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Exploiting social data for tourism management: the SMARTCAL project

Author

Listed:
  • Annarita Maio

    (University of Milano-Bicocca)

  • Elisabetta Fersini

    (University of Milano-Bicocca)

  • Enza Messina

    (University of Milano-Bicocca)

  • Francesco Santoro

    (ITACA s.r.l.)

  • Antonio Violi

    (University of Sannio)

Abstract

In this work we describe a new Smart Tourism System called SMARTCAL, born during the development of a R&D project for supporting the tourism digitalisation, that includes the release of a pilot in Calabria (a region in the South of Italy). The project is a new initiative to support tourism and hospitality industry with a series of statistical tools for the decision makers, to provide digital and smart services for the tourists that want to build their itineraries with flexibility and to improve the valorisation of a particular territory from the economical and tourist point of view. Indeed, the system is designed by considering Points and Events of Interest (PEOI) and their relationship with the local transport systems, with the hospitality industries and with the policy makers. Two major tools are described in the following: a proactive tourist tour planner algorithm, proposed to generate optimised itineraries based on static and dynamic profiling of the users, and a sentiment analysis module that supports decision makers with a scorecard with a set of key indicators.

Suggested Citation

  • Annarita Maio & Elisabetta Fersini & Enza Messina & Francesco Santoro & Antonio Violi, 2023. "Exploiting social data for tourism management: the SMARTCAL project," Quality & Quantity: International Journal of Methodology, Springer, vol. 57(3), pages 307-319, October.
  • Handle: RePEc:spr:qualqt:v:57:y:2023:i:3:d:10.1007_s11135-020-01049-8
    DOI: 10.1007/s11135-020-01049-8
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    References listed on IDEAS

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    1. Gendreau, Michel & Laporte, Gilbert & Semet, Frederic, 1998. "A tabu search heuristic for the undirected selective travelling salesman problem," European Journal of Operational Research, Elsevier, vol. 106(2-3), pages 539-545, April.
    2. Lorenzo Ardito & Roberto Cerchione & Pasquale Del Vecchio & Elisabetta Raguseo, 2019. "Big data in smart tourism: challenges, issues and opportunities," Current Issues in Tourism, Taylor & Francis Journals, vol. 22(15), pages 1805-1809, September.
    3. Bruce L. Golden & Larry Levy & Rakesh Vohra, 1987. "The orienteering problem," Naval Research Logistics (NRL), John Wiley & Sons, vol. 34(3), pages 307-318, June.
    4. Gunawan, Aldy & Lau, Hoong Chuin & Vansteenwegen, Pieter, 2016. "Orienteering Problem: A survey of recent variants, solution approaches and applications," European Journal of Operational Research, Elsevier, vol. 255(2), pages 315-332.
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