Qualitative Comparative Analysis in Organizational Studies
Summary
Qualitative Comparative Analysis (QCA) has emerged as a robust method for exploring complex causality in organisational settings by combining the systematic rigour of quantitative techniques with the contextual richness of qualitative inquiry. Rooted in set theory and Boolean algebra, QCA enables researchers to identify configurations of conditions that are necessary or sufficient for given outcomes, acknowledging that multiple pathways may lead to similar organisational phenomena. In organisational studies, QCA has proven particularly valuable for uncovering how combinations of leadership styles, strategic orientations, institutional environments and technological capabilities interact to influence performance, innovation adoption and strategic change. By emphasising causal complexity and asymmetric relationships, QCA offers an alternative to variance‐based methods, allowing scholars to address questions of heterogeneous case trajectories, institutional variety and context‐dependent effects. Its flexibility supports both cross‐sectional and longitudinal designs, facilitates comparisons across organisational types and sectors, and yields practical insights for managers seeking to tailor interventions to distinct constellations of internal and external factors.
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Qualitative Comparative Analysis in Organizational Studies publication trend
The graph below shows the total number of articles in qualitative comparative analysis in organizational studies across all publications each year (not limited to Nature Index journals).
Technical terms
Qualitative Comparative Analysis (QCA): A set‐theoretic method for analysing how combinations of conditions relate to an outcome across multiple cases.
Fuzzy‐set QCA (fsQCA): An extension of QCA allowing partial membership in sets, enabling degrees of presence or absence of conditions.
Calibration: The process of translating raw data into set‐membership scores, typically ranging from full non‐membership (0) to full membership (1).
Configurational causality: The notion that outcomes result from specific combinations of conditions, rather than from single variables acting independently.
Consistency and coverage: Metrics used in QCA to assess the degree to which empirical data support a causal configuration (consistency) and the proportion of cases explained by that configuration (coverage).
Asymmetric relationships: The principle that causal pathways leading to the presence of an outcome may differ from those leading to its absence.
References
- Fuzzy-set qualitative comparative analysis (fsQCA) in business and management research: A contemporary overview. Technological Forecasting and Social Change (2022).
- FsQCA in entrepreneurship research: Opportunities and best practices. Journal of Small Business Management (2022).
- Hybrid Context, Management Practices and Organizational Performance: A Configurational Approach. Journal of Management Studies (2020).
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