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Finding similar price preferences on tourism activities


  • 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)


This article builds on the double role of the effect of prices on the choice of tourism activities: not only is it the only component of a destination marketing strategy that represents income but also a determinant factor in tourist choice. On this account, identifying patterns of tourists with different degrees of sensitivities to prices would help them design an appropriate bundle of activities and have a clear definition of the segment the destination should try to attract. Accordingly, the objective of this paper is to find tourist segments from individual price sensitivities to activities. The results show that, although price has a dissuasive influence on the choice of activities it shows a differentiated effect; this heterogeneous responsiveness to price supports the use of this variable as a segmentation criterion. In the empirical application four segments are found with significantly different price sensitivities.

Suggested Citation

  • Lorenzo Masiero & Juan L. Nicolau, 2011. "Finding similar price preferences on tourism activities," Quaderni della facoltà di Scienze economiche dell'Università di Lugano 1102, USI Università della Svizzera italiana.
  • Handle: RePEc:lug:wpaper:1102

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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, vol. 10(12), pages 1-16, November.
    2. Paker, Neslihan & Vural, Ceren Altuntaş, 2016. "Customer segmentation for marinas: Evaluating marinas as destinations," Tourism Management, Elsevier, vol. 56(C), pages 156-171.
    3. Ayat Zaki Ahmed & Manuel Rodríguez-Díaz, 2020. "Analyzing the Online Reputation and Positioning of Airlines," Sustainability, MDPI, vol. 12(3), pages 1-27, February.
    4. Viglia, Giampaolo & Dolnicar, Sara, 2020. "A review of experiments in tourism and hospitality," Annals of Tourism Research, Elsevier, vol. 80(C).
    5. 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, vol. 9(3), pages 1-27, July.
    6. Shah, Mumtaz Hussain & Khan, Sajjad, 2017. "Factors Effecting Commercial Banks Profitability in Pakistan," MPRA Paper 82016, University Library of Munich, Germany.
    7. Angeloni, Silvia, 2016. "A tourist kit ‘made in Italy’: An ‘intelligent’ system for implementing new generation destination cards," Tourism Management, Elsevier, vol. 52(C), pages 187-209.
    8. Jun Lee & Jeong-Joon Kim, 2023. "A Study on Market Segmentation According to Wellness Tourism Motivation and Differences in Behavior between the Groups—Focusing on Satisfaction, Behavioral Intention, and Flow," IJERPH, MDPI, vol. 20(2), pages 1-22, January.
    9. Carlos Fernández-Hernández & Carmelo J. León & Jorge E. Araña & Flora Díaz-Pére, 2016. "Market segmentation, activities and environmental behaviour in rural tourism," Tourism Economics, , vol. 22(5), pages 1033-1054, October.
    10. Yang, Yang & Liu, Hongbo & Li, Xiang (Robert) & Harrill, Rich, 2018. "A shrinking world for tourists? Examining the changing role of distance factors in understanding destination choices," Journal of Business Research, Elsevier, vol. 92(C), pages 350-359.
    11. Weiwei Zhang & Lingling Jiang, 2021. "Effects of High-Speed Rail on Sustainable Development of Urban Tourism: Evidence from Discrete Choice Model of Chinese Tourists’ Preference for City Destinations," Sustainability, MDPI, vol. 13(19), pages 1-19, September.

    More about this item


    individual price sensitivity; tourism activities; tourist choice; segmentation strategy;
    All these keywords.

    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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