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1.
Data Brief ; 46: 108910, 2023 Feb.
Article in English | MEDLINE | ID: covidwho-2178033

ABSTRACT

This dataset contains the full results of a survey on mobility patterns after the Covid-19 pandemic. The survey was conducted in the second trimester of 2021 and collected information from 10000 respondents across 20 urban areas. The questions covered demographic and socio-economic characteristics, employment and job related situation, the use of technological alternatives in daily activities, mobility patterns (trip frequency, purpose, destination, mode, level of comfort), and perceptions as regards the usability of each transport option. Particular emphasis was given to the comparison of current activity to that before the pandemic. The survey combined an online (Computer-Assisted Web Interviews, CAWI) approach with telephone (Computer-Assisted Telephone Interviews, CATI) interviews. The sample in each city was representative of the local demographic and socio-economic profile according to age, sex, employment situation, education and urbanization.

2.
Transp Policy (Oxf) ; 129: 105-116, 2022 Dec.
Article in English | MEDLINE | ID: covidwho-2069748

ABSTRACT

This article explores the changes in transport and mobility patterns that were triggered by the Covid-19 pandemic, as well as citizens' potential new expectations arising from this situation regarding public transport policy and urban planning. We conducted an extensive survey in 20 cities across 11 European countries during the second quarter of 2021, with a total of 10000 respondents. The information that we collected covered the change in the frequency of technology-based alternatives to travel -such as teleworking and online shopping-compared to the pre-pandemic period. It also included the change in trip frequency, purpose, mode and destination. Using the survey dataset as input, we applied a classification model that explains the change in mode choice based on the respondent characteristics and preferences. Our findings suggest that the changes in mobility patterns induced by the pandemic are the result of the combination of the degree of mobility restrictions imposed in each city, the adoption of new lifestyle and work patterns, and individual choices that depend on personal risk aversion. We identify three main challenges for urban transport policy: the increasing use of car that can reinforce long-term car dependency, the avoidance of public transport that may lead to financial and operational instability, and the uncertainty as regards the future of innovation in urban transport, especially as regards emerging technologies and business models.

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