Qualitative comparative analysis is increasingly applied in strategy and organization research. The main purpose of our essay is to support this growing community of qualitative comparative analysis scholars by identifying best practices that can help guide researchers through the key stages of a qualitative comparative analysis empirical study (model building, sampling, calibration, data analysis, reporting, and interpretation of findings) and by providing examples of such practices drawn from strategy and organization studies. Coupled with this main purpose, we respond to Miller's essay on configuration research by highlighting our points of agreement regarding his recommendations for configurational research and by addressing some of his concerns regarding qualitative comparative analysis. Our article thus contributes to configurational research by articulating how to leverage qualitative comparative analysis for enriching configurational theories of strategy and organization.

We utilized a multilevel approach to both estimate the relative importance of industry, corporate, and business segment effects on firm performance, as well as to demonstrate how it enables the investigation of specific strategic factors within each class of effects. Our results confirmed previous findings suggesting that although business segment effects carry the most relative importance, industry and corporate effects are also important. Among the findings regarding specific factors, we found that industry concentration and munificence, as well as the resource environment provided by corporate parents, impact performance. These findings suggest that investigators should consider both industry and corporate environments when examining performance.importance of industry, corporate, and business unit effects on firm performance. Since the seminal studies of Schmalensee (1985) and Rumelt (1991) on this issue, several scholars have entered the debate (From a practical standpoint, the identification of the factors which most substantially contribute to firm performance would enable managers to focus their attention on influential factors rather than peripheral ones.Despite the vast attention this line of inquiry has received, however, this literature offers varying conclusions about the relative contribution of each effect to firm performance (see Bowman and Helfat, 2001, for a comprehensive review). The

We would like to thank Associate Editor Heather Haveman and three anonymous reviewers for their insightful and developmental comments. We also thank the participants of the O&S Workshop at the University of Southern California and of an OTREG meeting held at the University of Cambridge for their valuable feedback on an earlier version of this paper, especially

Causal complexity has long been recognized as a ubiquitous feature underlying organizational phenomena, yet current theories and methodologies in management are for the most part not well-suited to its direct study. The introduction of the Qualitative Comparative Analysis (QCA) configurational approach has led to a reinvigoration of configurational theory that embraces causal complexity explicitly. We argue that the burgeoning research using QCA represents more than a novel methodology; it constitutes the emergence of a neo-configurational perspective to the study of management and organizations that enables a fine-grained conceptualization and empirical investigation of causal complexity through the logic of set theory. In this article, we identify four foundational elements that characterize this emerging neo-configurational perspective: (a) conceptualizing cases as set theoretic configurations, (b) calibrating cases’ memberships into sets, (c) viewing causality in terms of necessity and sufficiency relations between sets, and (d) conducting counterfactual analysis of unobserved configurations. We then present a comprehensive review of the use of QCA in management studies that aims to capture the evolution of the neo-configurational perspective among management scholars. We close with a discussion of a research agenda that can further this neo-configurational approach and thereby shift the attention of management research away from a focus on net effects and towards examining causal complexity.

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.