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Transactions on Large-Scale Data- and Knowledge-Centered Systems XXVII pp 177–189Cite as

Analysis of Customers’ Spatial Distribution Through Transaction Datasets

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Part of the book series: Lecture Notes in Computer Science ((TLDKS,volume 9860))

Abstract

Understanding people’s consumption behavior while traveling between retail shops is essential for successful urban planning as well as determining an optimized location for an individual shop. Analyzing customer mobility and deducing their spatial distribution help not only to improve retail marketing strategies, but also to increase the attractiveness of the district through the appropriate commercial planning. For this purpose, we employ a large-scale and anonymized datasets of bank card transactions provided by one of the largest Spanish banks: BBVA. This unique dataset enables us to analyze the combination of visits to stores where customers make consecutive transactions in the city. We identify various patterns in the spatial distribution of customers. By comparing the number of transactions, the distributions and their respective properties such as the distance from the shop we reveal significant differences and similarities between the stores.

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Acknowledgments

We would like to thank the Banco Bilbao Vizcaya Argentaria (BBVA) for providing the dataset for this study. Special thanks to Juan Murillo Arias, Marco Bressan, Elena Alfaro Martinez, Maria Hernandez Rubio and Assaf Biderman for organizational support of the project and stimulating discussions. We further thank MIT SMART Program, Accenture, Air Liquide, The Coca Cola Company, Emirates Integrated Telecommunications Company, The ENEL foundation, Ericsson, Expo 2015, Ferrovial, Liberty Mutual, The Regional Municipality of Wood Buffalo, Volkswagen Electronics Research Lab and all the members of the MIT Senseable City Lab Consortium for supporting the research.

Author information

Authors and Affiliations

  1. SENSEable City Laboratory, Massachusetts Institute of Technology, 77 Massachusetts Avenue, Cambridge, MA, 02139, USA

    Yuji Yoshimura, Alexander Amini, Stanislav Sobolevsky & Carlo Ratti

  2. Department of Information and Communication Technologies, Universitat Pompeu Fabra, Roc Boronat, 138, Tanger Building, 08018, Barcelona, Spain

    Yuji Yoshimura & Josep Blat

  3. Center for Urban Science and Progress, New York University, 1 MetroTech Center, 19th Floor, Brooklyn, NY, 11201, USA

    Stanislav Sobolevsky

Authors
  1. Yuji Yoshimura
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  2. Alexander Amini
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  3. Stanislav Sobolevsky
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  4. Josep Blat
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  5. Carlo Ratti
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Corresponding author

Correspondence to Yuji Yoshimura .

Editor information

Editors and Affiliations

  1. IRIT, Paul Sabatier University, Toulouse, France

    Abdelkader Hameurlain

  2. FAW, University of Linz, Linz, Austria

    Josef Küng

  3. FAW, University of Linz, Linz, Austria

    Roland Wagner

  4. MIT SENSEable City Lab, Cambridge, Massachusetts, USA

    Amin Anjomshoaa

  5. Faculty of Business and Information Technology, University of Ontario Institute of Technology (UOIT), Oshawa, Ontario, Canada

    Patrick C. K. Hung

  6. Trinity University, Plainview, Texas, USA

    Dominik Kalisch

  7. New York University, Brooklyn, New York, USA

    Stanislav Sobolevsky

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Yoshimura, Y., Amini, A., Sobolevsky, S., Blat, J., Ratti, C. (2016). Analysis of Customers’ Spatial Distribution Through Transaction Datasets. In: Hameurlain, A., et al. Transactions on Large-Scale Data- and Knowledge-Centered Systems XXVII. Lecture Notes in Computer Science(), vol 9860. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-53416-8_11

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  • DOI: https://doi.org/10.1007/978-3-662-53416-8_11

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-662-53415-1

  • Online ISBN: 978-3-662-53416-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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