Embracing Causal Complexity: The Emergence of a Neo-Configurational Perspective
Furnari, S., Misangyi, V., Greckhamer, T. , Fiss, P., Crilly, D. & Aguilera, R. V. (2017). Embracing Causal Complexity: The Emergence of a Neo-Configurational Perspective. Journal of Management, 43(1), pp. 255-282. doi: 10.1177/0149206316679252
Abstract
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 neoconfigurational perspective: 1) conceptualizing cases as set theoretic configurations; 2) calibrating cases’ memberships into sets; 3) viewing causality in terms of necessity and sufficiency relations between sets; and, 4) 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 neoconfigurational approach and thereby shift the attention of management research away from a focus on net effects and towards examining causal complexity.
Publication Type: | Article |
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Additional Information: | Copyright Sage 2016 |
Publisher Keywords: | configuration; causal complexity; Qualitative Comparative Analysis (QCA); fuzzy |
Subjects: | H Social Sciences > HD Industries. Land use. Labor > HD28 Management. Industrial Management |
Departments: | Bayes Business School > Management |
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