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A variant bagging forecasting framework for customer churn in airline

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  • Li, Qiang
  • Li, Yuangang
  • Jing, Ranzhe

Abstract

The goal of this study is to forecast customer churn and analyze the influence of quality of service on customer churn in airline industry. Following a multifactor approach, a variant Bagging forecasting framework is proposed to mine the inner patterns of customer churn. A probabilistic sampling approach is embedded in the developed model simulating the customer churn probabilities. The airline customer feedback data by airline carriers in the U.S. was used to train the prediction model. The results indicate the accuracy for predicting customer churn is 96Â %, and the most important factors for customer churn are in-flight entertainment, seat comfort, and type of travel. We also investigated the effects of service quality (both hedonistic and utilitarian factors) on various customer groups and discovered that improving hedonistic service quality can effectively reduce customer churn.

Suggested Citation

  • Li, Qiang & Li, Yuangang & Jing, Ranzhe, 2025. "A variant bagging forecasting framework for customer churn in airline," Journal of Air Transport Management, Elsevier, vol. 125(C).
    • Handle: RePEc:eee:jaitra:v:125:y:2025:i:c:s0969699725000584
    DOI: 10.1016/j.jairtraman.2025.102795
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    References listed on IDEAS

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    1. Forgas, Santiago & Moliner, Miguel A. & Sánchez, Javier & Palau, Ramon, 2010. "Antecedents of airline passenger loyalty: Low-cost versus traditional airlines," Journal of Air Transport Management, Elsevier, vol. 16(4), pages 229-233.
    2. Wagner Kamakura & Carl Mela & Asim Ansari & Anand Bodapati & Pete Fader & Raghuram Iyengar & Prasad Naik & Scott Neslin & Baohong Sun & Peter Verhoef & Michel Wedel & Ron Wilcox, 2005. "Choice Models and Customer Relationship Management," Marketing Letters, Springer, vol. 16(3), pages 279-291, December.
    3. De Caigny, Arno & Coussement, Kristof & De Bock, Koen W. & Lessmann, Stefan, 2020. "Incorporating textual information in customer churn prediction models based on a convolutional neural network," International Journal of Forecasting, Elsevier, vol. 36(4), pages 1563-1578.
    4. Hussain, Rahim & Al Nasser, Amjad & Hussain, Yomna K., 2015. "Service quality and customer satisfaction of a UAE-based airline: An empirical investigation," Journal of Air Transport Management, Elsevier, vol. 42(C), pages 167-175.
    5. Calisir, Nese & Basak, Ecem & Calisir, Fethi, 2016. "Key drivers of passenger loyalty: A case of Frankfurt–Istanbul flights," Journal of Air Transport Management, Elsevier, vol. 53(C), pages 211-217.
    6. Myungsook An & Yonghwi Noh, 2009. "Airline customer satisfaction and loyalty: impact of in-flight service quality," Service Business, Springer;Pan-Pacific Business Association, vol. 3(3), pages 293-307, September.
    7. Athanassopoulos, Antreas D., 2000. "Customer Satisfaction Cues To Support Market Segmentation and Explain Switching Behavior," Journal of Business Research, Elsevier, vol. 47(3), pages 191-207, March.
    Full references (including those not matched with items on IDEAS)

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