fsQCA in 2023–2026: Trends and Reporting Standards to Prioritize
The notable trend is toward stronger requirements for calibration, robustness, transparency, and inferential boundaries, rather than simply more use of fsQCA.
Prioritize preregistering major decisions, explaining anchors and directional expectations, reporting PRI and solution types, conducting sensitivity/holdout analyses, sharing de-identified data, and avoiding claims that observed configurations inherently establish causality.
fsQCA: from sets to outcome configurations
- Calibration
Justify set-membership anchors
- Truth table
Review frequency and consistency
- Solutions
Interpret alternative configurations
- Robustness
Check sensitivity and report choices
Conceptual diagram. Do not interpret an fsQCA configuration as a net-effect coefficient.
Source: Lê Minh · Conceptual illustration, not software output.1. Five Directions of Development
| Direction | Requirement |
|---|---|
| Substantive calibration | Anchors linked to field standards rather than percentiles alone |
| Robustness | Variation in anchors/frequency/consistency/PRI |
| Validation | Holdout or sample/time comparisons where feasible |
| Method integration | Separate net effects, necessity, and sufficiency |
| Open workflow | Save scripts, truth tables, and decisions |
2. What Articles Need to Disclose
- Definitions of the outcome set and its negation.
- Sources of every calibration anchor.
- N and membership distributions.
- Necessity consistency/coverage.
- Frequency, raw consistency, and PRI thresholds.
- Directional expectations and solution types.
- Raw/unique coverage of each configuration.
- Sensitivity and causal limitations.
3. Three Trends to Avoid
First, using fsQCA to manufacture novelty after nonsignificant regression results. Second, selecting anchors and thresholds after inspecting solutions to obtain attractive configurations. Third, treating core/peripheral notation as evidence of causal strength (Pappas & Woodside, 2021; Ragin, 2008).
Configurational results can be sensitive to samples and calibration. Demonstrate stability under reasonable changes rather than keeping all decisions fixed and calling the output robust.
Coverage describes coverage within the analyzed data. Prediction assessment requires a holdout or separate validation workflow.
4. An Analysis-Plan Template
Finalize questions
Clearly distinguish necessity, sufficiency, and the negated outcome.
Finalize the primary specification
Record anchors, thresholds, and counterfactuals before examining solutions.
Define robustness
State when two solutions will be considered consistent.
Example report
Before analysis, the study specified set definitions, anchors, and directional expectations. The primary specification used frequency [ ], consistency [ ], and PRI [ ]; robustness checks varied [ ]. Solutions were additionally assessed using [holdout/subsample/another time point] and interpreted as observed set relations.
Conclusion
A strong standard for fsQCA in 2023–2026 is the ability to explain every decision and assess sensitivity, rather than the number of configurations or model complexity.
References
- Pappas, I. O., & Woodside, A. G. (2021). fsQCA guidelines for research practice.https://doi.org/10.1016/j.ijinfomgt.2021.102310
- Ragin, C. C. (2008). Redesigning Social Inquiry.https://press.uchicago.edu/ucp/books/book/chicago/R/bo5973952.html
Academic note: The period 2023–2026 identifies the article’s synthesis timeframe; standards will continue to evolve.