FsQCA versus regression: The context of customer engagement

Abstract

The purpose of this study is to address the strengths and weaknesses of the Fuzzy set Qualitative Comparative Analysis (fsQCA) method by contrasting it with traditional multiple regression analysis. To achieve our objective, we utilize the context of customer engagement and explore how both methodological approaches can explain the factors that lead customers to engage with brands/firms. We test the association between customer engagement and its antecedents by using both methods, fsQCA and multiple regression analysis (MRA), and compare the findings. MRA results show a significant relationship between customer engagement and perceived interactivity, perceived identification, perceived value, and brand involvement, a negative relationship with perceived fairness, while the relationship with customer satisfaction and perceived value is not statistically significant. On the other hand, fsQCA revealed eight different combinations of these antecedents that lead to high levels of customer engagement. Although multiple regression analysis (MRA) certainly has its own merit, our findings indicate that this methodological approach does not capture the complexities extant in real life. This method's strength of providing generalizable results is also its weakness as relationships cannot always be generalized as shown in our study. As such, at a minimum, fsQCA should be used as a complementary approach when authors employ MRA. We suggest ‘at a minimum’ because fsQCA possesses sufficient explanatory power to be employed by itself to offer a rich perspective on the relationships of interest. We also make several noteworthy contributions to the customer engagement and service marketing literatures.