The Impact of the Coronavirus Outbreak on Public Transportation Choices (‌Case Study: Tehran)

Document Type : Original Article

Authors
Sajad Abdi Shejani 1
Sajad Alizadeh 2
Seyed Mohammad Hossein Dehnad 3
1 M.Sc., Student, Department of Civil Engineering, University of Qom, Qom, Iran.
2 M.Sc., Student, Department of Civil Engineering, University of Semnan, Semnan, Iran.
3 Assistant Professor, Department of Civil Engineering, University of Qom, Qom, Iran.
10.22034/road.2023.350513.2067
Abstract
With the global spread of the coronavirus in late 2020 and the implementation of strict policies to control and mitigate its transmission, including travel restrictions, the behavior of public transportation users underwent significant changes. This shift in user behavior within the public transportation systems of Tehran was assessed through the distribution of over 100 electronic questionnaires to 72 men and 26 women, ranging in age from under 18 to over 65 years. The data were analyzed using SPSS software, employing a Likert scale to evaluate the frequency of public transportation usage across five levels, with a Cronbach's alpha coefficient of 0.822 indicating good reliability. The study revealed the percentage of frequency for various activities prior to the pandemic: educational and training activities (3.16), cultural and artistic activities (4.5), recreational activities (4.13), and religious activities (4.5). In contrast, the frequency of these activities during the pandemic was recorded as follows: educational and training activities (3.9), cultural and artistic activities (2.3), recreational activities (1.11), and religious activities (7.3). While the frequency of non-essential activities decreased during the pandemic, service and healthcare-related activities increased by 3.5% compared to the pre-pandemic period, reflecting a heightened demand for medical services due to COVID-19. Additionally, the number of buses in operation decreased by 1.4% during the pre-pandemic period. However, there was a 2.4% increase in the number of individuals using taxis during the same timeframe.
Keywords
Coronavirus
Public Transport
SPSS Software
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