Using Qualitative Comparative Analysis (QCA) as a Descriptive Numerical Method in Support of Narrative Methods
An important reason that qualitative research has had such an impact on the field of organization studies is that it uses narrative methods to cull coherent stories from complex realities that still manage to explain what really goes on in organizations. It might seem tautological to equate qualitative research with narrative methods, but it is only in practice that they have become all but synonymous among organizational scholars. Relatively few qualitative organizational scholars include detailed quantitative analyses in their studies. Indeed, looking through a sample of exemplar qualitative papers can easily lead to the conclusion that these scholars are number averse. One reason for this is that the philosophical foundations of the quantitative methods that currently predominate in organizational studies are generally in direct conflict with those of qualitative research. As a result, qualitative researchers have had few numerical methods available as potential options to include in their work. Additionally, qualitative researchers who use narrative methods are often subtly (and not so subtly) under pressure to convert their research to fit the “general linear reality” (Abbott, 1988) of dominant quantitative methods and thus displace the logic of qualitative research (see Goertz & Mahoney, 2012, for an example of this division). Any inclusion of numerical analysis within narrative analysis can become an opportunity for requests for its expansion at the expense of the narrative methods. Qualitative researchers who have sufficient cases in their studies are invariably asked by reviewers (friendly and not) to run a regression or a similar type of analysis. This tendency drives some qualitative researchers to bury their numbers even when they have numbers to support their findings.