Abstract
How to keep customers’ loyalty and prevent customer churn is an important problem for airlines. Logistic regression model is a tool for prediction customer churn. This paper is to segment airline customers into four groups, set different churn rules to evaluate churn rate and analyze customer churn propensity based on logistic model. With the help of these strategies, the airlines can take positive and effective measures to reduce the company’s operating costs and enhance the company’s core competencies.
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Acknowledgments
The work is supported by Open Project Foundation of Information Technology Research Base of Civil Aviation Administration of China (No. CAAC-ITRB-201206).
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Hu, HY. (2019). Research on Customer Churn Prediction Using Logistic Regression Model. In: Xhafa, F., Patnaik, S., Tavana, M. (eds) Advances in Intelligent, Interactive Systems and Applications. IISA 2018. Advances in Intelligent Systems and Computing, vol 885. Springer, Cham. https://doi.org/10.1007/978-3-030-02804-6_46
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DOI: https://doi.org/10.1007/978-3-030-02804-6_46
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Online ISBN: 978-3-030-02804-6
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