Latent pattern analysis of conscious cooperation for developing sustainable transport
•This study explores the emerging pattern of conscious cooperation for developing sustainable transport.•A multi-factor latent cluster analysis is adopted for testing and validating a research model.•The study identifies three emerging patterns including the diversity average pattern, the pro-social...
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Published in | Transportation research. Part F, Traffic psychology and behaviour Vol. 86; pp. 356 - 369 |
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Main Authors | , |
Format | Journal Article |
Language | English |
Published |
Oxford
Elsevier Ltd
01.04.2022
Elsevier Science Ltd |
Subjects | |
Online Access | Get full text |
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Summary: | •This study explores the emerging pattern of conscious cooperation for developing sustainable transport.•A multi-factor latent cluster analysis is adopted for testing and validating a research model.•The study identifies three emerging patterns including the diversity average pattern, the pro-social pattern and the pro-environment pattern.•This study provides better understanding of conscious cooperation for developing sustainable transport.
This study explores the emerging pattern of conscious cooperation in travel mode selection for developing sustainable transport. A conceptual model for investigating the formation of conscious cooperation is examined based on a multi-factor latent cluster analysis of the survey data from Chinese cites. The study identifies three dominant patterns including the diversity average pattern, the pro-social pattern and the pro-environment pattern. An analysis of such patterns reveals that improving mobility and accessibility is more important than increasing availability of transport facilities for enhancing conscious cooperation. It finds out that there is much more to be done in addressing the concern of travelers on social equity and environment for sustainable transport development. These findings above provide better understanding of the formation of conscious cooperation for developing sustainable transport. |
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ISSN: | 1369-8478 1873-5517 |
DOI: | 10.1016/j.trf.2022.03.004 |