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An Auto-Coding Process for Testing the Cognitive-Affective and Conative Model of Destination Image

In: Information and Communication Technologies in Tourism 2015

Author

Listed:
  • Ainhoa Serna

    (Mondragon Unibertsitatea)

  • Elena Marchiori

    (UniversitÁ della Svizzera italiana (USI - University of Lugano))

  • Jon Kepa Gerrikagoitia

    (Competence Research Center in Tourism, CICtourGUNE)

  • Aurkene Alzua-Sorzabal

    (Competence Research Center in Tourism, CICtourGUNE)

  • Lorenzo Cantoni

    (UniversitÁ della Svizzera italiana (USI - University of Lugano))

Abstract

Current research on online contents analysis relies mainly on human coding procedures, and it is still under research the creation of automatic tools for content analysis in the eTourism domain. Thus, considering the current research gap in the field of automatic coding procedure for content analysis, this study aims at contributing to the auto-coding analysis of the three image components: the cognitive, the affective (feelings expressed), and conative ones (behavioral intentions towards a destination) which might be reported in the tourism-related online conversations. Hence, an ad-hoc software has been developed and tested for the auto-coding analysis of online conversations, together with a human-coding procedure used for coding unclassified entities. The image of the Basque Country has been used as case study and data have been collected from Minube, a popular travel experience community. Results of this study show that the proposed approach can be apt for the analysis of cognitive-affective and conative components of destination image, and in turn help destination managers in their web marketing strategies.

Suggested Citation

  • Ainhoa Serna & Elena Marchiori & Jon Kepa Gerrikagoitia & Aurkene Alzua-Sorzabal & Lorenzo Cantoni, 2015. "An Auto-Coding Process for Testing the Cognitive-Affective and Conative Model of Destination Image," Springer Books, in: Iis Tussyadiah & Alessandro Inversini (ed.), Information and Communication Technologies in Tourism 2015, edition 127, pages 111-123, Springer.
    • Handle: RePEc:spr:sprchp:978-3-319-14343-9_9
    DOI: 10.1007/978-3-319-14343-9_9
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    Citations

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    Cited by:

    1. Ainhoa Serna & Tomas Ruiz & Jon Kepa Gerrikagoitia & Rosa Arroyo, 2019. "Identification of Enablers and Barriers for Public Bike Share System Adoption using Social Media and Statistical Models," Sustainability, MDPI, vol. 11(22), pages 1-21, November.
    2. Mohammed Jabreel & Assumpció Huertas & Antonio Moreno, 2018. "Semantic analysis and the evolution towards participative branding: Do locals communicate the same destination brand values as DMOs?," PLOS ONE, Public Library of Science, vol. 13(11), pages 1-29, November.
    3. Estela Marine-Roig & Salvador Anton Clavé, 2016. "A detailed method for destination image analysis using user-generated content," Information Technology & Tourism, Springer, vol. 15(4), pages 341-364, January.

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