2014/05/16 by Stanislav Sobolevsky, Sobolevsky, Stanislav, Izabela Sitko +11
Business, Management and Accounting · Economics, Econometrics and Finance · Environmental Science · Social Sciences · #62-07 #68U01 #Consumer Retail Behavior Studies #FOS: Computer and information sciences #FOS: Economics and business #FOS: Physical sciences #General Finance (q-fin.GN) #H.2.8 #Human Mobility and Location-Based Analysis #J.4 #Land Use and Ecosystem Services #Physics and Society (physics.soc-ph) #Regional Economics and Spatial Analysis #Social and Information Networks (cs.SI) #Transportation Planning and Optimization
paper · pdf · doi:10.48550/arxiv.1405.4301
openalex publication_date 2014/05/16 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
Intensive development of urban systems creates a number of challenges for\nurban planners and policy makers in order to maintain sustainable growth.\nRunning efficient urban policies requires meaningful urban metrics, which could\nquantify important urban characteristics including various aspects of an actual\nhuman behavior. Since a city size is known to have a major, yet often\nnonlinear, impact on the human activity, it also becomes important to develop\nscale-free metrics that capture qualitative city properties, beyond the effects\nof scale. Recent availability of extensive datasets created by human activity\ninvolving digital technologies creates new opportunities in this area. In this\npaper we propose a novel approach of city scoring and classification based on\nquantitative scale-free metrics related to economic activity of city residents,\nas well as domestic and foreign visitors. It is demonstrated on the example of\nSpain, but the proposed methodology is of a general character. We employ a new\nsource of large-scale ubiquitous data, which consists of anonymized countrywide\nrecords of bank card transactions collected by one of the largest Spanish\nbanks. Different aspects of the classification reveal important properties of\nSpanish cities, which significantly complement the pattern that might be\ndiscovered with the official socioeconomic statistics.\n