, Volume 45, Issue 5, pp 1559–1578 | Cite as

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

  • Zi-jia Wang
  • Feng ChenEmail author
  • Bo Wang
  • Jian-ling Huang


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.


Smart card data Fare change Demand Trip distance Demand elasticity 



This work was supported by the National Natural Science Foundation of China (Grant No.: 51408029).


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Copyright information

© Springer Science+Business Media New York 2017

Authors and Affiliations

  • Zi-jia Wang
    • 1
  • Feng Chen
    • 1
    • 2
    Email author
  • Bo Wang
    • 3
  • Jian-ling Huang
    • 3
  1. 1.School of Civil EngineeringBeijing Jiaotong UniversityBeijingChina
  2. 2.Beijing Engineering and Technology Research Center of Rail Transit Line Safety and Disaster PreventionBeijingChina
  3. 3.Beijing Transportation Information CenterBeijingChina

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