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Effectiveness Analysis of Public Transit Pandemic Prevention Strategy Considering Traveler Risk Perception
Since the outbreak of COVID-19, there have been hundreds of millions of confirmed cases in the world, and people can strongly perceive the risk of infection with the virus in their daily lives, which has seriously affected people’s life and travel, thus hindering the development of all sectors of society, especially the transportation sector. Taking China as an example, since the outbreak of the pandemic, China’s overall public transportation passenger volume has decreased by about 37%, seriously affecting the normal running of the public transit. Therefore, the ways of ensuring the normal running of the public transport system during the pandemic has become the focus of this paper. In order to solve this problem, this paper constructed a SEM model based on pandemic risk perception, analyzed the impact of public transit pandemic prevention strategies (TPS) on risk perception (RP) and travel mode use according to the personal trip survey data in Harbin, China during the pandemic. The results showed that people’s risk perception had a significant negative impact on car usage and transit usage. In other words, people’s risk perception of virus infection had a great impact on travel, especially on the use of public transit. The transit pandemic prevention strategy had a significant negative impact on risk perception, and had a significant positive impact on people’s use of transit. This showed that in the current pandemic outbreak period, the transit pandemic prevention strategy proposed by the Harbin authorities cannot effectively reduce transit usage, and can provide proven and effective transit pandemic prevention strategies. This provided an important support for ensuring the normal running of the public transit system and guiding the sustainable development of public transit during the outbreak of the pandemic.
Effectiveness Analysis of Public Transit Pandemic Prevention Strategy Considering Traveler Risk Perception
Since the outbreak of COVID-19, there have been hundreds of millions of confirmed cases in the world, and people can strongly perceive the risk of infection with the virus in their daily lives, which has seriously affected people’s life and travel, thus hindering the development of all sectors of society, especially the transportation sector. Taking China as an example, since the outbreak of the pandemic, China’s overall public transportation passenger volume has decreased by about 37%, seriously affecting the normal running of the public transit. Therefore, the ways of ensuring the normal running of the public transport system during the pandemic has become the focus of this paper. In order to solve this problem, this paper constructed a SEM model based on pandemic risk perception, analyzed the impact of public transit pandemic prevention strategies (TPS) on risk perception (RP) and travel mode use according to the personal trip survey data in Harbin, China during the pandemic. The results showed that people’s risk perception had a significant negative impact on car usage and transit usage. In other words, people’s risk perception of virus infection had a great impact on travel, especially on the use of public transit. The transit pandemic prevention strategy had a significant negative impact on risk perception, and had a significant positive impact on people’s use of transit. This showed that in the current pandemic outbreak period, the transit pandemic prevention strategy proposed by the Harbin authorities cannot effectively reduce transit usage, and can provide proven and effective transit pandemic prevention strategies. This provided an important support for ensuring the normal running of the public transit system and guiding the sustainable development of public transit during the outbreak of the pandemic.
Effectiveness Analysis of Public Transit Pandemic Prevention Strategy Considering Traveler Risk Perception
Xiaodan Li (Autor:in) / Binglei Xie (Autor:in) / Di Gong (Autor:in)
2023
Aufsatz (Zeitschrift)
Elektronische Ressource
Unbekannt
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