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Intelligent Transport Systems. 6th EAI International Conference, INTSYS 2022, Lisbon, Portugal, December 15-16, 2022, Proceedings

Research Article

Analysis of the Tourist’s Behavior in Lisbon Using Data from a Mobile Operator

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BibTeX Plain Text
  • @INPROCEEDINGS{10.1007/978-3-031-30855-0_1,
        author={Bruno Francisco and Ricardo Ribeiro and Fernando Batista and Jo\"{a}o Ferreira},
        title={Analysis of the Tourist’s Behavior in Lisbon Using Data from a Mobile Operator},
        proceedings={Intelligent Transport Systems. 6th EAI International Conference, INTSYS 2022, Lisbon, Portugal, December 15-16, 2022, Proceedings},
        proceedings_a={INTSYS},
        year={2023},
        month={4},
        keywords={Tourism Lisbon Travel Behavior Smart Mobility Transportation Networks Big Data Data Analytics Mobile Networks Data driven},
        doi={10.1007/978-3-031-30855-0_1}
    }
    
  • Bruno Francisco
    Ricardo Ribeiro
    Fernando Batista
    João Ferreira
    Year: 2023
    Analysis of the Tourist’s Behavior in Lisbon Using Data from a Mobile Operator
    INTSYS
    Springer
    DOI: 10.1007/978-3-031-30855-0_1
Bruno Francisco1, Ricardo Ribeiro1, Fernando Batista1, João Ferreira2,*
  • 1: Instituto Universitário de Lisboa (ISCTE-IUL)
  • 2: Instituto Universitário de Lisboa (ISCTE-IUL), ISTAR
*Contact email: joao.carlos.ferreira@iscte-iul.pt

Abstract

This paper aims to provide to all entities involved in Lisbon tourism activities a geospatial, statistical, and longitudinal analysis tool based on data provided by a mobile operator in cooperation with Lisbon City council, which allows obtaining knowledge about the behaviors and habits of tourists and visitors of the city. The main intention is to provide information that allows decision-makers to base their choices on real data and facts instead of empirical knowledge and non-sustained information The work was mainly developed in three distinct phases. On the first phase, it was necessary to create knowledge about the tourism business and understand the available data to understand whether they would be able to answer our questions. In the next phase, the dataset was prepared and adapted to our needs - the data given to us had information regarding both mobile phones belonging to Portuguese and foreign users. Considering that our focus was on second group, part of the information was discarded.

Through the work developed, it was possible to identify which countries and geographical areas come from Lisbon’s tourists and visitors. Additionally, we were able to identify, through the available data, the most visited places, and parishes in the city, as well as the place where they eat and sleep when they are in the city. It was also possible to characterize how events such as the Web Summit or a football game influence the behavior and movements of visitors in Lisbon.

The analyses and information provided were duly validated by specialists from the Lisbon Municipal Council, through presentations and questionnaires to decision-makers and users of the developed solution.

Keywords
Tourism Lisbon Travel Behavior Smart Mobility Transportation Networks Big Data Data Analytics Mobile Networks Data driven
Published
2023-04-28
Appears in
SpringerLink
http://dx.doi.org/10.1007/978-3-031-30855-0_1
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