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An observational user study for group recommender systems in the tourism domain

Author

Listed:
  • Amra Delic

    (TU Wien)

  • Julia Neidhardt

    (TU Wien)

  • Thuy Ngoc Nguyen

    (Free University of Bozen-Bolzano)

  • Francesco Ricci

    (Free University of Bozen-Bolzano)

Abstract

In this article we argue and give evidence that the research on group recommender systems must look more carefully at the dynamics of group decision-making in order to produce technologies that will be truly beneficial for groups. We illustrate the adopted research method and the results of a user study aimed at observing and measuring the evolution of user preferences and interaction in a tourism decision-making task: finding a destination to visit together as a group. We discuss the benefits and caveats of such an observational study method and we present the implications that the derived data and findings have on the design of interactive group recommender systems.

Suggested Citation

  • Amra Delic & Julia Neidhardt & Thuy Ngoc Nguyen & Francesco Ricci, 2018. "An observational user study for group recommender systems in the tourism domain," Information Technology & Tourism, Springer, vol. 19(1), pages 87-116, June.
    • Handle: RePEc:spr:infott:v:19:y:2018:i:1:d:10.1007_s40558-018-0106-y
    DOI: 10.1007/s40558-018-0106-y
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    Cited by:

    1. Rakhi Saxena & Sharanjit Kaur & Harita Ahuja & Sunita Narang, 2024. "Leveraging item attribute popularity for group recommendation," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 15(6), pages 2645-2655, June.

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