Understanding peak avoidance commuting by subway: an empirical study in Beijing

Yacan Wang, Dick Ettema, Huiyu Zhou*, Xiangrui Sun

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review


Congestion is a major problem for peak-hour commuters in the Beijing subway system, as it leads to long queuing times and overcrowded vehicles. This paper explores to what extent peak travel can be reduced by providing incentives for peak avoidance. In a stated preference study, travellers’ responses to two financial and two non-financial incentives were measured, and factors increasing or limiting the response were identified. Our results suggest that all four incentives can be reasonably effective tools and the financial incentives seem to have a slightly stronger effect than the services and credit-for-gifts-based scenarios. Ordered logit models indicate that various factors influence people’s receptiveness of incentives for peak avoidance which relate to the ease of change or presence of alternatives and receptiveness to incentives. Both theoretical and policy implications are concluded that the proposed factors and incentive system can help solving the subway congestion in Beijing.

Original languageEnglish
Pages (from-to)597-613
Number of pages17
JournalInternational Journal of Logistics Research and Applications
Issue number6
Publication statusPublished - 2018


  • Beijing
  • incentives
  • ordered logit model
  • Subway peak-hour avoidance


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