Study of Residents’ Ongoing Behavioural Intentions for Regular Bus Travel


  • Jinhui Li Henan University of Science and Technology, School of Vehicle and Traffic Engineering
  • Jiahao Sun Henan University of Science and Technology, School of Vehicle and Traffic Engineering
  • Weihang Wang Henan University of Science and Technology, School of Vehicle and Traffic Engineering



urban transport, ongoing behavioural intentions, planned behaviour, regular bus travel, multiple-group analysis


With the emergence of novel transportation trends, regular buses have experienced a significant decline in passenger numbers. Consequently, it becomes imperative to conduct studies on passengers’ intentions. This particular investigation employed a meticulously designed survey questionnaire to gather data, and developed a new model that integrates the theory of planned behaviour, technology acceptance model and expectation confirmation theory. The primary aim was to explore the key factors that influence residents’ ongoing behavioural intentions towards regular public bus travel. Furthermore, a gender-based multi-group analysis was conducted to investigate the impact mechanism of gender differences on ongoing behavioural intentions. The new model demonstrates various degrees of positive or negative influences among the variables, thereby confirming its universal applicability. Moreover, the multi-group analysis reveals that compared to gender, travel satisfaction has a stronger impact on women’s intentions, while travel attitude has a stronger impact on men’s intentions to travel by certain mean of transport. Simultaneously, perceived behavioural control does not significantly affect persistent intention for women but has a significant positive impact on persistent intention for men. Furthermore, perceived ease of use does not significantly impact perceived usefulness for women but has a significant positive effect on perceived usefulness for men. These research findings bear great significance in promoting environmentally-friendly travel practices.


Akbari M, et al. Consumers’ intentions to use ridesharing services in Iran. Research in Transportation Business & Management. 2021;41:100616. DOI: 10.1016/j.rtbm.

Wang Y, et al. An empirical study of consumers’ intention to use ride-sharing services: Using an extended technology acceptance model. Transportation. 2020;47(1):397-415. DOI: 10.1007/s11116-018-9893-4.

Huang C, et al. Impact factors of travel intention during the toll road being free on the major holidays. Journal of Transportation Systems Engineering and Information Technology. 2013;13(6):161-168. DOI: 10.3969/j.issn.1009-6744.2013.06.025.

Jian Y, Zhang J, Jin S. Analysis of influencing factors of residents' willingness to custom bus travel. Journal of Wuhan University of Technology Transportation Science & Engineering. 2019;43(2):247-252. DOI: 10.3963/j.issn.2095-3844.2019.02.014.

Ismael K, Duleba S. Investigation of the relationship between the perceived public transport service quality and satisfaction: A PLS-SEM technique. Sustainability. 2021;13(23):13018. DOI: 10.3390/su132313018.

Sun S. An evaluation approach for public transit loyalty considering passengers' emotional value. Journal of Transportation Systems Engineering and Information Technology. 2020;20(4):158-165. DOI: 10.16097/j.cnki.1009-6744.2020.04.023.

Allen J, et al. The role of critical incidents and involvement in transit satisfaction and loyalty. Transport Policy. 2019;75(MAR.):57-69. DOI: 10.1016/j.tranpol.

Hjorteset MA, Böcker L. Car sharing in Norwegian urban areas: Examining interest, intention and the decision to enrol. Transportation Research Part D: Transport and Environment. 2020;84:102322. DOI: 10.1016/j.trd.2020.102322.

Rafiq R, Mitra SK. Shared school transportation: Determinants of carpooling as children’s school travel mode in California. Transportation. 2020;47(3):1339-1357. DOI: 10.1007/s11116-018-9942-z.

Pang S, et al. Knowledge sharing platforms: An empirical study of the factors affecting continued use intention. Sustainability. 2020;12(6):2341. DOI: 10.3390/su12062341.

Huang D, et al. A two-phase optimization model for the demand-responsive customized bus network design. Transportation Research Part C Emerging Technologies. 2020;111(7):1-21. DOI: 10.1016/j.trc.2019.12.004.

Xiong R, et al. The influence path of urban residents' electric vehicle travel intention: Based on fuzzy set qualitative comparative analysis. Journal of Transportation Engineering and Information. 2022;20(4):31-41.

Oa JD, E Estévez, Oa RD. Public transport users versus private vehicle users: Differences about quality of service, satisfaction and attitudes toward public transport in Madrid (Spain). Travel Behaviour and Society. 2021;23,76-85. DOI: 10.1016/j.tbs.2020.11.003.

Zhang Yu-Yang, Zou Z, Zhang H. Research on low-carbon commuting willingness of Beijing-Tianjin-Hebei residents based on structural equation. City Planning Review. 2023;47(2):67-74.

Allen J, et al. Effect of critical incidents on public transport satisfaction and loyalty: An ordinal probit SEM-MIMIC approach. Transportation. 2020;47: 827-863. DOI: 10.1007/s11116-018-9921-4.

Chen J, et al. Multiple-group structural equation model of passenger satisfaction in urban rail transit. Journal of Transportation Systems Engineering and Information Technology. 2018;18(1):173-178,244. DOI: 10.16097/j.cnki.1009-6744.2018.01.026.




How to Cite

Li, J., Sun, J., & Wang, W. (2024). Study of Residents’ Ongoing Behavioural Intentions for Regular Bus Travel. Promet - Traffic&Transportation, 36(2), 345–356.