Investigating factors affecting university students' use of subway before and after COVID-19 outbreak: A case study in Tehran

Social and spatial heterogeneities in COVID-19 impacts on individual's metro use: A big-data driven causality inference

“…Third, the limited attention given to the causality at the individual level might be due to the lack of longitudinal observations of individuals' repeated metro use, particularly right before and after the occurrence of the outbreak and mobility intervention events. Most existing studies rely on data from questionnaire surveys or interviews and transit smart card big data to investigate the associations between the COVID-19 and individual's metro use ( Lee, 2022 ; Maljaee & Sameni, 2022 ; Park et al, 2022 ; Zhou et al, 2021 ). However, these data sources are often difficult to be applied to build rigorous quasi-experimental designs.…”

“…However, these data sources are often difficult to be applied to build rigorous quasi-experimental designs. For example, the data of questionnaire surveys are often cross-sectional or two waves with before-and-after information ( Cho & Park, 2021 ; Maljaee & Sameni, 2022 ). It is difficult to track the change of an individual's metro use behaviors in multiple time series, thus failing to estimate time-varying causal effects of the COVID-19 or intervention policies.…”

“…It is difficult to track the change of an individual's metro use behaviors in multiple time series, thus failing to estimate time-varying causal effects of the COVID-19 or intervention policies. By contrast, the smart card data typically provides a time series of repeated observations of daily metro use information, whereas this type of data is mostly not rich enough to support individual-based research, but aggregated at the station level or merely focused on single-faceted socioeconomic groups (e.g., Maljaee & Sameni, 2022 ; Park & Cho, 2021 ). To be more specific, such datasets have limited information of the individual's socioeconomic attributes for control and other travel behavior outcomes but only the metro use ( Lee, 2022 ).…”

“…An increasing number of empirical studies have substantiated the change of city-level or station-level metro transit ridership due to the pandemic and mobility policies ( Chang et al, 2021 ; Jiang & Cai, 2022 ; Kwon et al, 2022 ). However, only a limited number of studies have investigated the change of individual-level metro use behaviors, including metro trip frequency, travel time, and mode shift from metro to private cars ( Astroza et al, 2020 ; Park & Cho, 2021 ; Park et al, 2022 ; Maljaee & Sameni, 2022 ). The individual-level research, which is needed more, can help policymakers identify vulnerable socioeconomic groups and disadvantaged groups in metro use during and post the pandemic, promoting effective and equitable mobility intervention policies ( Park et al, 2022 ).…”

Impact of the COVID-19 on electricity consumption of open university campus buildings – The case of Twente University in the Netherlands

“…At the same time, a series of changes in the behavior of people's daily activities, such as work and study, have occurred due to restrictive policies. The daily behavior of occupants, in turn, has a significant impact on building energy consumption [17] , [18] . Therefore, the restrictive policies during the epidemic will certainly cause changes in building energy consumption.…”