The DOI matches its Crossref record; 137 of the 139 references it cites were found in a registry or an index.
A set-theoretic approach to organizational configurations
Open accessAbstract
I argue that research on organizational configurations has been limited by a mismatch between theory and methods and introduce set-theoretic methods as a viable alternative for overcoming this mismatch. I demonstrate the value of such methods for studying organizational configurations and discuss their applicability for examining equifinality and limited diversity among configurations, as well as their relevance to other research fields such as complementarities theory, complexity theory, and the resource-based view
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“By using the logic of set theory to conceptualize cases as configurations of causal attributes, QCA has been deliberately designed to both conceptualize and analyze the causal complexity underlying much organizational phenomena (Fiss, 2007).”
From Embracing Causal Complexity: The Emergence of a Neo-Configurational Perspective (2017) · cites this paper as Fiss, 2007
In the citing paper
“In fact, until recently, there was a void in tools capable of fully capturing causal complexity (Fiss, 2007; Fiss et al., 2013).”
From Embracing Causal Complexity: The Emergence of a Neo-Configurational Perspective (2017) · cites this paper as Fiss, 2007
In the citing paper
“Fiss (2007) introduced QCA's set-theoretic approach to management research as a means to study configurations and complex causality, demonstrating how it might overcome the mismatch between theory and methods that had plagued earlier configurational theorizing.”
From Embracing Causal Complexity: The Emergence of a Neo-Configurational Perspective (2017) · cites this paper as Fiss, 2007
In the citing paper
“Although such designs are well suited to assess the effectiveness of clinical treatments, it has long been recognised 110 that such research designs are less able to identify how exactly variables combine to create outcomes 111 or to fully explain the processes through which programmes actually work.”
From ReseArch with Patient and Public invOlvement: a RealisT evaluation – the RAPPORT study (2015) · cites this paper as [111]
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Metadata
- Authors
- Fiss, P. C.
- Affiliations
- University of Southern California (US)
- Corresponding author
- Fiss, Peer C.
- Venue
- Academy of Management Review
- Publisher
- Academy of Management
- Published
- 2007-10
- Volume
- 32
- Issue
- 4
- Pages
- 1180-1198
- ISSN
- 0363-7425 (ISSN-L)
- 1930-3807
- OpenAlex
- W2098386901
- Semantic Scholar
- 901b357c7d4ab59298bd0872554f3f34091c40ff
- Cited by
- 2,225
- References
- 139
- Citations by year
- 2026: 180 · 2025: 213 · 2024: 194 · 2023: 182 · 2022: 167 · 2021: 166 · 2020: 145 · 2019: 181 · 2018: 129 · 2017: 114 · 2016: 132 · 2015: 103 · 2014: 65 · 2013: 73 · 2012: 53
- FWCI
- 55.16
- Type
- journal article
- Language
- en
- Open access
- green
- papers.ssrn.com
- Locations
- Academy of Management Review (publishedVersion)
- SSRN Electronic Journal (submittedVersion)
- Topics
- Social Sciences › Business, Management and Accounting › Organizational Behavior and Human Resource Management › Management and Organizational Studies
- Social Sciences › Sociology and Political Science › Qualitative Comparative Analysis Research
- Social Sciences › Business, Management and Accounting › Strategy and Management › Innovation and Knowledge Management
- Keywords
- organizational configuration, set-theoretic methods, equifinality, complexity theory, resource-based view
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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