Forecasting Car Repair Shops Customers’ Loyalty based on SERVQUAL Model: An Application of Machine Learning Techniques

In today’s competitive world, service quality and customer satisfaction are recognized as key factors in the success of service organizations. This paper examines the impact of the SERVQUAL model and machine learning techniques on these two factors in the automotive repair and maintenance industry. With increasing customer awareness of different options and increasing competition in the market, repair shops must continuously improve their service quality to attract and retain customers. Satisfied customers are more likely to return to repair shops and share their positive experiences with others, which helps attract new customers. The research aims to predict customers’ willingness to return to a repair shop based on existing features and service quality indicators according to the SERVQUAL model. The results show that using machine learning methods to analyze data can more effectively identify complex patterns and predict customer behaviour. This paper also discusses the limitations of structural equation models (SEM) in predicting future customer behaviour and emphasizes that machine learning methods can provide more accurate predictions. Finally, this research emphasizes the importance of paying attention to service quality and creating a positive customer experience so that repair shops can succeed in a competitive market.