Customer choice of a car maintenance service provider: A model to identify the service attributes that determine choice

This paper investigates the determinants of customer choice of a car maintenance service provider after the warranty period. It focuses on the alternative of using branded car dealers, who provide this service during the warranty period, or independent garages.

A comprehensive list of 30 service attributes is developed drawing on the service quality literature, specific previous studies on car maintenance services, and including other purchase behaviour determinants such as perceived value. Simple random sampling with replacement is used to collect data from 400 car owners using the actual choice of a service provider as the dependent variable. A quantitative analysis using a set of logistic regressions links directly customer choice to the service attributes.

Service attributes that determine customer choice are the ones consumers simultaneously consider important and perceive differences in performance between the service providers. The branded dealers service operation proved to be relatively weak, having only one of these attributes, while being better evaluated in less important ones. Independent garages have a much better offer justifying their gain in market share.

Only economic cars (1,000 cc) were analysed. Convenience and location were only partially controlled and could play a more significant role in some decision settings. Logistic regressions could effectively predict customer choice in close to 90 per cent of the cases demonstrating the adequacy of including other service attributes beyond the ones covered in the service quality literature.

Directions for improvement in the operations of both branded dealers and independent garages could be derived and some recent moves by both types of players could be supported by the results.

Investigation of the Brazilian setting and the methodological approach of linking actual customer choice to the extended set of service attributes by the combination of logistic regressions and the importance rating of the attributes.