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This study aims to identify the travelers' adoption behavior towards electric vehicles (EVs) using the theoretical background of the Norm Activation Model (NAM) theory. A questionnaire was designed and conducted in Lahore, Pakistan. A total of 402 usable samples were obtained. The collected data were analyzed using factor analysis and Structural Equation Modeling methods. The factor analysis confirmed the hypothesis of the statements designed according to the NAM theory, that is, awareness of consequences (AC), ascription of responsibility (AR), and personal norm (PN). Other factor analyses resulted in the following reliable factors: social and economic values (SEV), personal preferences (PP), willingness to buy (Buy), and willingness to use (Use) of an EV. The results of SEM revealed that the AC, AR, and SEV are significant predictors of PN, whereas the PN and PP are also positive predictors of travelers' willingness to buy and use. The young travelers (≤30 years), motorcycle users, employees, and trip distance (>10 km) have significant and positive correlations with the PN. The car ownership status of travelers has a positive correlation with the ownership and usage of EVs. Suitable behavioral intervention techniques were derived to promote the ownership and usage of EVs in the context of developing regions. [ABSTRACT FROM AUTHOR]

Public transport use has drastically declined during the COVID-19 pandemic because the virus spreads through close contact with infected people and contaminated surfaces, especially in closed-environments. Evidence suggests that following the necessary safety guidelines can limit the spread of the virus, however, non-compliance to precautionary measures has been reported widely. Ignoring the precautionary measures may lead to quick transmission of the virus since public transport vehicles generally resemble closed-environments. This study explores people's intentions to use public transport during the COVID-19 pandemic while adhering to precautionary measures. For this purpose, a total of 1516 useable responses were collected through a questionnaire survey conducted in Lahore, Pakistan. Regression models were developed to model the intentions to use public transport during the pandemic, to adhere to the precautionary measures while using public transport during the pandemic, and to use public transport while suffering from COVID-19 disease. The results of this study will help in understanding the intentions of the public transport users during the COVID-19 pandemic. It will also provide insights for policymakers and public transport operators about further necessary actions to promote safe public transport use during the current and any possible future pandemics. As public transport use declined during the pandemic, policy implications for alternative mobility options such as demand-responsive-transport (DRT) are also presented. Considering the study results, a policy interventions framework is proposed to promote the safe use of various public transport modes, particularly in developing regions. [ABSTRACT FROM AUTHOR]

App-based demand-responsive transit (DRT) services are emerging where conventional public transport is unable to meet the demand. SWVL (choice A) and Airlift (choice B) are two such DRT bus services operating in Lahore, Pakistan. It is important for the policy makers and operators to evaluate the satisfaction levels of the passengers using these services. This study evaluated passengers' satisfaction regarding choice A and choice B through a questionnaire survey. A total of 440 responses were collected from the users of the DRT services through personal interviews and a web-based approach. Factor analysis on the collected data produced two underlying factors, namely service-attributes and bus ambiance. Ordinal regression showed that the service-attributes and ambiance were significant predictors of overall satisfaction levels about choice A. Service-attributes indicated a larger positive impact on overall satisfaction with choice A as compared to ambiance. Although the ordinal model for choice B fitted the data well, the predictors were found to be insignificant. The results offer an insight into which predictors affect the overall satisfaction and how it can be improved. [ABSTRACT FROM AUTHOR]