Abstract

In designing the city of the future, city managers and urban planners are driven by specific citizens’ behaviors. In fact, economic and financial behaviors, and specifically, which goods and services citizens purchase and how they allocate their spending, are playing a central role in planning targeted services. In this context, cashless payments provide an invaluable data source to identify such spending behaviors. In this work, we propose a methodology to extract the consumption behaviors of a large sample of customers through credit card transaction data. The main outcome of the methodology is a concise representation of the economic behavior of people residing in a city, the so-called city consumption profile. We inferred the city consumption profile from a network-based representation of the similarity among the customers in terms of purchase allocation; on top of which we applied a community detection algorithm to identify the representative consumption profiles. By applying the above methodology to a set of credit card transactions of an Italian financial group, we showed that cities, even geographically close, exhibit different profiles which makes them unique. Specifically, usage patterns focused on a single type of good/service—mono-categorical consumption profile—are the main factors leading to the differences in the city profiles. Our analysis also showed that there is a group of consumption profiles common to all cities, made up by purchases of primary goods/services, such as food or clothing. In general, the city consumption profile represents a tool for understanding the economic behaviors of the citizens and for comparing different cities. Moreover, city planners and managers may use it in the outline of city services tailored to the citizens’ needs.

Highlights

  • According to the United Nations report, today 56% of the world’s population lives in urban areas, a proportion that is expected to increase to 68% by 2050, with 1.7 billion people around the globe moving into a city every week

  • In a step toward achieving a city profile within a people-centric approach, in this work, we address a specific aspect of cities: the city consumption profile

  • Results we report the results about the customers’ spending behaviors and the city consumption profiles of some of the most important cities in Northern Italy derived by applying the above methodology to the credit card transaction dataset

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Summary

Introduction

According to the United Nations report (https://unhabitat.org/sites/default/files/​2020/10/wcr_​2020_report.pdf ), today 56% of the world’s population lives in urban areas, a proportion that is expected to increase to 68% by 2050, with 1.7 billion people around the globe moving into a city every week. Existing literature on urban studies has started addressing the issue of creating the profile of the cities, but we are still a long way from being able to reconstruct comprehensive profiles, including the wealth of aspects and facets that make a city one of a kind (Moustaka et al 2017, 2020). In this context, urban science research (Lobo et al 2020; Silva et al 2019; Batty 2021) is seeking to provide tools and results for a fine comprehension of cities, increasingly within a citizen-centric approach. Di Clemente et al (2018) have used a text compression technique on the sequences of credit card purchases, as here, to show that it is possible to detect ubiquitous patterns of collective behavior

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