Money on the Move: Big Data of Bank Card Transactions as the New Proxy for Human Mobility Patterns and Regional Delineation. The Case of Residents and Foreign Visitors in Spain

• Published in: 2014 IEEE International Congress on Big Data pp. 136 - 143
• Main Authors: Sobolevsky, Stanislav, Sitko, Izabela, Tachet des Combes, Remi, Hawelka, Bartosz, Arias, Juan Murillo, Ratti, Carlo
• Format: Conference Proceeding
• Language: English
• Published: IEEE 01.06.2014
• Subjects: bank card transactions; big data; Business; Cities and towns; Communities; Economics; Electronic mail; Gravity; human mobility; network analysis; Optimization; regional delineation
• ISSN: 2379-7703
• DOI: 10.1109/BigData.Congress.2014.28

Increasing availability of big data, which documents human activity in space and time, offers new solutions to well-known operational problems. Recent studies have demonstrated how topological community detection in large-scale networks of human interactions and mobility can produce geographically cohesive regions, which are meaningful for the regional division of countries. So far, those networks have mainly been built based on the country-wide datasets of telephone calls, typically available for residents of a country. However, it is natural to expect that foreign visitors explore a country in a different way, with patterns that vary depending on nationality. Understanding those differences can be of a great importance for the touristic industry and transportation planning. In this study, we demonstrate the potential of a new type of extensive data, namely bank card transactions executed in a variety of businesses by the domestic and foreign customers of a Spanish bank. We confirm applicability of this data to the regional delineation inline with other datasets and reveal new opportunities related to the distinction of customers by their origin. We point out the important differences between the optimal regional structure derived from the mobility of residents and of foreign visitors. The definition of the mobility network appears to be a crucial component of the methodology, and is potentially sensitive to the dataset being used. While a reasonable comparison of results obtained based on different data of course requires the consistency of such definition. We propose a novel, consistent way of constructing mobility networks using transactional data, a way transposable to a variety of other datasets. Finally, we perform a quantitative study of the impact of tourists' nationality on their mobility behavior. We find a surprisingly consistent trend between the distance from a given country to Spain, and the mobility characteristics of visitors coming from this country, i.e. the parameters of the gravity model estimation.