摘要：Teleworking and online shopping became commonplace during the COVID-19 pandemic and can be expected to maintain a strong presence in the foreseeable future. They can lead to significant changes in mobility patterns and transport demand. It is still unclear, however, how extensive their adoption can be, since each individual has different preferences or constraints. The overall impact on transport depends on which segments of the population will modify their behaviour and on what the substitutes to the current patterns will be. The purpose of this work is to identify the user profiles and spatial aspects that affect the adoption of teleworking and online shopping, and to explore the potential impact on transport demand. To that end, data from an EU-wide survey on mobility were analysed using a Machine Learning methodology. The results suggest that while the take up of the new work and consumption patterns is high on average, there are significant differences among countries and across different socio-economic profiles. Teleworking appears to have a high potential mainly in certain services sectors, affecting commuting patterns predominantly in large urban areas. Online shopping activity is more uniform across the population, although differences among countries and age groups may still be relevant. The findings of this work can be useful for the analysis of policies to encourage the uptake of new technologies in transport and mobility. They can be also a good reference point for future studies on the ex-post analysis of the impacts of the pandemic on mobility.
