Resilience in demand for public transportation during the pandemic

The concept of resilience and its applicability to ecological, social, and business systems are capable of restructuring and recovering from a perturbation that corroborates (Holling, 1974; Holling and Gunderson, 2002; Walker et al., 2004)
The associated external shocks, such as environmental issues, oil shocks, or congestion, contribute significantly to the difference in choices observed in travel mode preference. Notably, unexpected disasters cause considerable damage to transportation networks, culminating in significant economic disruption (Nakanish et al., 2014; Chang and Nojima, 2001).

The presence of external shocks, such as COVID-19, negatively influences the stability of public transport demand. To enhance the resilience of the public transportation system, it is imperative to analyze the extent of the impact of such external shocks on overall use.
Therefore, this study aimed to establish the impact of the daily confirmed cases of COVID-19 on the use of the public transportation system.

This study’s data contain
• Total number of passengers using the subway in Seoul metropolitan area
(Number of total passengers = get in + get off from each station)
• Newly confirmed cases: Korea total, Seoul
• Traffic volume, inside Seoul
• Weather (rain or snow)
on a daily basis (2020.01.20 ~ 2020.04.30).

I employed two techniques to analyze panel data: Fixed effect and random effect.
If the fixed-effect model is consistent, individual effects will correlate with the other variables in the model, while the random-effects model will present a contrariwise result. Conversely, if the individual effects are not correlated with the other variables in the model; in that case, is possible to define both random effects as efficient and random, and fixed effects as consistent.

Considering the p-value of the Hausmann test is greater than 0.01, the null hypothesis should be adopted, and it was established that it is appropriate to select a random effect model.

The result is as presented in [Table 1]:

[Table 1] Panel Analysis Result

Compared to overall confirmed cases, Seoul’s confirmed cases had a more significant effect on the decreased number of subway passengers in each station than the number of total confirmed cases in South Korea. However, considering South Korea is quite a small country, people can travel from the northernmost region to the southernmost region in 6 hours. The number of confirmed cases in other regions also significantly influenced the choice of commuters who opted for the subway.

Consequently, it was expected that people would use more cars when moving instead of public transport; contrary to such an assumption, they were proportional to each other. This can be interpreted as a result of the decrease in overall inner-city traffic due to quarantine.

Notably, people tend to commute by subway on a snowy/rainy day, rather than sunny days.
Although this study is relevant considering it addresses changes in demand for subways.

However, additional data and in-depth research are imperative to reinforce the assertion.
A comparison between the number of passengers who opted for the bus and subway was conducted to establish which type of public transportation had a greater impact on the COVID-19 pandemic. Furthermore, to demonstrate the impact of transit on the pandemic, it is crucial to examine which transit system suffered from a greater decline in passengers between the transit and non-transit stations.

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