Fuzzy-set Qualitative Comparative Analysis (fsQCA): Guidelines for research practice in Information Systems and marketing
Open accessAbstract
The increasing interest in fuzzy-set Qualitative Comparative Analysis (fsQCA) in Information Systems and marketing raises the need for a tutorial paper that discusses the basic concepts and principles of the method, provide answers to typical questions that editors, reviewers, and authors would have when dealing with a new tool of analysis, and practically guide researchers on how to employ fsQCA. This article helps the reader to gain richer information from their data and understand the importance of avoiding shallow information‐from‐data reporting. To this end, it proposes a different research paradigm that includes asymmetric, configurational‐focused case‐outcome theory construction and somewhat precise outcome testing. This article offers a detailed step-by-step guide on how to employ fsQCA by using as an example an already published study. We analyze the same dataset and present all the details in each step of the analysis to guide the reader onto how to employ fsQCA. The article discusses differences between fsQCA and variance-based approaches and compares fsQCA with those from structured equation modelling. Finally, the article offers a summary of thresholds and guidelines for practice, along with a discussion on how existing papers that employ variance-based methods are extendable and complemented through fsQCA.
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The variables examined may have complex and asymmetric relationships, or the configuration of multiple conditions.
“we are aware that the variables examined may have complex and asymmetric relationships, or the configuration of multiple conditions”
From Understanding managers’ attitudes and behavioral intentions towards using artificial intelligence for organizational decision-making (2021) · cites this paper as Pappas and Woodside, 2021
The final sample (N=468) exceeded recommended thresholds for both SEM and fsQCA, ensuring sufficient power and generalisability.
“The final sample (N = 468) exceeded recommended thresholds for both SEM (Kock and Hadaya 2016) and fsQCA (Pappas and Woodside 2021), ensuring sufficient power and generalisability.”
From Seeing Is Believing, Experiencing Is Deciding: How Augmented Reality Attributes Drive Confidence in Choice and Willingness to Pay (2026) · cites this paper as Pappas and Woodside 2021
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- Authors
- Pappas, I. O., & Woodside, A. G.
- Affiliations
- University of Agder (NO)
- Boston College (US)
- Corresponding author
- Pappas, Ilias O.
- Venue
- International Journal of Information Management
- Publisher
- Elsevier BV
- Published
- 2021-06
- Volume
- 58
- Pages
- 102310
- ISSN
- 0268-4012 (ISSN-L)
- OpenAlex
- W3128415798
- Cited by
- 2,254
- References
- 10
- Citations by year
- 2026: 560 · 2025: 624 · 2024: 505 · 2023: 337 · 2022: 182 · 2021: 46
- FWCI
- 370.73
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- International Journal of Information Management (publishedVersion, cc-by)
- RePEc: Research Papers in Economics (submittedVersion)
- NORA - Norwegian Open Research Archives (submittedVersion, cc-by)
- Funders
- Horizon 2020 Framework Programme (751550)
- Topics
- Social Sciences › Sociology and Political Science › Qualitative Comparative Analysis Research
- Social Sciences › Decision Sciences › Information Systems and Management › Business and Management Studies
- Social Sciences › Education › Qualitative Research Methods and Applications
- Keywords
- fuzzy-set qualitative comparative analysis, configurational analysis, information systems research, market analysis
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