To contribute to the largely unexplored issue of directly assessing the effect of service quality factors on store performance.
Service quality is decomposed into tangible elements, such as store size and personnel. A binary probit model is utilized in order to analyze the effect of various service quality factors on the probability that a store performs above average compared with its competitors.
Results indicate that the store size, product variety, location and belonging to chain, variables exert the largest positive effect upon the probability that a store experiences above‐average performance.
The present study suffers the limitation of a rather small usable questionnaires sample, albeit that the very satisfactory fit of the estimated econometric model allows for the findings to be a reliable comparison basis with future findings.
The approach proposed here can be widely used for empirical investigation in order to provide findings that may be compared across services sectors, trading places/countries and time. On the other hand, the importance of such findings to managerial decision‐making processes is evident.
The paper introduces a framework for empirically investigating the direct effect of service quality elements on store performance.
