Understanding the effects of travel demand management on metro commuters’ behavioural loyalty: a hybrid choice modelling approach

Ning Huan (), Stephane Hess () and Enjian Yao ()
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Ning Huan: Beijing Jiaotong University
Stephane Hess: University of Leeds
Enjian Yao: Beijing Jiaotong University

Transportation, 2022, vol. 49, issue 2, No 2, 343-372

Abstract: Abstract As part of efforts to promote sustainable mobility, many cities are currently experiencing the rapid expansion of their metro network. The consequent growth in ridership motivates a broad range of travel demand management (TDM) policies, both in terms of passenger flow control and dynamic pricing strategies. This work aims to reveal the impact of TDM on metro commuters’ behavioural loyalty using stated-preference data collected in Guangzhou, China. Commuters’ behavioural response to TDM strategies is investigated in terms of the possible shift in departure time and travel mode. A hybrid choice model framework is used to incorporate four latent variables of interest, i.e., service quality, overall impression, external attractiveness and switching cost, into the discrete choice model and thereby capture the relationships between the attitudinal factors and observed variables. The model estimation results indicate that the four latent variables all prove useful in interpreting commuters’ behavioural loyalty. Commuters’ perceived service quality and overall impression both show a positive effect on their willingness to continue travelling by metro and are thus instructive for ridership retention. External attractiveness is found to be significant only in the case of the tendency to shift to a private car. Switching costs reveal commuters’ emotional attachment to their already developed commuting habit. These insights into commuters’ behavioural change intention enable metro operators to enhance commuters’ loyalty to their service and develop more effective TDM strategies in future practice.

Keywords: Behaviour change; Nested Logit model; SP-off-RP survey; Attitudinal factor; Urban rail transit (search for similar items in EconPapers)
Date: 2022
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DOI: 10.1007/s11116-021-10179-3

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