Planning mobility solutions that are tailored to the users needs, while being sustainable and energy efficient, will be crucial for the development of the Smart Cities of the future. This is especially true nowadays, given the environmental and political issues characterizing this historical time. Sharing mobility can be an asset in increasing the sustainability of daily transportation in urban areas, allowing more people to move around, while leading to energy and resource savings. At the same time, there are several barriers preventing the adoption of this mobility solution. In this work, we introduce the steps leading to the construction of the Sharing-DNA, a novel data-driven tool to understand the main levers of individual attitudes towards sharing services. By compactly embedding relevant information on the socio-economic profile and mobility preferences of potential adopters, this new tool can be of use for the design of incentive policies in the future Smart Cities. This is proven by the preliminary results obtained by exploiting the Sharing-DNA to detect clusters of sharing-oriented and less sharing-enthusiast individuals within Europe. The characteristics of these clusters allow us to shed a light on the attributes of the final users (or potential ones) of sharing services, providing a useful machinery for the design of common fostering policies.

Sharing-DNA: a data-driven tool to map the attitude towards sharing services across Europe

Villa E.;Preti G.;Riva M.;Breschi V.;Tanelli M.
2022-01-01

Abstract

Planning mobility solutions that are tailored to the users needs, while being sustainable and energy efficient, will be crucial for the development of the Smart Cities of the future. This is especially true nowadays, given the environmental and political issues characterizing this historical time. Sharing mobility can be an asset in increasing the sustainability of daily transportation in urban areas, allowing more people to move around, while leading to energy and resource savings. At the same time, there are several barriers preventing the adoption of this mobility solution. In this work, we introduce the steps leading to the construction of the Sharing-DNA, a novel data-driven tool to understand the main levers of individual attitudes towards sharing services. By compactly embedding relevant information on the socio-economic profile and mobility preferences of potential adopters, this new tool can be of use for the design of incentive policies in the future Smart Cities. This is proven by the preliminary results obtained by exploiting the Sharing-DNA to detect clusters of sharing-oriented and less sharing-enthusiast individuals within Europe. The characteristics of these clusters allow us to shed a light on the attributes of the final users (or potential ones) of sharing services, providing a useful machinery for the design of common fostering policies.
2022
ISC2 2022 - 8th IEEE International Smart Cities Conference
978-1-6654-8561-6
Data analysis
Green mobility
Machine Learning
Sharing services
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11311/1241718
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