Applying Data Envelopment Analysis (DEA) Models to Investigation of the Efficiencies of Accident-Prone Locations and Subsidy Allocation

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Project title

Code/計畫編號

NSC102-2221-E019-049

Translated Name/計畫中文名

應用資料包絡分析法探討國內易肇事路段改善計畫之執行效率與經費配置原則

Project Coordinator/計畫主持人

Chi-Hung Wu

Department/Unit

Department of Transportation Science

Website

https://www.grb.gov.tw/search/planDetail?id=3109619

Year

2013

Start date/計畫起

01-08-2013

Expected Completion/計畫迄

31-07-2014

Bugetid/研究經費

378千元

ResearchField/研究領域

交通運輸

"至民國101年底止，國內已完成29期易肇事路段改善計畫。目前易肇事路段改善作業程序已建立標準作業程序，主要依循民國92年交通部運輸研究所出版的「易肇事地點改善作業技術參考手冊」。但是未曾針對易肇事路段改善計畫的執行成效進行評估。以第24期易肇事路段改善計畫為例，全國共有143處改善地點，分別由台北市、高雄市及 21的縣市實際執行改善作業，平均每處改善經費差異相當大，最高者為臺中市，單一處改善經費高達273萬元，最低者為台南縣，僅約7,500元。由於各改善地點的經費差異相當大，因此了解各改善地點之改善效能與影響改善效能的因素實具有其重要性。此外，建立一考量各縣市執行改善計畫效能的經費補助配置模式，應可提升計畫執行的成效。本研究計劃以第24期易肇事路段改善計畫143處改善地點為研究範圍，彙整此143處改善地點的事故資料，利用考量經費補助配置資料包絡分析法(ABDEA)進行效率分析。根據模式分析結果效率與目標產出的訂定，本研究將從改善地點本身的特性、所在縣市之特性、計畫執行單位與經費來源等方面，探討改善效能的影響因素，並訂定經費補助配置的原則，以建立一考量執行效能的經費補助配置模式。""Up to 2012, there have been 29 projects of improving accident-prone locations carried out in Taiwan Area. These successive projects followed a three-phase procedure established in a technical manual published by the Institute of Transportation, Ministry of Transportation and Communications in 2003. In the phase of performance evaluation, this manual provides an operational procedure of effectiveness evaluation. However, this evaluation process has not been practically complied with. To illustrate the necessity of effectiveness evaluation and to propose a subsidy allocation method, the 143 accident-prone locations included in the 24th project are analyzed. The project costs of these 143 locations varied greatly from city to city. On average, Taichung spent 2.73 million NT dollars at one accident-prone location, while Tainan spent only 7.5 thousand NT dollars at each location. With the large variation in project expenses, it is essential to compare improvement effectiveness of each location. Therefore, the investigation of influence factors on improvement effectiveness is crucial. Subsidy allocation is also an important issue to each cities/counties. Hence, a subsidy allocation model is developed to take improvement effectiveness of each accident-prone location into account. This study proposes to apply a deterministic non-parametric model, data envelopment analysis (DEA) to measure project effectiveness. An allocation-based data envelopment analysis (ABDEA) model will be chosen to calculate effectiveness of each location and to allocate subsidies. The factors influencing the effectiveness of each accident-prone location will be investigated and a target output will be determined to allocate subsidy baselines for the next project."

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Applying Data Envelopment Analysis (DEA) Models to Investigation of the Efficiencies of Accident-Prone Locations and Subsidy Allocation

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