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Estimating a latent-class user model for travel recommender systems

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  • Theo Arentze

    (Eindhoven University of Technology)

  • Astrid Kemperman

    (Eindhoven University of Technology)

  • Petr Aksenov

    (Eindhoven University of Technology)

Abstract

In determining the selection of sites to visit on a trip tourists have to trade-off attraction values against routing and time-use characteristics of points of interest (POIs). For recommending optimal personalized travel plans an accurate assessment of how users make these trade-offs is important. In this paper we report the results of a study conducted to estimate a user model for travel recommender systems. The proposed model is part of c-Space—a tour-recommender system for tourists on a city trip which uses the LATUS algorithm to find personalized optimal tours. The model takes into account a multi-attribute utility function of POIs as well as dynamic needs of persons on a trip. A stated choice experiment is designed where the current need is manipulated as a context variable and activity choice alternatives are varied. A random sample of 316 individuals participated in the on-line survey. A latent-class analysis shows that significant differences exist between tourists in terms of how they make the trade-offs between the factors and respond to needs. The estimation results provide the parameters of a multi-class user model that can be used for travel recommender systems.

Suggested Citation

  • Theo Arentze & Astrid Kemperman & Petr Aksenov, 2018. "Estimating a latent-class user model for travel recommender systems," Information Technology & Tourism, Springer, vol. 19(1), pages 61-82, June.
    • Handle: RePEc:spr:infott:v:19:y:2018:i:1:d:10.1007_s40558-018-0105-z
    DOI: 10.1007/s40558-018-0105-z
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    References listed on IDEAS

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    1. Armbrecht, John, 2014. "Use value of cultural experiences: A comparison of contingent valuation and travel cost," Tourism Management, Elsevier, vol. 42(C), pages 141-148.
    2. Yeh, Duen-Yian & Cheng, Ching-Hsue, 2015. "Recommendation system for popular tourist attractions in Taiwan using Delphi panel and repertory grid techniques," Tourism Management, Elsevier, vol. 46(C), pages 164-176.
    3. William Greene, 2001. "Fixed and Random Effects in Nonlinear Models," Working Papers 01-01, New York University, Leonard N. Stern School of Business, Department of Economics.
    4. Ashworth, Gregory & Page, Stephen J., 2011. "Urban tourism research: Recent progress and current paradoxes," Tourism Management, Elsevier, vol. 32(1), pages 1-15.
    5. Arentze, Theo A. & Timmermans, Harry J.P., 2009. "A need-based model of multi-day, multi-person activity generation," Transportation Research Part B: Methodological, Elsevier, vol. 43(2), pages 251-265, February.
    6. Matthias Braunhofer & Francesco Ricci, 2017. "Selective contextual information acquisition in travel recommender systems," Information Technology & Tourism, Springer, vol. 17(1), pages 5-29, March.
    7. Fernando A. Mikic Fonte & Marta Rey López & Juan C. Burguillo & Ana Peleteiro & Ana B. Barragáns Martínez, 2013. "A Tagging Recommender Service for Mobile Terminals," Springer Books, in: Lorenzo Cantoni & Zheng (Phil) Xiang (ed.), Information and Communication Technologies in Tourism 2013, edition 127, pages 424-435, Springer.
    8. Wynen, Jan, 2013. "Explaining travel distance during same-day visits," Tourism Management, Elsevier, vol. 36(C), pages 133-140.
    9. Lin, Yeqiang & Kerstetter, Deborah & Nawijn, Jeroen & Mitas, Ondrej, 2014. "Changes in emotions and their interactions with personality in a vacation context," Tourism Management, Elsevier, vol. 40(C), pages 416-424.
    10. Matthias Braunhofer & Mehdi Elahi & Francesco Ricci, 2015. "User Personality and the New User Problem in a Context-Aware Point of Interest Recommender System," Springer Books, in: Iis Tussyadiah & Alessandro Inversini (ed.), Information and Communication Technologies in Tourism 2015, edition 127, pages 537-549, Springer.
    11. Matthias Braunhofer & Francesco Ricci, 0. "Selective contextual information acquisition in travel recommender systems," Information Technology & Tourism, Springer, vol. 0, pages 1-25.
    12. Hensher,David A. & Rose,John M. & Greene,William H., 2015. "Applied Choice Analysis," Cambridge Books, Cambridge University Press, number 9781107465923, January.
    13. Peter Boxall & Wiktor Adamowicz, 2002. "Understanding Heterogeneous Preferences in Random Utility Models: A Latent Class Approach," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 23(4), pages 421-446, December.
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    Cited by:

    1. Kemperman, Astrid, 2021. "A review of research into discrete choice experiments in tourism: Launching the Annals of Tourism Research Curated Collection on Discrete Choice Experiments in Tourism," Annals of Tourism Research, Elsevier, vol. 87(C).

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