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Price sensitivity to tourism activities: looking for determinant factors

Author

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  • Lorenzo Masiero

    () (Institute for Economic Research (IRE), Faculty of Economics, University of Lugano, Switzerland)

  • Juan L. Nicolau

    () (Dpt. of Financial Economics, Accounting and Marketing, Faculty of Economics, University of Alicante, Spain)

Abstract

Literature shows evidence that there is a marked heterogeneity in price responses to tourism products, leading to a great variety of tourist sensitivities to price. It means that the role price plays is complex and, particularly challenging is that its effect is not unambiguous, thereby dismissing the idea that demand for tourism products and tourist activities is always that of ordinary goods. The objective of this article is to identify and explain, as a novelty for the tourism industry, price sensitivities to tourism activities -individual by individual-. The operative formalization follows a Mixed Logit Model to estimate the individual sensitivities to price and then, a regression analysis to detect their determinants. The empirical application finds that motivations -influenced by age- and length of stay -with a non-linear effect- are explanatory factors of the tourists' price sensitivity to activities.

Suggested Citation

  • Lorenzo Masiero & Juan L. Nicolau, 2011. "Price sensitivity to tourism activities: looking for determinant factors," Quaderni della facoltà di Scienze economiche dell'Università di Lugano 1101, USI Università della Svizzera italiana.
  • Handle: RePEc:lug:wpaper:1101
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    References listed on IDEAS

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    1. Eugeni Aguiló & Joaquín Alegre & Maria Sard, 2003. "Examining the Market Structure of the German and UK Tour Operating Industries through an Analysis of Package Holiday Prices," Tourism Economics, , vol. 9(3), pages 255-278, September.
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    Cited by:

    1. Manuel Rodríguez-Díaz & Rosa Rodríguez-Díaz & Ana Cristina Rodríguez-Voltes & Crina Isabel Rodríguez-Voltes, 2018. "Analysing the Relationship between Price and Online Reputation by Lodging Category," Sustainability, MDPI, Open Access Journal, vol. 10(12), pages 1-1, November.
    2. Adam Blake & Mondher Sahli & Neelu Seetaram, 2012. "Introduction," Tourism Economics, , vol. 18(6), pages 1155-1159, December.
    3. Manuel Rodríguez-Díaz & Crina Isabel Rodríguez-Voltes & Ana Cristina Rodríguez-Voltes, 2019. "Determining the Relationships between Price and Online Reputation in Lodgings," Administrative Sciences, MDPI, Open Access Journal, vol. 9(3), pages 1-1, July.
    4. Juan L. Nicolau & Lorenzo Masiero, 2013. "Relationship between Price Sensitivity and Expenditures in the Choice of Tourism Activities at the Destination," Tourism Economics, , vol. 19(1), pages 101-114, February.
    5. Taiga Saito & Akihiko Takahashi & Noriaki Koide & Yu Ichifuji, 2017. "Optimal overbooking strategy in online hotel booking systems¡ÊRevised as "Application of Online Booking Data to Hotel Revenue Management" in F-448¡Ë," CARF F-Series CARF-F-421, Center for Advanced Research in Finance, Faculty of Economics, The University of Tokyo.
    6. Emanuele Breda & Rita Cappariello & Valentina ROmano, "undated". "International tourism in Italy: recent trends, potential demand and a comparison with the main European competitors," Questioni di Economia e Finanza (Occasional Papers) 475, Bank of Italy, Economic Research and International Relations Area.
    7. Ferrer-Rosell, Berta & Martínez-Garcia, Esther & Coenders, Germà, 2014. "Package and no-frills air carriers as moderators of length of stay," Tourism Management, Elsevier, vol. 42(C), pages 114-122.
    8. Engelina du Plessis & Melville Saayman, 2018. "Aspects contributing to tourism price competitiveness of South Africa," Tourism Economics, , vol. 24(2), pages 146-156, March.

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    More about this item

    Keywords

    tourism activities; response to prices; market heterogeneity; tourist choice;

    JEL classification:

    • C25 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions; Probabilities
    • L83 - Industrial Organization - - Industry Studies: Services - - - Sports; Gambling; Restaurants; Recreation; Tourism

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