吳文方臺灣大學：工業工程學研究所陳孟良Chen, Meng-LiangMeng-LiangChen2007-11-262018-06-292007-11-262018-06-292007http://ntur.lib.ntu.edu.tw//handle/246246/51233因為大客車的搭乘人數比一般汽車多，所以發生車禍時，常常會造成重大傷亡，使得社會成本增加，因此本研究希望為客運公司建立一個風險評估之模式，藉以減少大客車的車禍發生率。本論文透過車禍有關的文獻與車禍新聞事件，選取出25個車禍風險因素，並將其分為5大類，分別是個人生理因素、個人行為因素、個人違規行為因素、組織因素及環境因素，依據上述建立出風險層級結構，再製作問卷交由專家填答，且根據問卷填答所得出的資料，利用模糊層級分析法，求取出各項風險因素的權重，並加以排序。結果顯示，在個人生理因素中，權重排序最高者為高血壓；在個人行為因素中，權重排序最高者為打瞌睡；在個人違規行為因素中，權重排序最高者為飲酒；在組織因素中，權重排序最高者為超時工作；在環境因素中，權重排序最高者為道路型態為交叉路及彎曲路。此外，依據本論文所建立的風險層級結構，其層級串聯之權重結果，可做為客運公司風險管理的工具。A bus carries more passengers than then the average vehicles. Therefore an accident involving often leads to heavy casualties, raising social cost. This research aims to build a risk evaluation model for bus corporations, hoping to reduce bus traffic accidents. Twenty-five risk factors of bus traffic accidents are chosen from literature on traffic accidents as well as from news reporting. They are further divided into five categories - personal physiological factors, personal behavioral factors, personal traffic regulation violation factors, organizational factors and environmental factors. Based on the above-mentioned factors, a risk hierarchy model of bus is established and questionnaires are then produced and distributed to transportation experts in order to attain data. Finally, Fuzzy Analytic Hierarchy Process is applied to obtain the weight value of and ranking for each risk factor. The results show that high blood pressure ranks highest in terms of the personal physiological factors. While drivers’ dozing off ranks highest in terms of the personal behavioral factors. Drinking ranks highest in terms of personal traffic regulation violation factors. Working overtime ranks highest in terms of the organizational factors. Finally, intersections and winding roads rank highest in terms of the environmental factors. In conclusion, the results of these risk factors correlated can be provided as a risk management tool for bus companies.誌謝……………………………………………………………………………………...Ⅱ 中文摘要…………………………………………………..……………..……………..Ⅲ 英文摘要…………………………………………………..……………..……………..Ⅳ 目錄……………………………………………………………………………..……….V 表目錄……………………………………………………………………………….…ⅥI 圖目錄……………………………………………………………..………………......Ⅷ 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 討論範圍與限制………………………………………………………………..3 1.5 本文內容………………………………………………………………………..4 第二章 文獻回顧……………………………………………………………………….5 2.1 風險管理文獻回顧………………………………………………………….….5 2.2 客運車禍風險因素之文獻回顧……………………………………………....11 2.3 層級分析法…………………………………………………………………....17 2.4 模糊理論……………………………………………………………...……….21 2.5 模糊層級分析法……………………………………………...………….……24 第三章 研究方法…………………………………………………………………….26 3.1 研究流程………………………………………………………………………26 3.2 研究架構………………………………………………………………………26 3.3　研究分析方法…………………………………………………………………32 第四章　研究結果…………………………………………………………………….43 4.1 客運行車安全因素之權重結果………………………………………………43 4.2　個人生理因素之權重結果……………………………………………………44 4.3　個人行為因素之權重結果……………………………………………………45 4.4　個人違規行為因素之權重結果………………………………………………47 4.5　組織因素之權重結果…………………………………………………………48 4.6　環境因素之權重結果…………………………………………………………49 4.7 風險因素串聯之權重結果………………………..…………………………..50 第五章　結論與建議………………………………………………………………….55 5.1 結論……………………………………………………………………………55 5.2　建議……………………………………………………………………………57 5.3 未來研究方向……………………………………..…………………………..58 參考文獻……………………………………………………………………………….59 附錄…………………………………………………………………………………….65en-US客運公司風險管理車禍風險因素風險評估模式模糊層級分析法bus companyrisk managementtraffic accident risk factorsrisk evaluation modelFuzzy Analytic Hierarchy Process[SDGs]SDG3thesis