DOI: 10.3390/systems14111402 ISSN: 2079-8954

Moderating Effects of Multidimensional Environmental Factors on the Green Travel Intention–Behavior Relationship: A Case Study of Nanjing, China

Jie Chen, Jiameng Yang, Mengyuan Qiu, Wenrui Zhang, Suwan Li

Green travel is an effective approach to reducing carbon emissions from urban transport and promoting sustainable urban development. However, the factors influencing residents’ green travel behavior and the process through which travel intentions are translated into actual behavior remain insufficiently understood. This study aims to clarify how environmental conditions shape the relationship between green travel intention and behavior and to identify combinations of psychological and environmental factors associated with high levels of green travel behavior. To this end, it integrates the Theory of Planned Behavior (TPB) with Behavior Setting Theory (BST) to examine urban residents’ green travel behavior within a resident-level behavioral system. Environmental factors are classified into three dimensions to investigate how they moderate the relationship between green travel intention and behavior. Data from 707 valid questionnaires collected from residents in Nanjing, China, were analyzed using structural equation modeling (SEM). Fuzzy-set qualitative comparative analysis (fsQCA) was further employed to identify multiple configurations associated with high levels of green travel behavior. The results indicate that attitude, subjective norm, and perceived behavioral control positively influence green travel intention. Green travel intention, in turn, significantly promotes green travel behavior. Furthermore, the natural, built, and technological environments all strengthen the relationship between green travel intention and behavior. The fsQCA results identify six configurations grouped into three broader types, demonstrating that high green travel behavior can arise from multiple combinations of psychological readiness and environmental support. These findings clarify how individual decision processes and environmental conditions jointly shape behavioral outcomes. They also provide practical guidance for designing targeted policies to promote sustainable urban mobility.

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