The development and evolution of the digital society has brought about relevant changes in the way people experience the city today. In particular, its impact on mobility patterns is evident, especially in the Post-COVID-19 society, where it is possible to access different types of daily activities online (e.g. working, shopping, training, etc.). At the same time, this digital era brings with it new challenges for urban and transport planning, in which information and communication technologies (ICT) can play a relevant role as transformers of traditional urban structures. For this reason, studying and understanding how the digital society is transforming current cities is important and necessary to optimize planning patterns/guidelines and achieve more sustainable and inclusive cities.To address this challenge, this project has implemented multivariate statistical techniques to characterize the city of Madrid (Spain) at urban level, in order to detect the impact of ICTs on the current urban structure of the city. The methodology incorporated both factorial and cluster analysis with spatial restriction, based on a set of starting indicators referring to urban equipment, demography, socioeconomics, transportation, as well as variables of the digital society (e.g., electronic mailboxes-online commerce, free public and commercial Wi-Fi points, etc.).The results, among other things, show an optimal classification grouping, as well as the way it was obtained. In this case, the optimal classification grouping is the one conformed by 6 clusters, in which different relationships were detected between the space built, the equipment and aspects of the digital society such as online shopping and the proximity to transport equipment public and physical commerce. These results support a growing influence of the digital society in the urban characterization, suggesting the need to translate this influence into effective planning criteria.
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