multi-criteria decision-making combined with performance evaluation methods to establish assessment frameworks. The traditional AHP method has critical issues such as time-consuming, inconsistent results, inability to rank alternatives, and difficulty in selecting the best alternative. Therefore, this study combines the Best Worst Method (BWM) and Modified VIKOR methods. Two urban mass rapid transit corporations ,Taipei Metro and Taoyuan Metro, are chosen as empirical case studies. Firstly, based on criteria derived from literature reviews concerned digital transformation, an evaluation framework of digital transformation maturity for urban mass rapid transit corporations is proposed. Then, the criteria are statistically verified by experts and scholars from the railway sector with the Modified Delphi method. Finally, BWM and Modified VIKOR are used to calculate the weights of the indicators and the digital transformation maturity performance of Taipei Metro and Taoyuan Metro.
The empirical case studies show that the "Digital Operation Information Platform" is the most critical dimension which effectively reflects that the priority of development of digital transformation for Urban Mass Rapid Transit Corporations is initial infrastructure deployments. The top three highest-weighted criteria are "Establishment of Dedicated Digital Transformation Units," "Investment and Integration of Digital Resources," and "Digital Information and Communication Infrastructure." In summary, Taipei Metro's digital transformation maturity is better than Taoyuan Metro. Both of corporations should raise the priority to improve "Digital Enterprise Organization Innovation and Integration Capability," "Employee Digital Education and Training," "Establishment of Dedicated Digital Transformation Units," "Investment and Integration of Digital Resources," "Passenger Travel Information Service Platform," "Operational Emergency Response and Recovery Capability," "Data Sources and Output of Digital Platforms," "Data Security Acquisition and Risk Assessment Management," "Data Quality Monitoring," and "Diverse Customer Information and Communication Services within Stations/Trains". The research results of this study may serve as references for other urban mass rapid transit corporations in Taiwan to enhance the digital transformation maturity. It is also anticipated that urban mass rapid transit service quality and management efficiency will be improved by introducing digital transformation maturity.

目錄
目錄	i
圖目錄	iii
表目錄	iv
第一章 緒論	1
1.1研究背景與研究動機	1
1.2研究目的	3
1.3研究範圍	3
1.4研究流程	4
第二章 文獻回顧	5
2.1數位轉型相關概念與研究	5
2.1.1數位經濟介紹	5
2.1.2數位轉型三階段發展	7
2.1.3數位轉型之定義	9
2.2軌道事業數位轉型相關案例	11
2.2.1德國鐵路股份公司	11
2.2.2日本JR公司	13
2.3大眾捷運營運機構數位轉型成熟度評估架構	15
2.4德爾菲法相關研究	28
2.4.1德爾菲法起源	28
2.4.2修正式德爾菲法相關研究	29
2.5多評準決策-最佳最差法	30
2.6績效評估方法-修正式折衷排序法	35
2.7文獻回顧小結	38
第三章 研究方法	40
3.1研究架構	40
3.2修正式德爾菲法分析程序	41
3.3最佳最差法分析程序	43
3.4修正式折衷排序法分析程序	48
第四章 實證分析	49
4.1修正式德爾菲法指標篩選實證分析	49
4.1.1第一階段修正式德爾菲法分析	52
4.1.2第二階段修正式德爾菲法分析	53
4.2最佳最差法與修正式折衷排序法實證分析	59
4.2.1最佳最差法分析	60
4.2.2修正式折衷排序法分析	65
4.3實證分析小結	72
4.3.1專家群觀點之異同	72
4.3.2管理意涵	79
第五章 結論與建議	82
5.1結論	82
5.2建議	84
參考資料	85
附錄	97
附錄一 第一次修正式德爾菲法問卷	97
附錄二 第二次修正式德爾菲法問卷	103
附錄三 最佳-最差法（BWM）問卷	113
附錄四 都市大眾捷運營運機構數位轉型成熟度績效評估問卷	124
附錄五 專家學者填答之BO向量值	125
附錄六 專家學者填答之OW向量值	127
圖目錄
圖1.1研究流程圖	4
圖2.1初擬大眾捷運營運機構數位轉型成熟度評估模型	27
圖2.2 BWM準則比較示意圖	31
圖2.3 VIKOR理想解與妥協解示意圖	36
圖3.1研究流程圖	40
圖3.2 BWM與AHP成對比較次數對比圖	43
圖4.1大眾捷運營運機構數位轉型成熟度評估模型	59
圖4.2都市大眾捷運營運機構數位轉型成熟度評估準則整體權重	64
圖4.3臺北捷運數位轉型成熟度評估準則與理想值之差距	69
圖4.4桃園捷運數位轉型成熟度評估準則與理想值之差距	70
表目錄
表2.1過往數位經濟相關文獻定義	6
表2.2過往數位轉型相關文獻定義	10
表2.3 Firmanyah et al.（2017）都市的數位化運輸成熟度	16
表2.4 Jabłoński & Jabłoński（2019）鐵路公司業務模式數位化評估	17
表2.5 Berger et al.（2020）運輸數位能力評估模型	18
表2.6 Büyüközkan et al.（2021）低成本航空公司數位能力評估模型	19
表2.7 Asadamraji et al（2021）交通運輸數位化成熟度準則	20
表2.8 Li et al.（2022）地鐵車站之智慧化服務水準評估模型	21
表2.9 Xue et al.（2022）智慧城市軌道交通永續發展評估指標	22
表2.10 Varol et al.（2022）運輸事業數位轉型成熟度評估模型	23
表2.11都市大眾捷運數位轉型成熟度評比指標彙整表	24
表2.12過往數位轉型成熟度相關研究文獻整理	26
表2.13多評準決策法（MCDM）比較表	34
表2.14績效評估法比較表	37
表3.1 BWM之一致性指數	47
表4.1修正式德爾菲問卷之專家學者背景	49
表4.2文獻蒐集後大眾捷運營運機構數位轉型成熟度指標（1/2）	50
表4.3文獻蒐集後大眾捷運營運機構數位轉型成熟度指標（2/2）	51
表4.4修正式德爾菲法後大眾捷運營運機構數位轉型成熟度指標（1/4）	53
表4.5修正式德爾菲法後大眾捷運營運機構數位轉型成熟度指標（2/4）	54
表4.6修正式德爾菲法後大眾捷運營運機構數位轉型成熟度指標（3/4）	55
表4.7修正式德爾菲法後大眾捷運營運機構數位轉型成熟度指標（4/4）	56
表4.8修正式德爾菲法篩選後大眾捷運營運機構數位轉型成熟度指標	57
表4.9 BWM專家學者問卷之統計資料	60
表4.10專家學者填答之四大構面BO向量	62
表4.11專家學者填答之四大構面OW向量	62
表4.12大眾捷運營運機構數位轉型成熟度評估構面與準則之整合權重	63
表4.13本研究之備選大眾捷運營運機構相關說明	65
表4.14專家學者績效評估矩陣	66
表4.15專家學者正規化後的績效矩陣	67
表4.16專家學者加權後正規化績效矩陣	68
表4.17全體專家學者方案整體效益（Sj）以及最大個別遺憾（Rj）	71
表4.18專家學者之方案綜合效益（Qj）與排序	71
表4.19產業專家學者之準則改善順序	73
表4.20官方專家學者之準則改善順序	74
表4.21學術專家學者之準則改善順序	75
表4.22全體專家學者之準則改善順序	76
表4.23不同群體專家學者之準則優先改善順序比較	78
表4.24臺北捷運數位轉型成熟度評估準則長短期可行性	80
表4.25桃園捷運數位轉型成熟度評估準則長短期可行性	81

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