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Pandemic insights: Analyzing public transport with logit models

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Rizelioğlu, Mehmet
Demir, Şerife Gülsüm
Arslan, Turan

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Emerald Group Publishing Ltd

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The study examines how the COVID-19 pandemic impacted public transportation demand in Bursa province, Turkey. It assessed pre- and during-pandemic usage of major transit systems-buses, trams, and light rail. Through an online survey of 767 participants from key activity centers, it captured changes in public transportation behavior. Using two Ordinal Logit Models, it identified factors influencing preferences, revealing that age, gender, and home-to-work distance mattered before the pandemic, while educational status and distance became crucial during the pandemic. The research further explored the tendency to walk, cycle, or e-scooter use if safe, separated non-motorized transportation routes had been provided, considering various scenarios of distance between homes and workplaces. This study will shed light on decision makers to make sustainable transportation plans by taking into account such catastrophic periods as the pandemic.

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Regression-models, Covid-19, Impact, Public health, Statistical analysis, Transport management, Transport planning, Science & technology, Technology, Engineering, civil, Transportation science & technology, Engineering, Transportation

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