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Qualitative Comparative Analysis (QCA), initiated by Charles C. Ragin, is a research strategy with distinctive added value for organization studies. QCA constitutes in essence two configurational approaches, each grounded in set theory. One approach uses crisp-sets (dichotomous variables) to analyze cases. The other approach uses fuzzy-sets. While the use of fuzzy-sets has been increasing over the last few years, the crisp-set (csQCA) approach is still used in a majority of empirical applications. This chapter discusses in-depth the application of csQCA in organization studies. This chapter starts with a stylized presentation of two dominant research strategies, case-based research and variable-based research, and how csQCA relates to them. Subsequently, csQCA is further introduced and the different applications in organization studies are discussed. This section ends with a brief step-wise “how to” presentation. The chapter then turns to a presentation of the main distinctive strengths of the approach. In the final part, the chapter discusses extensively the main criticisms which have been raised with regard to (cs)QCA and draws out some of the main implications of this discussion.

In this concluding chapter, we look ahead to future theoretical and methodological directions that emerge from the contributions in this volume and that carry the potential to enrich contemporary organizational research. We furthermore point to some issues that remain unsolved and need to be addressed in future research to further establish the configurational approach in the field of organizational studies, such as the growing need for homogeneity in how the analysis is conducted and results are presented. We argue that the momentum of the configurational approach in organizational research is strong, but that important challenges remain.

The notion of configuration – that the whole is best understood from a systemic perspective and should be viewed as a constellation of interconnected elements – is arguably one of the central ideas of organization studies. Yet, this idea also remains one of the field’s least understood aspects. In this volume and its introduction, we outline a new perspective for understanding configuration. Our starting point is the emergence of set theoretic configurational methods, and especially Qualitative Comparative Analysis (QCA), which provides novel ways for analyzing configurations. Our volume goes beyond introducing a new method to the fields of management and organization, as these methods furthermore offer an opportunity to rethink our understanding of the field and to develop different ways of theorizing the rich complexity of relationships that characterize organizational life. In this introduction, we introduce some of the key themes that differentiate the approach taken here from previous work on organizational configurations and provide evidence for the emerging renaissance of the configurational approach in organizational theory and research.

Although QCA was originally developed specifically for small-N settings, recent studies have shown its potential for large-N organization studies. In this chapter, we provide guidance to prospective researchers with the goal of opening up QCA’s potential for widespread use in organization studies involving large-N settings, both as an alternative and as a complement to conventional regression analyses. We compare small-N and large-N QCA with respect to theoretical assumptions and objectives, processes and decisions involved in building the causal model, selecting the sample, as well as analyzing the data and interpreting the results. Finally, we discuss the prospects for large-N configurational analysis in organization studies and related fields going forward.

I have always felt that one of the most important roles that a book chapter can fulfill is effectively setting the stage for future scholars to build on the content of the chapter. This is a particularly important task where doctoral students are concerned, given their status as newcomers to organizational research. Ideally a doctoral student can pick up tips in a book chapter that will facilitate her or him conducting better studies than if s/he had never read the chapter.