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系統識別號 U0026-2507201613584500
論文名稱(中文) 建構一電動車導入投資計畫評估之多準則決策支援系統
論文名稱(英文) A Multi-criteria Decision Support System for Electric Vehicle Investment Project Assessment
校院名稱 成功大學
系所名稱(中) 工業與資訊管理學系
系所名稱(英) Department of Industrial and Information Management
學年度 104
學期 2
出版年 105
研究生(中文) 謝書軒
研究生(英文) Shu-Hsuan Hsieh
學號 R36021128
學位類別 碩士
語文別 中文
論文頁數 98頁
口試委員 指導教授-呂執中
口試委員-謝佩璇
口試委員-梁直青
口試委員-彭泉
中文關鍵字 電動車  成本效益分析  多準則決策分析  決策支援系統 
英文關鍵字 electric vehicle  cost-benefit analysis  multi-criteria decision analysis  decision support system 
學科別分類
中文摘要   隨著溫室效應的加劇,全球氣溫屢創新高,嚴重地影響了生態、社會、經濟與健康等方面。而運輸部門為主要的溫室氣體排放者之一,因此各國政府陸續推廣具有零排放、零污染特性的電動車。然而,電動車至今能未普及的原因,包括電池成本居高不下、充電基礎設施普遍不足等,使電動車之投資成本過高,導致欲導入業者裹足不前。再者,導入電動車之投資決策,因其成本結構複雜,經濟可行性難以評估,加上決策涉及其他非經濟構面因素之考量,面對動輒上千萬之投資決策,如無法有效先行評估其成本效益,容易使業者望之卻步。因此,目前實需一個架構良好、彈性且簡單易懂,並能將多項決策準則納入考慮之評估方法。
  本研究發展出一個決策支援系統,系統模式中融合車隊投資決策模型、成本效益分析模型與多準則決策分析模組,使用者先以車隊投資決策模型求得建議的最佳投資規模,並以成本效益分析模型評估方案之經濟可行性,最後運用多準則決策模組,納入環境影響與能源補充便利性兩構面共同考量,以針對電動車與傳統汽車之投資方案進行比較。使用者可從資料庫萃取決策相關資訊,運用參數的調整設定情境,進行模擬與分析。
  藉由實際案例的導入,進行本研究系統的驗證,根據個案參數設定之分析結果,顯示運用此系統後,決策者可獲得利潤最大化之投資規模建議,並能協助個案公司找出整體效益最高之方案,此外,電動車方案之獲利有著顯著的提升。本研究亦藉由實驗設計的執行,了解於參數變動下,電動車經濟優勢程度之變化,根據分析結果,發現消費者對電動車之願付價格、租賃需求成長率與政府補助三項因子皆具有顯著的主效用與交互作用。最後,並據此給予業者與政府在投資與推廣電動車時之建議,提供往後制定決策之依據。
英文摘要 SUMMARY
Air pollution, climate change, and rising fuel expenses are all factors that promote the usage of electric vehicle (EV). Since the investment on an EV project is rather complicated, a well-structured evaluation method for EV investment decision is proposed. This work constructs a decision support system which includes fleet investment decision model and cost-benefit analysis model within a multi-criteria decision analysis module. Using this decision support system, a decision-maker could adopt simulation to do the scenario analysis to justify economic feasibility, include the criteria of non-economic aspects into account and may obtain the optimal investment scale of the project. A real case, which intent to invest a fleet of EV for renting service, had been selected to examine the appropriateness of the proposed system and models. The analysis shows that the EV investment would increase its profitability by 51.73% compared to original setup, through the re-arrangement of the fleet by the system. In addition, this work also used design of experiment (DOE) to examine the factors which might have an impact on economic feasibility in the case study. It is found out that willingness to pay for renting EV, government subsidy, and growth rate of renting demand are key factors that have significant effect. The proposed system is illustrated its usefulness for the practitioners.
論文目次 目錄
摘要 I
英文延伸摘要 II
致謝 VII
目錄 VIII
表目錄 XI
圖目錄 XIII
第一章 緒論 1
1.1 研究背景 1
1.2 研究動機 2
1.3 研究目的 3
1.4 研究限制 4
1.5 研究流程 4
第二章 文獻探討 6
2.1 電動車概論 6
2.1.1 電動車簡介及種類 6
2.1.2 電動車發展歷史 7
2.1.3 台灣電動車產業概況 9
2.2 成本效益分析 15
2.2.1 成本效益分析之發展 15
2.2.2 私人部門與公共部門運用之比較 17
2.2.3 導入電動車之成本結構 18
2.3 多準則決策分析 21
2.3.1 多準則決策分析之概念與發展 21
2.3.2 於替代能源汽車選擇之運用 22
2.3.3 電動車相關決策準則 23
2.4 決策支援系統 26
2.4.1 定義與特質 26
2.4.2 系統架構 27
2.4.3 運用 29
第三章 系統建構 31
3.1 電動車投資決策支援系統 31
3.2 多準則決策分析模組 38
3.3 車隊投資決策模型 44
3.4 成本效益分析模型 46
3.4.1 影響變數選擇 46
3.4.2 建置成本計算 48
3.4.3 營運成本計算 51
3.4.4 經濟效益計算 53
3.4.5 成本效益分析計算 53
第四章 情境模擬 56
4.1 使用者介面與操作說明 56
4.1.1 成本收益參數輸入 56
4.1.2 權重參數輸入 58
4.1.3 車輛性能與能源補充資訊輸入 59
4.2 個案介紹 60
4.3 參數設定 62
4.3.1 車輛與充電設施參數設定 62
4.3.2 需求參數設定 65
4.3.3 成本參數設定 66
4.3.4 收益參數設定 68
4.3.5 權重參數設定 69
4.4 數值計算與結果輸出 71
4.4.1 決策支援系統結果輸出 71
4.4.2 敏感性分析 77
4.5 實驗設計 83
4.5.1 實驗因子與水準之選擇 83
4.5.2 模型適合性檢驗 85
4.5.3 變異數分析 87
4.5.4 主效用分析與交互作用分析 88
4.6 綜合討論 91
第五章 結論與建議 92
5.1 研究結論 92
5.2 後續研究建議 93
參考文獻 94
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