IDEAS home Printed from https://ideas.repec.org/a/sae/sagope/v14y2024i2p21582440241255827.html
   My bibliography  Save this article

Exploring Customers Experience and Satisfaction with Theme Hotels: A Cross-Cultural Analysis of Hotel Reviews

Author

Listed:
  • Xiaobin Zhang
  • Jun Yu
  • Hak-Seon Kim

Abstract

There is a generalized global market trend that tourists and consumers tend to pursue “themed†experiences closely related to their preferences or specific purposes. In the accommodation sector, the concept of “themed†is reflected by various theme hotels such as green hotels, family hotels, E-sports hotels, etc. In the era of Web 2.0, online information has been testified to be one of the most effective data sources for understanding customers and developing relative marketing strategies. Therefore, this research examined online customer reviews with both quantitative and qualitative methods to extract a range of variables reflecting customers’ experiences, and then, to explore their contribution to customers’ satisfaction/dissatisfaction with theme hotels; to understand theme hotels and develop novel insights for the industry, with new data sources. Moreover, a cross-cultural perspective was applied to examine the differences among different markets, so that more specific and targeted marketing strategies could be developed to develop and promote theme hotels. As a result, different clusters reflecting customers’ understanding of two areas have been applied. In addition, it was demonstrated that the connection between customer experience and satisfaction can be utilized to distinguish the differences between the two areas.

Suggested Citation

  • Xiaobin Zhang & Jun Yu & Hak-Seon Kim, 2024. "Exploring Customers Experience and Satisfaction with Theme Hotels: A Cross-Cultural Analysis of Hotel Reviews," SAGE Open, , vol. 14(2), pages 21582440241, May.
    • Handle: RePEc:sae:sagope:v:14:y:2024:i:2:p:21582440241255827
    DOI: 10.1177/21582440241255827
    as

    Download full text from publisher

    File URL: https://journals.sagepub.com/doi/10.1177/21582440241255827
    Download Restriction: no
    File URL: https://libkey.io/10.1177/21582440241255827?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
    ---><---

    References listed on IDEAS

    as
    1. Mariani, Marcello M. & Fosso Wamba, Samuel, 2020. "Exploring how consumer goods companies innovate in the digital age: The role of big data analytics companies," Journal of Business Research, Elsevier, vol. 121(C), pages 338-352.
    2. Narariya Dita Handani & Angellie Williady & Hak-Seon Kim, 2022. "An Analysis of Customer Textual Reviews and Satisfaction at Luxury Hotels in Singapore’s Marina Bay Area (SG-Clean-Certified Hotels)," Sustainability, MDPI, vol. 14(15), pages 1-16, July.
    3. Chen, Ching-Fu & Chen, Fu-Shian, 2010. "Experience quality, perceived value, satisfaction and behavioral intentions for heritage tourists," Tourism Management, Elsevier, vol. 31(1), pages 29-35.
    4. Osman M. Karatepe, 2011. "Service Quality, Customer Satisfaction and Loyalty: The Moderating Role of Gender," Journal of Business Economics and Management, Taylor & Francis Journals, vol. 12(2), pages 278-300, January.
    5. Xiang, Zheng & Du, Qianzhou & Ma, Yufeng & Fan, Weiguo, 2017. "A comparative analysis of major online review platforms: Implications for social media analytics in hospitality and tourism," Tourism Management, Elsevier, vol. 58(C), pages 51-65.
    6. Xiaobin Zhang & Hak-Seon Kim, 2021. "Customer Experience and Satisfaction of Disneyland Hotel through Big Data Analysis of Online Customer Reviews," Sustainability, MDPI, vol. 13(22), pages 1-17, November.
    7. Liu, Yong & Teichert, Thorsten & Rossi, Matti & Li, Hongxiu & Hu, Feng, 2017. "Big data for big insights: Investigating language-specific drivers of hotel satisfaction with 412,784 user-generated reviews," Tourism Management, Elsevier, vol. 59(C), pages 554-563.
    8. Henry Kaiser, 1974. "An index of factorial simplicity," Psychometrika, Springer;The Psychometric Society, vol. 39(1), pages 31-36, March.
    9. Guo, Yue & Barnes, Stuart J. & Jia, Qiong, 2017. "Mining meaning from online ratings and reviews: Tourist satisfaction analysis using latent dirichlet allocation," Tourism Management, Elsevier, vol. 59(C), pages 467-483.
    10. 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.
    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. Sunyoung Hlee & Hanna Lee & Chulmo Koo, 2018. "Hospitality and Tourism Online Review Research: A Systematic Analysis and Heuristic-Systematic Model," Sustainability, MDPI, vol. 10(4), pages 1-27, April.
    2. Woohyuk Kim & Sung-Bum Kim & Eunhye Park, 2021. "Mapping Tourists’ Destination (Dis)Satisfaction Attributes with User-Generated Content," Sustainability, MDPI, vol. 13(22), pages 1-16, November.
    3. Nguyen The Hien & Yen-Lun Su & Raksmey Sann & Le Thi Phuong Thanh, 2022. "Analysis of Online Customer Complaint Behavior in Vietnam’s Hotel Industry," Sustainability, MDPI, vol. 14(7), pages 1-15, March.
    4. Xiaobin Zhang & Hak-Seon Kim, 2021. "Customer Experience and Satisfaction of Disneyland Hotel through Big Data Analysis of Online Customer Reviews," Sustainability, MDPI, vol. 13(22), pages 1-17, November.
    5. Seungju Nam & Hyun Cheol Lee, 2019. "A Text Analytics-Based Importance Performance Analysis and Its Application to Airline Service," Sustainability, MDPI, vol. 11(21), pages 1-24, November.
    6. Carmela Iorio & Giuseppe Pandolfo & Antonio D’Ambrosio & Roberta Siciliano, 2020. "Mining big data in tourism," Quality & Quantity: International Journal of Methodology, Springer, vol. 54(5), pages 1655-1669, December.
    7. Jun Hwan Kim & Hyun Cheol Lee, 2019. "Understanding the Repurchase Intention of Premium Economy Passengers Using an Extended Theory of Planned Behavior," Sustainability, MDPI, vol. 11(11), pages 1-19, June.
    8. Boccali, Filippo & Mariani, Marcello M. & Visani, Franco & Mora-Cruz, Alexandra, 2022. "Innovative value-based price assessment in data-rich environments: Leveraging online review analytics through Data Envelopment Analysis to empower managers and entrepreneurs," Technological Forecasting and Social Change, Elsevier, vol. 182(C).
    9. Ahani, Ali & Nilashi, Mehrbakhsh & Yadegaridehkordi, Elaheh & Sanzogni, Louis & Tarik, A. Rashid & Knox, Kathy & Samad, Sarminah & Ibrahim, Othman, 2019. "Revealing customers’ satisfaction and preferences through online review analysis: The case of Canary Islands hotels," Journal of Retailing and Consumer Services, Elsevier, vol. 51(C), pages 331-343.
    10. 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.
    11. Gang Ren & Taeho Hong, 2017. "Investigating Online Destination Images Using a Topic-Based Sentiment Analysis Approach," Sustainability, MDPI, vol. 9(10), pages 1-18, September.
    12. Mariani, Marcello M. & Borghi, Matteo & Laker, Benjamin, 2023. "Do submission devices influence online review ratings differently across different types of platforms? A big data analysis," Technological Forecasting and Social Change, Elsevier, vol. 189(C).
    13. Mehrbakhsh Nilashi & Abbas Mardani & Huchang Liao & Hossein Ahmadi & Azizah Abdul Manaf & Wafa Almukadi, 2019. "A Hybrid Method with TOPSIS and Machine Learning Techniques for Sustainable Development of Green Hotels Considering Online Reviews," Sustainability, MDPI, vol. 11(21), pages 1-21, October.
    14. Kim, Taeyong & Hwang, Seungsoo & Kim, Minkyung, 2022. "Text analysis of online customer reviews for products in the FCB quadrants: Procedure, outcomes, and implications," Journal of Business Research, Elsevier, vol. 150(C), pages 676-689.
    15. Deborah Agostino & Marco Brambilla & Silvio Pavanetto & Paola Riva, 2021. "The Contribution of Online Reviews for Quality Evaluation of Cultural Tourism Offers: The Experience of Italian Museums," Sustainability, MDPI, vol. 13(23), pages 1-20, December.
    16. Lee, Chia-Chen & Wang, Stephen W. & Hsu, Maxwell K. & Jan, Shih-Ming, 2018. "Air passenger's perception toward pre-flight safety briefing videos: Does it matter?," Journal of Air Transport Management, Elsevier, vol. 72(C), pages 20-31.
    17. Samuel Bates, 2021. "A Glance at Tourism Economics over the last decade [Coup d'œil sur l'Économie du Tourisme de la dernière décennie]," Post-Print hal-03263048, HAL.
    18. Clérito Kaveski Peres & Edson Pacheco Paladini, 2022. "Quality Attributes of Hotel Services in Brazil and the Impacts of COVID-19 on Users’ Perception," Sustainability, MDPI, vol. 14(6), pages 1-15, March.
    19. Kolomoyets, Yuliya & Dickinger, Astrid, 2023. "Understanding value perceptions and propositions: A machine learning approach," Journal of Business Research, Elsevier, vol. 154(C).
    20. Jimenez-Marquez, Jose Luis & Gonzalez-Carrasco, Israel & Lopez-Cuadrado, Jose Luis & Ruiz-Mezcua, Belen, 2019. "Towards a big data framework for analyzing social media content," International Journal of Information Management, Elsevier, vol. 44(C), pages 1-12.

    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:sae:sagope:v:14:y:2024:i:2:p:21582440241255827. 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: SAGE Publications (email available below). General contact details of provider: .

    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.