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Three Decades of Business Activity Evolution in Curitiba: A Case Study

Author

Listed:
  • Nádia P. Kozievitch

    (Universidade Tecnológica Federal do Paraná)

  • Thiago H. Silva

    (Universidade Tecnológica Federal do Paraná)

  • Artur Ziviani

    (Laboratório Nacional de Computação Científica)

  • Giovani Costa

    (Universidade Tecnológica Federal do Paraná)

  • Gustavo Lugo

    (Universidade Tecnológica Federal do Paraná)

Abstract

Recent concepts such as Smart Cities, Urban Computing, and Geographic Information Systems are being discussed in various international forums, using themes such as sustainability and efficient use of the city infrastructures. One important aspect in this regard is to correctly associate computational techniques with statistical models and integrate heterogeneous data sources using open data shared by cities. Based on that, this study uses open data from the city of Curitiba (Brazil) in order to bring results on the spatiotemporal evolution of business activities along a period of over thirty years. To that end, the study identifies and discusses important challenges that had to be tackled toward data quality, data categorization, and data integration, in order to perform this type of study in practice. By looking at the dynamics of geographically grounded microeconomic variables, this study shows how the expansion and diversification of business types in different neighborhoods happened, contributing to a better understanding of the process of evolution of the business activity in a city.

Suggested Citation

  • Nádia P. Kozievitch & Thiago H. Silva & Artur Ziviani & Giovani Costa & Gustavo Lugo, 2017. "Three Decades of Business Activity Evolution in Curitiba: A Case Study," Annals of Data Science, Springer, vol. 4(3), pages 307-327, September.
    • Handle: RePEc:spr:aodasc:v:4:y:2017:i:3:d:10.1007_s40745-017-0104-5
    DOI: 10.1007/s40745-017-0104-5
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    References listed on IDEAS

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    1. Weigang Yan & Mike Hutchins & Steven Loiselle & Charlotte Hall, 2016. "An Informatics Approach for Smart Evaluation of Water Quality Related Ecosystem Services," Annals of Data Science, Springer, vol. 3(3), pages 251-264, September.
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