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Evaluation and improvement of a slow traffic system in a cold regional campus based on travel satisfaction

Zhang Jiaxin, Sun Xiaohui, Liu Jincheng, Guliziba Aimaiti

Transport Problems

2025

T. 20, z. 1

99--110

This study establishes a Bayesian-structural equation model based on the travel satisfaction survey at the Boda Campus of Xinjiang University to construct and optimize the slow traffic system of campus in cold regions. Moreover, relevant indicators are selected to construct the evaluation system of the campus’s slow traffic system in cold regions. Then, strategies are proposed to optimize the campus’s slow traffic system according to the key elements highlighted by the evaluation system. The results show that subjective emotion and perceived time have a great influence on travel satisfaction. The connectivity and density of the walking and cycling network, anti-skid performance of the road surface, canopy amount, and parking/pick-up convenience of shared bicycle sites substantially influence the construction of campuses’ slow traffic systems in cold regions. The score of the optimized campus’s slow traffic system increased by 72.10% compared with that of the pre-optimized system.

Research on the differentiation of urban residents’ low carbon travel intentions

Sun Xiaohui, Zhang Jiaxin, Wang Feiyan, Ran Jin

Transport Problems

2024

T. 19, z. 4

165--175

The literature on low-carbon travel (LCT) of urban residents regards urban residents as homogeneous individuals and lacks quantitative delineation of the disparities in LCT intentions among different residents. Therefore, this study aims to use Chinese cities as cases to comprehensively investigate the influencing factors and interaction mechanisms of the LCT intentions of urban residents in different regions with different characteristics. First, based on the theory of planned behavior, this study comprehensively considers the inner psychological factors and external factors, selects five psychological latent variables and designs a questionnaire to obtain the LCT intentions data in cities of Shenzhen and Xi’an in China. Secondly, according to the LCT intention data, the residents of Shenzhen and Xi’an are divided into three classes: low intention, medium intention, and high intention. Finally, structural equation models are constructed for different classes of urban residents to investigate the key factors influencing their choices of LCT. The findings indicate that the influencing factors and influencing mechanisms of LCT intentions vary among residents of different intention classes. For residents with low and high intentions, acceptance attitude and subjective norms are the key factors affecting the LCT intentions; for residents with medium intentions, policy perception is the key factor.