摘要
为解决铁路旅客进站查验效率评价的准确性和科学性等问题,针对区域一体化背景下铁路进站客流量大、班次密集等公交化运营的特点,以长三角地区核心城市车站为例,对旅客进站查验效率进行评价研究。通过构建融合变异系数与主成分分析法的指标筛选模型,建立旅客进站查验效率评价指标体系;引入DEA-Malmquist效率评价模型,对20个不同等级车站的进站查验效率进行评价,并基于时间序列,分析不同站点的进站查验效率的变化趋势;利用Tobit有限值回归模型,对旅客进站查验效率的影响因素进行定量分析。结果表明,DEA-Malmquist-Tobit模型综合了各模型的优点,能够更全面地评估铁路客运车站的效率变化和影响因素。研究结论对于铁路运输部门提升车站查验效率、优化客运组织具有重要参考价值。
In order to address the accuracy and scientificity issues in evaluating the efficiency of railway passengers’entrance checks,in response to the characteristics of public transportation operation such as large passenger flow and intensive train schedules under the background of regional integration,this study focused on evaluating the efficiency of passengers’entrance checks at stations of core cities in the Yangtze River Delta region.Firstly,an index filter model,integrating the coefficient of variation and principal component analysis,was constructed to establish an evaluation index system for passengers’entrance check efficiency.Secondly,the DEA-Malmquist efficiency evaluation model was applied to evaluate the entrance check efficiency of 20 stations of different grades,and the trends in entrance check efficiency across different stations were analyzed with time series data.Finally,the Tobit finite regression model was used to quantitatively analyze the factors influencing passengers’entrance check efficiency.The results demonstrate that the DEA-Malmquist-Tobit model,integrating the advantages of different models,enables a more comprehensive evaluation of efficiency changes and influencing factors in railway passenger stations.Research conclusions provide valuable insights for railway transportation departments in improving station check efficiency and optimizing passenger transport organization.
作者
姚佼
廖亦杭
张海东
何家平
王祯琦
YAO Jiao;LIAO Yihang;ZHANG Haidong;HE Jiaping;WANG Zhenqi(Business School,University of Shanghai for Science and Technology,Shanghai 200093,China;Smart Urban Mobility Institute,University of Shanghai for Science and Technology,Shanghai 200093,China;Safety Evaluation Institute,Safety Technology Center of National Railway Administration,Beijing 100160,China)
出处
《铁道运输与经济》
北大核心
2025年第1期156-164,190,共10页
Railway Transport and Economy
基金
上海市人民政府决策咨询研究项目(2023-JD-J08)。
