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Using User-Generated Content to Explore Hotel Service Quality Dimensions

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Book cover Exploring Services Science (IESS 2016)

Part of the book series: Lecture Notes in Business Information Processing ((LNBIP,volume 247))

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Abstract

A better evaluation and understanding of the client’s perception of the service provided by hotels is critical for hotel managers, especially in the “Travel 2.0” era, where tourists not only access but also actively review the service provided. This paper analyses data automatically collected from TripAdvisor reviews regarding 2 star and 5 star hotels in Porto. TripAdvisor user generated content is explored through text mining techniques with the purpose of creating word clouds, synthesizing and prioritizing the aspects of the service raised by customers. Furthermore, this content is analyzed using the SERVQUAL model to identify the service quality dimensions most valued by guests of the two types of hotels. The results of the preliminary study demonstrate that the methodology proposed allows us to identify service perceptions with reasonable effectiveness, highlighting the potential of the procedure to become a complementary tool for hotel management.

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Authors and Affiliations

  1. Faculdade de Engenharia da Universidade do Porto, Porto, Portugal

    Vera L. Miguéis & Henriqueta Nóvoa

Authors
  1. Vera L. Miguéis
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  2. Henriqueta Nóvoa
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Correspondence to Vera L. Miguéis .

Editor information

Editors and Affiliations

  1. Faculty of Automatic Control & Computers, University Politehnica of Bucharest, Bucharest, Romania

    Theodor Borangiu

  2. Faculty of Automatic Control & Computers, University Politehnica of Bucharest, Bucharest, Romania

    Monica Dragoicea

  3. Faculty of Engineering - FEUP, University of Porto, Porto, Portugal

    Henriqueta Nóvoa

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Miguéis, V.L., Nóvoa, H. (2016). Using User-Generated Content to Explore Hotel Service Quality Dimensions. In: Borangiu, T., Dragoicea, M., Nóvoa, H. (eds) Exploring Services Science. IESS 2016. Lecture Notes in Business Information Processing, vol 247. Springer, Cham. https://doi.org/10.1007/978-3-319-32689-4_12

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  • DOI: https://doi.org/10.1007/978-3-319-32689-4_12

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-32688-7

  • Online ISBN: 978-3-319-32689-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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