How Tourist Group Books Hotels Meeting the Majority Affective Expectations: A Group Selection Frame with Kansei Text Mining and Consensus Coordinating

Jia-Li Chang (), Hui Li () and Jian Wu ()
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Jia-Li Chang: Nankai University
Hui Li: Nankai University
Jian Wu: Shanghai Maritime University

Group Decision and Negotiation, 2023, vol. 32, issue 2, No 4, 327-358

Abstract: Abstract The decision on which hotel to book is a high-cost process for individuals and even more for groups due to the information explosion on online travel agent platforms. To assist group selecting the optimal hotel that meets the majority affective expectations, this study proposes a group hotel selection frame for booking with Kansei text mining and consensus coordinating. Firstly, to quantify the tourists’ affective needs for hotels, a Kansei-related dictionary towards hotel domain is constructed by Kansei text mining. Secondly, the bilattice-based Kansei score of hotels is defined and measured to represent hotel affective information scientifically. Then, a group consensus model with minimum adjustment cost is introduced to coordinate consistency of individual preferences in a tourist group. Moreover, a group hotel ranking based on group affective preference is interactively generated to meet the group personalized demands. Finally, a case study on Trip.com is conducted to demonstrate the proposed method.

Keywords: Group hotel selection; Multi-criteria decision-making; Kansei text mining; Bilattice-based Kansei score; Minimum adjustment cost consensus (search for similar items in EconPapers)
Date: 2023
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DOI: 10.1007/s10726-022-09810-0

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