IDEAS home Printed from https://ideas.repec.org/a/igg/jwsr00/v16y2019i4p21-39.html
   My bibliography  Save this article

Understanding the Determinants of Consumer Satisfaction With B&B Hotels: An Interpretive Structural Modeling Approach

Author

Listed:
  • Lin Xiao

    (School of Management, Fudan University, Shanghai, China)

  • Chuanmin Mi

    (College of Economics and Management, Nanjing University of Aeronautics and Astronautics, Nanjing, China)

  • Yetian Chen

    (College of Economics and Management, Nanjing University of Aeronautics and Astronautics, Nanjing, China)

  • Lihua Huang

    (School of Management, Fudan University, Shanghai, China)

Abstract

This study aims to understand the determinants of consumer satisfaction with bed-and-breakfast establishments (B&Bs) and build a hierarchical structure of these determinants. Content analysis was conducted based on the consumer online review data. Ten determinants of customer satisfaction were identified. The interpretive structural modeling (ISM) technique was then used to develop a five-level hierarchical structural model based on these determinants. Finally, the cross-impact matrix multiplication applied to the classification (MICMAC) technique was used to analyze the driver and dependence power for each determinant. This study has the potential to make significant contributions from both the theoretical and practical perspectives.

Suggested Citation

  • Lin Xiao & Chuanmin Mi & Yetian Chen & Lihua Huang, 2019. "Understanding the Determinants of Consumer Satisfaction With B&B Hotels: An Interpretive Structural Modeling Approach," International Journal of Web Services Research (IJWSR), IGI Global, vol. 16(4), pages 21-39, October.
  • Handle: RePEc:igg:jwsr00:v:16:y:2019:i:4:p:21-39
    as

    Download full text from publisher

    File URL: http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/IJWSR.2019100102
    Download Restriction: no
    ---><---

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Yan Hong & Gangwei Cai & Zhoujin Mo & Weijun Gao & Lei Xu & Yuanxing Jiang & Jinming Jiang, 2020. "The Impact of COVID-19 on Tourist Satisfaction with B&B in Zhejiang, China: An Importance–Performance Analysis," IJERPH, MDPI, vol. 17(10), pages 1-19, May.
    2. Malek Bader & Ramzi Al Rousan & Nermin Khasawneh & Mohammed Niyas KK, 2023. "Post-covid Tourist Satisfaction in the Hospitality industry: Reflections from Jordan," Technium Social Sciences Journal, Technium Science, vol. 42(1), pages 155-169, April.

    More about this item

    Statistics

    Access and download statistics

    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:igg:jwsr00:v:16:y:2019:i:4:p:21-39. 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.

    We have no bibliographic references for this item. You can help adding them by using 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: Journal Editor (email available below). General contact details of provider: https://www.igi-global.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.