Volume 40 Issue 1
Feb.  2022
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KONG Ning, WENG Jiancheng, SHI Qingshuai, LIU Zhe. A Method for Evaluating Transfer Efficiency Between Bus and Subway Based on Data Envelopment Analysis[J]. Journal of Transport Information and Safety, 2022, 40(1): 89-96. doi: 10.3963/j.jssn.1674-4861.2022.01.011
Citation: KONG Ning, WENG Jiancheng, SHI Qingshuai, LIU Zhe. A Method for Evaluating Transfer Efficiency Between Bus and Subway Based on Data Envelopment Analysis[J]. Journal of Transport Information and Safety, 2022, 40(1): 89-96. doi: 10.3963/j.jssn.1674-4861.2022.01.011

A Method for Evaluating Transfer Efficiency Between Bus and Subway Based on Data Envelopment Analysis

doi: 10.3963/j.jssn.1674-4861.2022.01.011
  • Received Date: 2020-12-28
    Available Online: 2022-03-31
  • EEfficient transfer between bus and subway can enhance the integration of public transportation and the coverage of rail transit. To quantitatively evaluate the transfer efficiency between bus and subway, a set ofinitial evaluation indices are listed with a comprehensive consideration of the supply and demand side. The core indices are then selected by exploring the correlation between the evaluation indices through structural equation modeling and an evaluation index system for transfer efficiency of public transit in a multi-modal transportation network is established covering five aspects of transit routes: design, operation, connectivity, passenger flow, and network accessibility. Given the multi-input and multi-output feature of the evaluation system, data envelopment analysis is introduced to develop a quantitative evaluation model for quantifying the connectivity of public transit and to identify the indicators that hinder efficiency of transit transfer. The evaluation of connectionefficiency of public transit is carried out in three residential communities in Beijing, namely Huilongguan, Tiantongyuan, and Shangdi. Study results show that the efficiency of transit transfer can be quantified based on the proposed evaluation model at various time intervals, which is consistent with observed data. The bus routes with a lower connectivity can be improved by identifying related reasons and referring those routes with good indices

     

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