Applying a Bayesian network for modelling the shift from motorcycle to public transport use in Vietnam

Son-Tung Nguyen, Mehdi Moeinaddini, Ismaïl Saadi and Mario Cools

Transportation Research Part A: Policy and Practice, 2024, vol. 183, issue C

Abstract: Transport mode choice models commonly incorporate factors such as utility maximisation, socio-ecological considerations, socio-demographic characteristics, and psychological factors. However, there is still a lack of integrated models linking objective factors, such as travel mode attributes, demographic & socio-economic characteristics and built environmental characteristics, with subjective factors, such as attitudes, personal norms, and perceived behavioural control, to better understand the commuters’ modal choices. Furthermore, a clear research gap exists on mode choice behaviour in Southeast Asian countries, where motorcycling is widespread. This study aims to address these research gaps by analysing data gathered from 618 Vietnamese motorcyclists between December 2020 and February 2021. Reliability analysis and a Bayesian network are used to identify the objective and subjective factors influencing the intention to use public transport among Vietnamese motorcyclists. The findings highlight that among five subjective factors, personal norm is the most sensitive parameter in calculating the posterior probability distribution of intention and decision to use public transport along with other objective factors, namely travel time and travel cost. The results also reveal that motorcyclists aged 23 + have a higher perceived value of travel time than those aged 23–. In contrast, motorcyclists aged 23– and female motorcyclists have a higher perceived value toward environment-friendly travel modes, such as public transport. At the same time, they do not try to differentiate themselves from the societal standards in terms of motorcycle usage. The findings of this study provide valuable insights to local urban/transport planners and policymakers in Southeast Asian countries.

Keywords: Travel mode choice; Modal shift; Motorcyclist; Public transport; Bayesian-networks; Network-learning (search for similar items in EconPapers)
Date: 2024
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DOI: 10.1016/j.tra.2024.104062

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