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Switzerland? The Best Choice for Accommodation in Europe for Skiing in the 2023 Season

Author

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  • Radu Lixăndroiu

    (Department of Management and Economic Informatics, Transilvania University of Brasov, 500036 Brasov, Romania)

  • Dana Lupșa-Tătaru

    (Department of Management and Economic Informatics, Transilvania University of Brasov, 500036 Brasov, Romania)

Abstract

The study investigates the connections between tourists‘ hotel preferences and distance from resort expressed in meters, distance from ski lift expressed in meters, booking score, number of reviews, room type, feature of free cancellation, price expressed in Euro, type (private host/hotel), destination (ski-to-door access/travel sustainable property) from 10 highly appreciated European ski locations offered in from February 2023 by Booking, using a sustainable, electronic instrument for collecting and analyzing a large amount of data, Octoparse 8 and a multi-attribute decision model. Previous studies concerning tourist preferences and online behavior used traditional methods, such as questionnaires and surveys, being limited to a certain number of questions and respondents; thus, this study covers a research gap in the literature with regard to the use of a large amount of data, electronic instruments and multi-attribute models to rank the hotel locations, which derives from the difficulty in obtaining the necessary data to carry out an in-depth analysis. The results show that when selecting a hotel location from an exclusive ski resort, the tourists are interested in the number of reviews, the price and the distances from the resorts to the ski slopes, while the booking score is less important. This is translated into practical implications for marketers and hotel managers, presented at the end of the paper.

Suggested Citation

  • Radu Lixăndroiu & Dana Lupșa-Tătaru, 2023. "Switzerland? The Best Choice for Accommodation in Europe for Skiing in the 2023 Season," Sustainability, MDPI, vol. 15(5), pages 1-17, February.
  • Handle: RePEc:gam:jsusta:v:15:y:2023:i:5:p:4032-:d:1077253
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    References listed on IDEAS

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    1. Popovic, Gabrijela & Stanujkic, Dragisa & Brzakovic, Miodrag & Karabasevic, Darjan, 2019. "A multiple-criteria decision-making model for the selection of a hotel location," Land Use Policy, Elsevier, vol. 84(C), pages 49-58.
    2. Nanda Kumar & Izak Benbasat, 2006. "Research Note: The Influence of Recommendations and Consumer Reviews on Evaluations of Websites," Information Systems Research, INFORMS, vol. 17(4), pages 425-439, December.
    3. Nicolau, Juan L. & Masiero, Lorenzo, 2017. "Determinants of advanced booking," Annals of Tourism Research, Elsevier, vol. 67(C), pages 78-82.
    4. Kim, Dohee & Park, Byung-Jin (Robert), 2017. "The moderating role of context in the effects of choice attributes on hotel choice: A discrete choice experiment," Tourism Management, Elsevier, vol. 63(C), pages 439-451.
    5. Konu, Henna & Laukkanen, Tommi & Komppula, Raija, 2011. "Using ski destination choice criteria to segment Finnish ski resort customers," Tourism Management, Elsevier, vol. 32(5), pages 1096-1105.
    6. Sparks, Beverley A. & Browning, Victoria, 2011. "The impact of online reviews on hotel booking intentions and perception of trust," Tourism Management, Elsevier, vol. 32(6), pages 1310-1323.
    7. Alderighi, Marco & Nava, Consuelo R. & Calabrese, Matteo & Christille, Jean-Marc & Salvemini, Chiara B., 2022. "Consumer perception of price fairness and dynamic pricing: Evidence from Booking.com," Journal of Business Research, Elsevier, vol. 145(C), pages 769-783.
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