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Passengers' response to transit fare change: an ex post appraisal using smart card data

机译：乘客对过境票价变化的反应：使用智能卡数据进行事后评估

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摘要

Fare change is an effective tool for public transit demand management. An automatic fare collection system not only allows the implementation of complex fare policies, but also provides abundant data for impact analysis of fare change. This study proposes an assessment approach for analyzing the influence when substituting a flat-fare policy with a distance-based fare policy, using smart card data. The method can be used to analyze the impact of fare change on demand, riding distances, as well as price elasticity of demand at different time and distance intervals. Taking the fare change of Beijing Metro implemented in 2014 as a case study, we analyze the change of network demand at various levels, riding distances, and demand elasticity of different distances on weekdays and weekends, using the method established and the smart card data a week before and after the fare change. The policy implication of the fare change was also addressed. The results suggest that the fare change had a significant impact on overall demand, but not so much on riding distances. The greatest sensitivity to fare change is shown by weekend passengers, followed by passengers in the evening weekday peak time, while the morning weekday peak time passengers show little sensitivity. A great variety of passengers' responses to fare change exists at station level because stations serve different types of land usage or generate trips with distinct purposes at different times. Rising fares can greatly increase revenue, and can shift trips to cycling and walking to a certain extent, but not so much as to mitigate overcrowding at morning peak times. The results are compared with those of the ex ante evaluation that used a stated preference survey, and the comparison illustrates that the price elasticity of demand extracted from the stated preference survey significantly exaggerates passengers' responses to fare increase.
机译：票价变更是公交需求管理的有效工具。自动票价收集系统不仅可以执行复杂的票价政策，而且还可以提供丰富的数据来分析票价变化的影响。这项研究提出了一种评估方法，用于分析使用智能卡数据以统一票价策略取代基于距离的票价策略时的影响。该方法可用于分析票价变化对需求，乘车距离以及不同时间和距离间隔的需求价格弹性的影响。以2014年实施的北京地铁票价变化为例，利用建立的方法和智能卡数据，分析了平日和周末各个层次的网络需求变化，乘车距离以及不同距离的需求弹性。票价更改前后的一周。还讨论了票价变动的政策含义。结果表明，票价变动对总体需求有重大影响，但对乘车距离影响不大。周末乘客对票价变化的敏感性最高，其次是工作日晚上的高峰时间，而工作日早晨的高峰时间则几乎没有敏感性。由于车站服务于不同类型的土地使用或在不同时间产生具有不同目的的行程，因此车站级别上存在多种乘客对票价变化的反应。票价上涨可以大大增加收入，并且可以在一定程度上改变骑行和步行的方式，但并不能减轻早上高峰时段的人满为患。将结果与使用陈述式偏好调查的事前评估的结果进行比较，比较结果表明，从陈述式偏好调查中提取的需求价格弹性极大地夸大了乘客对票价上涨的反应。

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  • 来源
    《Transportation》 |2018年第5期|1559-1578|共20页
  • 作者

    Wang Zi-jia; Chen Feng; Wang Bo; Huang Jian-ling;

  • 作者单位

    Beijing Jiaotong Univ, Sch Civil Engn, Beijing 100044, Peoples R China;

    Beijing Jiaotong Univ, Sch Civil Engn, Beijing 100044, Peoples R China;

    Beijing Transportat Informat Ctr, Beijing 100161, Peoples R China;

    Beijing Transportat Informat Ctr, Beijing 100161, Peoples R China;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Smart card data; Fare change; Demand; Trip distance; Demand elasticity;

    机译：智能卡数据;票价变更;需求;旅行距离;需求弹性;

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