PREDICTING CUSTOMER LOYALTY IN AUTOMOTIVE SERVICES: EVIDENCE FROM MACHINE LEARNING ON SATISFACTION AND SERVICE COSTS IN NIGERIA

Authors

  • Godspower Onyekachukwu Ekwueme Department of Industrial Production Engineering, Nnamdi Azikiwe University, Awka, Anambra State, Nigeria
  • Harold Chukwuemeka Godwin Department of Industrial Production Engineering, Nnamdi Azikiwe University, Awka, Anambra State, Nigeria
  • Chukwu Callistus Nkemjika Department of Industrial Production Engineering, Nnamdi Azikiwe University, Awka, Anambra State, Nigeria
  • Chukwunedum Ogochukwu Chinedum Department of Industrial Production Engineering, Nnamdi Azikiwe University, Awka, Anambra State, Nigeria

Keywords:

Customer Loyalty, Machine Learning, Automotive Services, XGBoost, Customer Satisfaction.

Abstract

Customer loyalty in Nigeria’s automotive service sector has become volatile due to digital competition, variable pricing, and shifting satisfaction patterns. Traditional regression models fail to capture the nonlinear links between satisfaction, cost, and loyalty. This study used machine learning algorithms: Random Forest (RF), Support Vector Machine (SVM), and Extreme Gradient Boosting (XGBoost), to predict loyalty using customer satisfaction, service cost, and behavioral indicators from Anaval Mechanic Workshop (January–December 2023). Model performance was evaluated using accuracy and Area Under the Curve (AUC). XGBoost performed best (AUC = 0.985; accuracy = 97.1%), followed by RF (AUC = 0.962) and SVM (AUC = 0.485). Findings confirm satisfaction, cost, and uncertainty as key loyalty drivers, highlighting XGBoost’s superiority in modeling complex satisfaction–cost dynamics

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Published

2025-10-15

How to Cite

Onyekachukwu Ekwueme, G., Chukwuemeka Godwin, H., Chukwu Callistus Nkemjika, & Ogochukwu Chinedum, C. (2025). PREDICTING CUSTOMER LOYALTY IN AUTOMOTIVE SERVICES: EVIDENCE FROM MACHINE LEARNING ON SATISFACTION AND SERVICE COSTS IN NIGERIA. SciencePlus, 1(2), 35–51. Retrieved from https://journal.barkahpublishing.com/index.php/sp/article/view/327

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