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Making sense of tourists' photographs using canonical variate analysis

Author

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  • Balomenou, Nika
  • Garrod, Brian
  • Georgiadou, Andri

Abstract

Tourists' photographs can serve as a rich database for researchers wishing to study tourists' perceptions and attitudes towards destinations. Such data can also be useful in examining how tourists behave, where, when, with whom and why. Many researchers favour the qualitative analysis of such data, which requires the use either of relatively small numbers of photographs or a considerable expense of researcher time and effort to undertake. Much of this process is speculative, in that it involves working with variables which may or may not prove to be significant in addressing the hypotheses chosen for the research. This paper recommends the use of a preliminary phase of research in which a quantitative approach is used to reduce the number of variables needing to be coded. Canonical variate analysis is suggested as an appropriate tool for achieving this. Case study results are presented to demonstrate the utility of this approach.

Suggested Citation

  • Balomenou, Nika & Garrod, Brian & Georgiadou, Andri, 2017. "Making sense of tourists' photographs using canonical variate analysis," Tourism Management, Elsevier, vol. 61(C), pages 173-179.
    • Handle: RePEc:eee:touman:v:61:y:2017:i:c:p:173-179
    DOI: 10.1016/j.tourman.2017.02.010
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    References listed on IDEAS

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    1. Pan, Steve & Lee, Jinsoo & Tsai, Henry, 2014. "Travel photos: Motivations, image dimensions, and affective qualities of places," Tourism Management, Elsevier, vol. 40(C), pages 59-69.
    2. Hosany, Sameer & Ekinci, Yuksel & Uysal, Muzaffer, 2006. "Destination image and destination personality: An application of branding theories to tourism places," Journal of Business Research, Elsevier, vol. 59(5), pages 638-642, May.
    3. Balomenou, Nika & Garrod, Brian, 2014. "Using volunteer-employed photography to inform tourism planning decisions: A study of St David's Peninsula, Wales," Tourism Management, Elsevier, vol. 44(C), pages 126-139.
    4. Kim, Hany & Stepchenkova, Svetlana, 2015. "Effect of tourist photographs on attitudes towards destination: Manifest and latent content," Tourism Management, Elsevier, vol. 49(C), pages 29-41.
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    Cited by:

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    2. Yu, Joanne & Egger, Roman, 2021. "Color and engagement in touristic Instagram pictures: A machine learning approach," Annals of Tourism Research, Elsevier, vol. 89(C).
    3. Giglio, Simona & Pantano, Eleonora & Bilotta, Eleonora & Melewar, T.C., 2020. "Branding luxury hotels: Evidence from the analysis of consumers’ “big” visual data on TripAdvisor," Journal of Business Research, Elsevier, vol. 119(C), pages 495-501.
    4. Palazzo, Maria & Vollero, Agostino & Vitale, Pierluigi & Siano, Alfonso, 2021. "Urban and rural destinations on Instagram: Exploring the influencers’ role in #sustainabletourism," Land Use Policy, Elsevier, vol. 100(C).
    5. Fangxuan (Sam) Li, 2020. "Chinese Tourists’ Barriers to Sharing Travel Photos in WeChat," Sustainability, MDPI, vol. 12(3), pages 1-13, January.

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