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An analysis of visitor behaviour using time blocks: A study of ski destinations in Greece

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  • Vassiliadis, Chris A.
  • Priporas, Constantinos-Vasilios
  • Andronikidis, Andreas

Abstract

This study presents a time-based analysis of activities undertaken by visitors to ski destinations. Only a few marketing studies have examined behaviour in tourism and leisure activities using an analysis based on time blocks. Data collection was undertaken by means of a diary-type semi-structured questionnaire which was administered in face to face interviews with visitors in thirteen ski centres in Greece. Through diary analysis, time periods were classified and used as a means of describing visitor flow and behaviour in various time blocks within a day. Expenditure patterns were identified in relation to specific time blocks relating to the consumption of preferred products and services. The average expenditure per visitor per day was €64.91. The study develops a Time Block Activity Matrix (TBAM), which is constructed using the dimensions of “participation intensity” and “benefit” to position visitor activities in the ski centres. The TBAM is proposed as a strategic tool for structuring decision making in tourism management. Implications for ski destinations are also discussed.

Suggested Citation

  • Vassiliadis, Chris A. & Priporas, Constantinos-Vasilios & Andronikidis, Andreas, 2013. "An analysis of visitor behaviour using time blocks: A study of ski destinations in Greece," Tourism Management, Elsevier, vol. 34(C), pages 61-70.
  • Handle: RePEc:eee:touman:v:34:y:2013:i:c:p:61-70
    DOI: 10.1016/j.tourman.2012.03.013
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    References listed on IDEAS

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    Cited by:

    1. Raun, Janika & Ahas, Rein & Tiru, Margus, 2016. "Measuring tourism destinations using mobile tracking data," Tourism Management, Elsevier, vol. 57(C), pages 202-212.
    2. Fotiadis, Anestis K., 2016. "Modifying and applying time and cost blocks: The case of E-Da theme park, Kaohsiung, Taiwan," Tourism Management, Elsevier, vol. 54(C), pages 34-42.
    3. Julio Vena-Oya & José-Alberto Castañeda-García & Miguel-à ngel Rodríguez-Molina, 2022. "Determinants of the Likelihood of Tourist Spending in Cultural Micro-Destinations: Type, Timing, and Distance of the Activity as Predictors," SAGE Open, , vol. 12(3), pages 21582440221, September.
    4. Fotiadis, Anestis & Williams, Russell Blair, 2017. "“TiCoSa” a 3d matrix conceptual model to investigate visitors’ perceptions in an athletic event," MPRA Paper 90638, University Library of Munich, Germany, revised 17 Apr 2017.
    5. Tomasz Korol & Anestis Fotiadis, 2016. "Applying Fuzzy Logic of Expert Knowledge for Accurate Predictive Algorithms of Customer Traffic Flows in Theme Parks," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 15(06), pages 1451-1468, November.
    6. Winitra Leelapattana & Shih-Yun Hsu & Weerapon Thongma & Chun Chen & Fu-Mei Chiang, 2019. "Understanding the Impact of Environmental Education on Tourists’ Future Visit Intentions to Leisure Farms in Mountain Regions," Sustainability, MDPI, vol. 11(6), pages 1-13, March.
    7. Teodoro Luque Martínez & Luis Doña Toledo & Nina Faraoni, 2019. "Auditing Marketing and the Use of Social Media at Ski Resorts," Sustainability, MDPI, vol. 11(10), pages 1-24, May.

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