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A platform for research: civil engineering, architecture and urbanism
Evaluation of Transfer Efficiency between Bus and Subway based on Data Envelopment Analysis using Smart Card Data
Abstract The government of Seoul has been operating the automatic fare collection system based on the smart card since 2004. The smart card data in Seoul consist of 15 million instances of individual transit information per day, providing 99% of transit users’ trips. This study provides information about the efficiency of transfer stations in Seoul. The purpose of this study was to estimate the relative efficiency of the transfer stations between bus and subway using smart card data and suggest the improvement strategies for achieving the optimal efficiency. The transfer efficiency was estimated by using the Data Envelopment Analysis (DEA) model, and Tobit regression analysis was conducted to identify the factors that influence transfer efficiency. The DEA model showed that the efficiency scores of 32 major stations were estimated to be 0.557 on average. The transfer efficiency scores of these stations were analyzed to be proportional to the number of transfer trips and the transfer rate of the station. In the external factor analysis, we selected two socioeconomic variables, i.e., population and the number of companies. The external factor analysis indicated that the DEA model produced reasonable results for evaluating transfer efficiency.
Evaluation of Transfer Efficiency between Bus and Subway based on Data Envelopment Analysis using Smart Card Data
Abstract The government of Seoul has been operating the automatic fare collection system based on the smart card since 2004. The smart card data in Seoul consist of 15 million instances of individual transit information per day, providing 99% of transit users’ trips. This study provides information about the efficiency of transfer stations in Seoul. The purpose of this study was to estimate the relative efficiency of the transfer stations between bus and subway using smart card data and suggest the improvement strategies for achieving the optimal efficiency. The transfer efficiency was estimated by using the Data Envelopment Analysis (DEA) model, and Tobit regression analysis was conducted to identify the factors that influence transfer efficiency. The DEA model showed that the efficiency scores of 32 major stations were estimated to be 0.557 on average. The transfer efficiency scores of these stations were analyzed to be proportional to the number of transfer trips and the transfer rate of the station. In the external factor analysis, we selected two socioeconomic variables, i.e., population and the number of companies. The external factor analysis indicated that the DEA model produced reasonable results for evaluating transfer efficiency.
Evaluation of Transfer Efficiency between Bus and Subway based on Data Envelopment Analysis using Smart Card Data
Lee, Eun Hak (author) / Lee, Hoyoung (author) / Kho, Seung-Young (author) / Kim, Dong-Kyu (author)
KSCE Journal of Civil Engineering ; 23 ; 788-799
2018-12-17
12 pages
Article (Journal)
Electronic Resource
English
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