Cases inconsistent with theoretical expectations are by default indicators for a lack of theory-data fit, and as such are prime candidates for theory building. However, the conventional tendency is to ignore inconsistent cases in Management research.
Our article- Analyzing inconsistent cases in Management fsQCA studies: A methodological manifesto (Nair, L. B., & Gibbert, M. 2016. Journal of Business Research, 69 (4), 1464–1470), focuses on the theory-building prowess of inconsistent or deviant cases which turn up during an fsQCA study. The study looks at some of the key tenets of QCA: A cross-tabulation of cause and effect can demonstrate superior explanatory completeness only if one can account for all cases (be they deviant or not). To improve the neat theory-data fit characteristic of QCA, the paper proposes two new strategies for analyzing inconsistent cases of necessity and sufficiency in fuzzy set QCA studies and discusses their contributions to methodological sophistication.