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The COVID-19 pandemic has significantly impacted Public Transport travel choices worldwide, leading to reduced demand and altered behaviors. Despite prior research suggesting that Public Transport (PT) demand may not fully recover post-pandemic, this claim requires validation in the post-vaccination scenario. Thus, this study is an attempt to model the casual relationship between the observed exogenous variables and latent factors that influenced the trip making behavior, which is related to the mode choice behavior of public transport users for choosing the mode of transport before, during 1st and 2nd wave of COVID-19 pandemic.
A comprehensive questionnaire survey dataset of PT commuters in a developing society is utilized for this study.Confirmatory factor analysis is used to transform 14 exogenous observed variables into smaller sets of factors. Three latent factors with Eigen values greater than one are extracted from the result of factor analysis. Three latent factors, namely 'Behavioral Immune System (BIS)', 'Service Performance (SP)', and 'Service Cost and Payment Method (SCPM)', are examined to understand their dynamic impact on ‘Trip Frequency (TF)’ during different phases of the pandemic. For each phase, first latent factor “BIS” is explained by six (06) observed exogenous variables (social distance, face mask, mysophobia, infection concern, disinfection facility, and air ventilation), second latent factor “SP” is explained by five (05) observed exogenous variables (sitting arrangement, reliability, vehicle entry-exit, in-vehicle time, and comfort), and third latent factor “SCPM” is explained by three (03) observed variables (manual payment, online payment, and daily expense) respectively.
Structural Equation Modeling (SEM) is employed to develop empirical models, effectively capturing both latent factors and observed variables, allowing for an in-depth analysis of risk perception and mode choice. Considering before, during 1st and 2nd wave of COVID as a different phase, the best fitted model is developed after a series of trial for each phase changing the number of latent factors and explaining exogenous observed variables for each latent factor, finally total three models are developed.Six measures are used to determine the goodness of fit of the developed models: (1) Root Mean Squared Error of Approximation (RMSEA); (2) Standardized Root Mean Square Residual (SRMR); (3) Comparative Fit Index (CFI); (4) Tucker-Lewis Index (TLI); (5) Akaike’s Information Criterion (AIC); and (6) Bayesian Information Criterion (BIC).
Before the pandemic, SCPM with the highest coefficient 0.206, emerged as the most influential latent factor, indicating that increased daily expenses reduced travel likelihood. During the first wave of COVID-19, BIS with the highest coefficient -0.206, became the dominant latent variable, negatively affecting TF as fears of contacting the virus during mass transportation led to reduced travel. Interestingly, during the lockdown measures, SCPM's significance diminished as work-related trips were abandoned. In the second wave, SCPM with the highest coefficient 0.246, regained prominence while the significance of BIS decreased due to vaccination programs. PT commuters from lower socioeconomic backgrounds displayed less concern for hygiene factors but prioritized daily expenses, and surprisingly, heavily relied on PT during the second wave. Before COVID, 55.17% of respondents favored PT as their most preferred mode of transportation. During 1stwave of COVID, this preference dropped to 7.40%, and during 2nd wave of COVID, it rebounded to 45.32% of respondents.
This study provides valuable insights into the temporal dynamics of PT travel choices during the pandemic. The findings challenge previous claims and suggest that PT demand may return to pre-pandemic levels, especially in developing societies with lower socioeconomic groups reliant on PT. Policymakers can utilize these findings to develop effective strategies for post-pandemic travel behavior and promote sustainable public transportation systems. |
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