IDEAS home Printed from https://ideas.repec.org/h/spr/sprchp/978-981-95-3210-0_7.html

Unpacking Machine Learning as an Organizational Resilience Strategy in the Tourism and Hospitality Sector

In: Resilience in the Hospitality and Travel Industry in Africa

Author

Listed:
  • Mufaro Dzingirai

    (Namibia University of Science and Technology, Harold Pupkewitz Graduate School of Business)

Abstract

This chapter aims to assess the role of machine learning in fostering organizational resilience in the tourism and hospitality sector. It is common knowledge that machine learning radically transformed the operations of tourism and hospitality companies that have a high affinity for advanced technology adoption. Nonetheless, scholarly attention is very scant when it comes to the nexus between machine learning and organizational resilience in the tourism and hospitality sector in the post-COVID-19 epoch. A systematic literature review methodology was adopted whereby data was extracted from secondary sources. In this sense, databases like Google Scholar, Scopus, and other institutional sources were employed. Thematic analysis was used to synthesize the collected data according to emerging patterns. This study adds value to the corpus of the extant knowledge base as it established that machine learning can ensure organizational resilience through enhancement of target marketing, provision of real-time data, payment, and ticket fraud detection, automation of customer service, trend analysis, and pattern recognition, enhancement of tourist experiences, efficient allocation of resources, and personalized recommendation systems. The results of this study add value to policymaking and practice.

Suggested Citation

  • Mufaro Dzingirai, 2026. "Unpacking Machine Learning as an Organizational Resilience Strategy in the Tourism and Hospitality Sector," Springer Books, in: Peter Chihwai (ed.), Resilience in the Hospitality and Travel Industry in Africa, chapter 0, pages 111-124, Springer.
    • Handle: RePEc:spr:sprchp:978-981-95-3210-0_7
    DOI: 10.1007/978-981-95-3210-0_7
    as

    Download full text from publisher

    To our knowledge, this item is not available for download. To find whether it is available, there are three options:
    1. Check below whether another version of this item is available online.
    2. Check on the provider's web page whether it is in fact available.
    3. Perform a
    for a similarly titled item that would be available.

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;

    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:spr:sprchp:978-981-95-3210-0_7. 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: 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.