• Investigate work travel mode choice (TMC) and promote a sustainable transportation system. • Household income and vehicle ownership have a positive correlation with motorized transport. • Public and non-motorized transport were found to have a positive correlation with urban areas. • Holding a driving license and the number of workers in a household are the most influential variables toward TMC. Travel mode choice (TMC) prediction is crucial for urban planning, transportation policy-making, and environmental sustainability. Understanding and forecasting how individuals choose their work travel modes can provide valuable insights that influence several societal and economic outcomes. Past studies analysed individual datasets to separately examine the relationships among the built environment, socio-demographic characteristics, economic factors, household vehicle ownership, and driver’s license ownership. However, there is a lack of research examining how these variables collectively shape individual work TMC at both the individual and household levels. The current study addresses this gap by utilising multidimensional data from the 2022 National Household Travel Survey to assess the combined influence of household characteristics, socio-economic status, driver’s license ownership, and urban/rural spatial environment on work TMC. The data are analysed using cross-tabulation, graphical bivariate analyses, and multinomial logistic regression due to a categorical dependent variable. The statistical analysis reveals that the employment status and driver’s license ownership are the primary predictors significantly influencing the preference for motorised (MT) over non-motorised transportation (NMT). Households with more vehicles and workers are more likely to use MT, whereas larger households tend to prefer public transport (PT) or NMT. Additionally, demographic factors, including age, gender, income, and urban/rural residence, play a pivotal role, with older individuals and males showing a higher likelihood of choosing MT, while high-income individuals favour both MT and PT over NMT. Governments can promote PT through infrastructure development, last-mile connectivity, and subsidies, while reducing car dependency through congestion pricing and carpooling incentives, and encouraging NMT by expanding bike lanes and pedestrian-friendly infrastructure.
Ali et al. (Fri,) studied this question.
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