IDEAS home Printed from https://ideas.repec.org/a/spr/grdene/v32y2023i2d10.1007_s10726-022-09810-0.html
   My bibliography  Save this article

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

Author

Listed:
  • Jia-Li Chang

    (Nankai University)

  • Hui Li

    (Nankai University)

  • Jian Wu

    (Shanghai Maritime University)

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.

Suggested Citation

  • Jia-Li Chang & Hui Li & Jian Wu, 2023. "How Tourist Group Books Hotels Meeting the Majority Affective Expectations: A Group Selection Frame with Kansei Text Mining and Consensus Coordinating," Group Decision and Negotiation, Springer, vol. 32(2), pages 327-358, April.
    • Handle: RePEc:spr:grdene:v:32:y:2023:i:2:d:10.1007_s10726-022-09810-0
    DOI: 10.1007/s10726-022-09810-0
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10726-022-09810-0
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s10726-022-09810-0?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Jian Jin & Danping Jia & Kejia Chen, 2022. "Mining online reviews with a Kansei-integrated Kano model for innovative product design," International Journal of Production Research, Taylor & Francis Journals, vol. 60(22), pages 6708-6727, November.
    2. Si Liu & David Ríos Insua, 2020. "Group Decision Making with Affective Features," Group Decision and Negotiation, Springer, vol. 29(5), pages 843-869, October.
    3. Jian-Wu Bi & Yang Liu & Zhi-Ping Fan & Erik Cambria, 2019. "Modelling customer satisfaction from online reviews using ensemble neural network and effect-based Kano model," International Journal of Production Research, Taylor & Francis Journals, vol. 57(22), pages 7068-7088, November.
    4. Dong, Yucheng & Xu, Yinfeng & Li, Hongyi & Feng, Bo, 2010. "The OWA-based consensus operator under linguistic representation models using position indexes," European Journal of Operational Research, Elsevier, vol. 203(2), pages 455-463, June.
    5. Hong-Bin Yan & Ming Li, 2021. "An uncertain Kansei Engineering methodology for behavioral service design," IISE Transactions, Taylor & Francis Journals, vol. 53(5), pages 497-522, May.
    6. Xiao-kang Wang & Sheng-hui Wang & Hong-yu Zhang & Jian-qiang Wang & Lin Li, 2021. "The Recommendation Method for Hotel Selection Under Traveller Preference Characteristics: A Cloud-Based Multi-Criteria Group Decision Support Model," Group Decision and Negotiation, Springer, vol. 30(6), pages 1433-1469, December.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Wang, Binni & Wang, Pong & Tu, Yiliu, 2021. "Customer satisfaction service match and service quality-based blockchain cloud manufacturing," International Journal of Production Economics, Elsevier, vol. 240(C).
    2. Fu, Chao & Yang, Shanlin, 2012. "An evidential reasoning based consensus model for multiple attribute group decision analysis problems with interval-valued group consensus requirements," European Journal of Operational Research, Elsevier, vol. 223(1), pages 167-176.
    3. Wu, Zhibin & Huang, Shuai & Xu, Jiuping, 2019. "Multi-stage optimization models for individual consistency and group consensus with preference relations," European Journal of Operational Research, Elsevier, vol. 275(1), pages 182-194.
    4. Zhang, Hengjie & Dong, Yucheng & Chiclana, Francisco & Yu, Shui, 2019. "Consensus efficiency in group decision making: A comprehensive comparative study and its optimal design," European Journal of Operational Research, Elsevier, vol. 275(2), pages 580-598.
    5. Lionel Nicod & Élodie Mallor & Sylvie Llosa, 2023. "L’influence de l’aide à participer en magasin sur la satisfaction client : une approche par le modèle tétraclasse," Post-Print hal-04311121, HAL.
    6. Wen-Kuo Chen & Dalianus Riantama & Long-Sheng Chen, 2020. "Using a Text Mining Approach to Hear Voices of Customers from Social Media toward the Fast-Food Restaurant Industry," Sustainability, MDPI, vol. 13(1), pages 1-17, December.
    7. Junegak Joung & Ki-Hun Kim & Kwangsoo Kim, 2021. "Data-Driven Approach to Dual Service Failure Monitoring From Negative Online Reviews: Managerial Perspective," SAGE Open, , vol. 11(1), pages 21582440209, January.
    8. Qiuying Chen & Shangyue Xu & Ronghui Liu & Qingquan Jiang, 2023. "Exploring the Discrepancy between Projected and Perceived Destination Images: A Cross-Cultural and Sustainable Analysis Using LDA Modeling," Sustainability, MDPI, vol. 15(12), pages 1-31, June.
    9. He-Wei Liu & Yi-Ting Wang & Xiao-Kang Wang & Ye Liu & Yan Liu & Xue-Yang Zhang & Fei Xiao, 2023. "Cloud Model-Based Fuzzy Inference System for Short-Term Traffic Flow Prediction," Mathematics, MDPI, vol. 11(11), pages 1-17, May.
    10. Wu, Xingli & Liao, Huchang, 2019. "A consensus-based probabilistic linguistic gained and lost dominance score method," European Journal of Operational Research, Elsevier, vol. 272(3), pages 1017-1027.
    11. Zibarzani, Masoumeh & Abumalloh, Rabab Ali & Nilashi, Mehrbakhsh & Samad, Sarminah & Alghamdi, O.A. & Nayer, Fatima Khan & Ismail, Muhammed Yousoof & Mohd, Saidatulakmal & Mohammed Akib, Noor Adelyna, 2022. "Customer satisfaction with Restaurants Service Quality during COVID-19 outbreak: A two-stage methodology," Technology in Society, Elsevier, vol. 70(C).
    12. Xuyuan Zhang & Hailin Liang & Shaojian Qu, 2024. "Robust Consensus Modeling: Concerning Consensus Fairness and Efficiency with Uncertain Costs," Mathematics, MDPI, vol. 12(8), pages 1-31, April.
    13. Sun, Bingzhen & Ma, Weimin, 2015. "An approach to consensus measurement of linguistic preference relations in multi-attribute group decision making and application," Omega, Elsevier, vol. 51(C), pages 83-92.
    14. Weijun Xu & Xin Chen & Yucheng Dong & Francisco Chiclana, 2021. "Impact of Decision Rules and Non-cooperative Behaviors on Minimum Consensus Cost in Group Decision Making," Group Decision and Negotiation, Springer, vol. 30(6), pages 1239-1260, December.
    15. Yazidi, Anis & Ivanovska, Magdalena & Zennaro, Fabio M. & Lind, Pedro G. & Viedma, Enrique Herrera, 2022. "A new decision making model based on Rank Centrality for GDM with fuzzy preference relations," European Journal of Operational Research, Elsevier, vol. 297(3), pages 1030-1041.
    16. Wu, Jie & Zhao, Narisa & Yang, Tong, 2024. "Wisdom of crowds: SWOT analysis based on hybrid text mining methods using online reviews," Journal of Business Research, Elsevier, vol. 171(C).
    17. Bowen Zhang & Yucheng Dong & Enrique Herrera-Viedma, 2019. "Group Decision Making with Heterogeneous Preference Structures: An Automatic Mechanism to Support Consensus Reaching," Group Decision and Negotiation, Springer, vol. 28(3), pages 585-617, June.
    18. Cheng, Dong & Yuan, Yuxiang & Wu, Yong & Hao, Tiantian & Cheng, Faxin, 2022. "Maximum satisfaction consensus with budget constraints considering individual tolerance and compromise limit behaviors," European Journal of Operational Research, Elsevier, vol. 297(1), pages 221-238.
    19. Mingwei Wang & Decui Liang & Zeshui Xu & Wen Cao, 2022. "Consensus reaching with the externality effect of social network for three-way group decisions," Annals of Operations Research, Springer, vol. 315(2), pages 707-745, August.
    20. Weiwen Li & Yijiang Zhou & Xingan Dai & Fang Hu, 2022. "Evaluation of Rural Tourism Landscape Resources in Terms of Carbon Neutrality and Rural Revitalization," Sustainability, MDPI, vol. 14(5), pages 1-22, March.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:grdene:v:32:y:2023:i:2:d:10.1007_s10726-022-09810-0. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.