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Author:

Zhou, Y.-Y. (Zhou, Y.-Y..) | Wang, P.-Y. (Wang, P.-Y..) | Chen, Y.-Y. (Chen, Y.-Y..)

Indexed by:

EI Scopus

Abstract:

The effectiveness of "green travel" guidance is influenced by external information and travelers' choice preferences. The heterogeneity of potential attribute categories of travelers needs to be considered. Self-presentation manifests itself as people influencing others' impressions of themselves by controlling the information that relates to them, which reflects the interaction of information and choice preferences. To quantify the influence of travelers' self-presentation awareness and environmental awareness on mode choice behavior, 1382 valid samples were collected through a questionnaire survey. The latent class model (LCM) is used to classify the travelers into high self-presentation group (18.23%), medium self-presentation group (20.26%) and low self-presentation group (61.51%). The results of the discrete choice model suggest that travelers pay more attention to travel time and the characteristics of the travel mode itself when making mode choices. The effect of travel expense on the high self-presentation group would be overestimated if mode characteristics are not considered. Travelers from the high self- presentation group have a strong preference for public transit only for short-distance trips, and their tendency for private cars is obvious for trips of 6 to 10 kilometers. The preference value of the low self-presentation group for cycling can offset to some extent the negative utility of excessively long travel times in short to medium distance trips. The construction of a mode choice model that considers travelers' heterogeneity can provide a theoretical basis for the government and related departments to formulate more coordinated and targeted regulation policies and public transportation operation strategies. © 2023 Science Press. All rights reserved.

Keyword:

self-presentation urban traffic latent class model travel behavior travel mode choice environmental awareness

Author Community:

  • [ 1 ] [Zhou Y.-Y.]Beijing Key Laboratory of Traffic Engineering, Ministry of Transport, Beijing University of Technology, Beijing, 100124, China
  • [ 2 ] [Zhou Y.-Y.]Key Laboratory of Advanced Public Transportation Sciences, Ministry of Transport, Beijing University of Technology, Beijing, 100124, China
  • [ 3 ] [Wang P.-Y.]Beijing Key Laboratory of Traffic Engineering, Ministry of Transport, Beijing University of Technology, Beijing, 100124, China
  • [ 4 ] [Chen Y.-Y.]Beijing Key Laboratory of Traffic Engineering, Ministry of Transport, Beijing University of Technology, Beijing, 100124, China
  • [ 5 ] [Chen Y.-Y.]Key Laboratory of Advanced Public Transportation Sciences, Ministry of Transport, Beijing University of Technology, Beijing, 100124, China

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Source :

Journal of Transportation Systems Engineering and Information Technology

ISSN: 1009-6744

Year: 2023

Issue: 3

Volume: 23

Page: 30-38

Cited Count:

WoS CC Cited Count: 0

SCOPUS Cited Count: 6

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 6

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