Capturing Causal Complexity: Heuristics for Configurational Theorizing
Furnari, S. ORCID: 0000-0003-3212-6604, Crilly, D., Misangyi, V. , Greckhamer, T., Fiss, P. C. & Aguilera, R. V. (2020). Capturing Causal Complexity: Heuristics for Configurational Theorizing. Academy of Management Review, 46(4), pp. 778-799. doi: 10.5465/amr.2019.0298
Abstract
Management scholars study phenomena marked by complex interdependencies where multiple explanatory factors combine to bring about an outcome of interest. Yet, theorizing about causal complexity can prove challenging for the correlational theorizing that is predominant in the field of management, given its “net effects thinking” that emphasizes the unique contribution of individual explanatory factors. In contrast, configurational theories and thinking are well-suited to explaining causally complex phenomena. In this article, we seek to advance configurational theorizing by providing a model of the configurational theorizing process which consists of three iterative stages—scoping, linking and naming. In each stage, we develop and offer several heuristics aimed at stimulating configurational theorizing. That is, these theorizing heuristics are intended to help scholars discover configurations of explanatory factors, probe the connections among these factors, and articulate the orchestrating themes that underpin their coherence. We conclude with a discussion of how configurational theorizing advances theory development in the field of management and organizations, and beyond.
Publication Type: | Article |
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Subjects: | H Social Sciences > HD Industries. Land use. Labor > HD28 Management. Industrial Management |
Departments: | Bayes Business School > Management |
SWORD Depositor: |
Available under License Creative Commons Attribution Non-commercial No Derivatives.
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