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Journal Articles Applied Network Science Year : 2017

Crowdsourcing the Robin Hood effect in cities

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Abstract

Socioeconomic inequalities in cities are embedded in space and result in neighborhood effects, whose harmful consequences have proved very hard to counterbalance efficiently by planning policies alone. Considering redistribution of money flows as a first step toward improved spatial equity, we study a bottom-up approach that would rely on a slight evolution of shopping mobility practices. Building on a database of anonymized credit card transactions in Madrid and Barcelona, we quantify the mobility effort required to reach a reference situation where commercial income is evenly shared among neighborhoods. The redirections of shopping trips preserve key properties of human mobility, including travel distances. Surprisingly, for both cities only a small fraction (∼ 5%) of trips need to be altered to reach equity situations, improving even other sustainability indicators. The method could be implemented in mobile applications that would assist individuals in reshaping their shopping practices, to promote the spatial redistribution of opportunities in the city.
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Dates and versions

hal-01535480 , version 1 (09-06-2017)

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Thomas Louail, Maxime Lenormand, Juan Murillo Arias, Jose Javier Ramasco. Crowdsourcing the Robin Hood effect in cities. Applied Network Science, 2017, 2 (11), ⟨10.1007/s41109-017-0026-3⟩. ⟨hal-01535480⟩
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