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Exploring Tourists’ Food and Beverage Spots in an Urban Destination Using a Spatial–temporal Approach

In: Transcending Borders in Tourism Through Innovation and Cultural Heritage

Author

Listed:
  • Ioannis A. Nikas

    (University of Patras)

  • Athanasios Koutras

    (University of Peloponnese)

  • Alkiviadis Panagopoulos

    (University of Patras)

  • Anastasios Vasileiadis

    (University of Patras)

Abstract

An important part of planning a trip involves not only search for accommodation, but for food and beverage spots as well, to enhance the visitor’s travel experience, especially when the trip involves visits to major urban centers. The agony and/or joy of tourists to meet the desired destinations can be seen nowadays in the continuous and overwhelming number of posts of their exact geographical position whereabouts together with evaluations of the provided travel services, using social networks and photo-sharing applications. The process of capturing and evaluating the travel experience has now been integrated into the life cycle of a trip, whether it involves visiting a museum, the accommodation, or the meals and drinks during the day. In this work, a temporal-spatial methodology is proposed, based mainly on clustering methods, to analyze geo-tagged data related to potential food and beverage choices of visitors in major urban centers during their holidays. Our aim is to depict spatially and temporally tourists’ food and beverage preferences during their stay in a city. The proposed methodology is tested on data acquired from the city of Athens from the Flickr photo-sharing platform and the OpenStreetMap web services.

Suggested Citation

  • Ioannis A. Nikas & Athanasios Koutras & Alkiviadis Panagopoulos & Anastasios Vasileiadis, 2022. "Exploring Tourists’ Food and Beverage Spots in an Urban Destination Using a Spatial–temporal Approach," Springer Proceedings in Business and Economics, in: Vicky Katsoni & Andreea Claudia Şerban (ed.), Transcending Borders in Tourism Through Innovation and Cultural Heritage, pages 977-989, Springer.
    • Handle: RePEc:spr:prbchp:978-3-030-92491-1_58
    DOI: 10.1007/978-3-030-92491-1_58
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    More about this item

    Keywords

    Social media analytics; Spatial–temporal analysis; Cluster analysis; Flickr; OpenStreetMap;
    All these keywords.

    JEL classification:

    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models
    • C38 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Classification Methdos; Cluster Analysis; Principal Components; Factor Analysis
    • C55 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Large Data Sets: Modeling and Analysis
    • L83 - Industrial Organization - - Industry Studies: Services - - - Sports; Gambling; Restaurants; Recreation; Tourism
    • Z32 - Other Special Topics - - Tourism Economics - - - Tourism and Development

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