IDEAS home Printed from https://ideas.repec.org/a/bjf/journl/v10y2025i10p1401-1408.html

Improving Customer Retention in Nigeria's Aviation Industry: A Machine Learning Perspective

Author

Listed:
  • Cosmas Akanna Ogbobe

    (University of East London)

  • Ezema Miracle Chikamso

    (Babcock University)

  • Olakunmi Olayinka Odumosu

    (National Open University)

Abstract

Nigeria's aviation sector faces intense competition, rising operational costs, and volatile passenger loyalty. This study employs a Random Forest classifier to predict passenger churn using anonymized flight data, developing a model that achieves high precision in identifying at-risk passengers. Key predictors include delayed flight duration, customer service interactions, and travel class. The results inform targeted retention strategies, such as predictive dashboards and loyalty programs, offering actionable insights for airline operations and revenue protection.

Suggested Citation

  • Cosmas Akanna Ogbobe & Ezema Miracle Chikamso & Olakunmi Olayinka Odumosu, 2025. "Improving Customer Retention in Nigeria's Aviation Industry: A Machine Learning Perspective," International Journal of Research and Innovation in Applied Science, International Journal of Research and Innovation in Applied Science (IJRIAS), vol. 10(10), pages 1401-1408, October.
    • Handle: RePEc:bjf:journl:v:10:y:2025:i:10:p:1401-1408
    as

    Download full text from publisher

    File URL: https://www.rsisinternational.org/journals/ijrias/uploads/vol10-iss10-pg1401-1408-202511_pdf.pdf
    Download Restriction: no
    File URL: https://www.rsisinternational.org/journals/ijrias/view/improving-customer-retention-in-nigerias-aviation-industry-a-machine-learning-perspective/
    Download Restriction: no
    ---><---

    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:bjf:journl:v:10:y:2025:i:10:p:1401-1408. 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: Dr. Renu Malsaria (email available below). General contact details of provider: https://rsisinternational.org/journals/ijrias/ .

    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.