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Dimensions of lodging guest satisfaction among guests with mobility challenges: A mixed-method analysis of web-based texts


  • Zhang, Ye
  • Cole, Shu Tian


Given that many lodging businesses cannot afford to provide satisfactory services to people with mobility challenges, this study recommends a strategic order of service attribute development to maximize customer satisfaction with minimal costs. The crucial lodging service attributes of this population are identified and distinguished by degrees of influence on customer satisfaction based on the analyses of 543 web travel reviews. The results suggests prioritizing the bottom-line delivery of basic and performance factors (i.e. room access and staff attitude capability), whereas optionally offering the delivery of excitement factors or above-and-beyond delivery of performance factors, such as luggage and equipment support and general lodging features. Being the first attempt to integrate quantitative and qualitative web content analysis with Penalty-Reward Contrast Analysis, this study captures the real-life tourist service evaluation criteria with improved accuracy and reliability. It also enables a thorough and efficient exploitation of customer-generated web textual data.

Suggested Citation

  • Zhang, Ye & Cole, Shu Tian, 2016. "Dimensions of lodging guest satisfaction among guests with mobility challenges: A mixed-method analysis of web-based texts," Tourism Management, Elsevier, vol. 53(C), pages 13-27.
  • Handle: RePEc:eee:touman:v:53:y:2016:i:c:p:13-27
    DOI: 10.1016/j.tourman.2015.09.001

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    References listed on IDEAS

    1. Stepchenkova, Svetlana & Zhan, Fangzi, 2013. "Visual destination images of Peru: Comparative content analysis of DMO and user-generated photography," Tourism Management, Elsevier, vol. 36(C), pages 590-601.
    2. Wei-Jaw Deng & Ying-Feng Kuo & Wen-Chin Chen, 2008. "Revised importance--performance analysis: three-factor theory and benchmarking," The Service Industries Journal, Taylor & Francis Journals, vol. 28(1), pages 37-51, January.
    3. Metz, D. H., 2000. "Mobility of older people and their quality of life," Transport Policy, Elsevier, vol. 7(2), pages 149-152, April.
    4. Capriello, Antonella & Mason, Peyton R. & Davis, Boyd & Crotts, John C., 2013. "Farm tourism experiences in travel reviews: A cross-comparison of three alternative methods for data analysis," Journal of Business Research, Elsevier, vol. 66(6), pages 778-785.
    5. Xiang, Zheng & Gretzel, Ulrike, 2010. "Role of social media in online travel information search," Tourism Management, Elsevier, vol. 31(2), pages 179-188.
    6. Darcy, Simon, 2010. "Inherent complexity: Disability, accessible tourism and accommodation information preferences," Tourism Management, Elsevier, vol. 31(6), pages 816-826.
    7. Lu, Weilin & Stepchenkova, Svetlana, 2012. "Ecotourism experiences reported online: Classification of satisfaction attributes," Tourism Management, Elsevier, vol. 33(3), pages 702-712.
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    Cited by:

    1. Hyun-Jeong Ban & Hak-Seon Kim, 2019. "Understanding Customer Experience and Satisfaction through Airline Passengers’ Online Review," Sustainability, MDPI, Open Access Journal, vol. 11(15), pages 1-17, July.
    2. 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.
    3. Huseyin Arasli & Mehmet Bahri Saydam & Hasan Kilic, 2020. "Cruise Travelers’ Service Perceptions: A Critical Content Analysis," Sustainability, MDPI, Open Access Journal, vol. 12(17), pages 1-13, August.
    4. Rosa Maria Fanelli & Luca Romagnoli, 2020. "Customer Satisfaction with Farmhouse Facilities and Its Implications for the Promotion of Agritourism Resources in Italian Municipalities," Sustainability, MDPI, Open Access Journal, vol. 12(5), pages 1-21, February.
    5. Alaa Shoukry & Fares Aldeek, 2020. "Attributes prediction from IoT consumer reviews in the hotel sectors using conventional neural network: deep learning techniques," Electronic Commerce Research, Springer, vol. 20(2), pages 223-240, June.
    6. Sainaghi, Ruggero & Phillips, Paul & Zavarrone, Emma, 2017. "Performance measurement in tourism firms: A content analytical meta-approach," Tourism Management, Elsevier, vol. 59(C), pages 36-56.


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