Qualitative Comparative Analysis (QCA) - Dr. Thomas Greckhamer

Which of the following best describes the rationale for using a set-theoretic approach in QCA?

To examine whether specific combinations of conditions are necessary or sufficient for an outcome
To analyze variance in interval-level data
To test for moderation and mediation effects
To optimize statistical efficiency across large-N samples

In constructing a configurational model, what risk arises from including too many conditions?

Sparsity in the truth table and increased interpretive complexity
Multicollinearity
Loss of external validity
Overfitting

Which of the following best captures the three core principles underlying Qualitative Comparative Analysis (QCA)?

Conjunctural causation, equifinality, and causal asymmetry
Parsimony, objectivity, and statistical generalizability
Moderation, mediation, and construct validity
Necessary conditions, sufficient conditions, and effect sizes

Which of the following scenarios illustrates causal asymmetry in QCA?

The presence of a condition leads to an outcome, but its absence does not necessarily lead to the absence of that outcome
The absence of X leads to the absence of Y
The presence of X always leads to Y, and the absence of X always leads to not-Y
Two variables show a correlation of r = 0.65

What role do “counterfactuals” play in QCA analysis (especially during Boolean minimization)?

They enable researchers to simplify configurations by evaluating logical remainders—combinations not observed but theoretically possible
They validate calibration thresholds empirically
They help establish convergent validity
They serve as instrumental variables

What is the primary goal of Boolean minimization in QCA?

To reduce complex configurations into simpler, logically equivalent expressions
To identify outliers
To find the best-fitting regression equation
To maximize internal validity by removing deviant cases

In QCA, what does a coverage score indicate?

The empirical relevance of a configuration i.e. how much of the outcome it explains
The probability of an outcome occurring
The statistical significance of each condition
The level of inter-rater reliability in coding conditions

What is the purpose of applying frequency and consistency thresholds in truth table construction?

To filter out configurations that are not empirically robust or do not meet minimum sufficiency criteria
To improve external generalizability
To align with SEM model fit standards
To balance the number of positive and negative outcomes

When interpreting QCA results, what does a unique coverage score indicate for a configuration?

The proportion of the outcome that is explained solely by that configuration (not overlapping with others)
The number of logical remainders supporting it
Its relative frequency among all cases
The causal strength of individual conditions within the configuration

Which of the following best describes the parsimonious solution in QCA?

It reduces complexity by incorporating all simplifying assumptions, even those lacking theoretical support
It prioritizes empirical robustness by using only observed configurations
It excludes conditions that are not statistically significant
It emphasizes consistency over coverage in the final output

In QCA, what is the purpose of applying theoretical heuristics during solution minimization?

To guide the use of counterfactuals by distinguishing plausible from implausible simplifying assumptions
To ensure statistical significance of configurations
To eliminate low-frequency truth table rows
To improve sample representativeness

In the fsQCA software, what does the ‘Frequency threshold’ control when constructing a truth table?

Minimum number of cases required for a configuration to be considered
Number of conditions per row
Range of calibrated scores
Tolerance for calibration error

When refining a fuzzy set calibration, researchers often:

Adjust crossover points to better reflect theoretical meaning
Recode all cases below the mean
Use only the highest observed value
Convert to binary sets for simplicity

You’re creating a fuzzy set for “Leader-Led Ventures.” Which of the following variables is least useful for this calibration?

Firm's year of incorporation
CEO has >10 years of industry experience
CEO is the founder
CEO has prior startup leadership

When defining a set for “Customer-Centric Culture,” what kind of indicator aligns best with fuzzy set logic?

Customer satisfaction scores from internal surveys
Product reviews (1–5 stars)
CEO gender
Total number of customers

Why is a fuzzy score of 0.7 not interpreted the same as a probability of 70%?

Fuzzy scores express degree of set membership, not likelihood
Fuzzy logic is not numerical
Probabilities are required in QCA
0.7 is actually a full membership

In defining “High Moral Reputation” as a set, which of the following conditions would help reduce ambiguity in calibration?

Multiple indicators: sustainability rating, CSR index, and press coverage
Relying only on one online score
Using arbitrary thresholds
Asking the CEO directly

What is a risk of relying purely on sample-based thresholds (e.g., top 25%) when calibrating sets?

It disconnects the calibration from theoretical meaning
It makes calibration non-repeatable
It introduces random error
It improves reliability at the expense of coverage

A configuration has a consistency score of 0.62. What does this suggest?

The configuration is not sufficiently consistent to warrant interpretation
The condition is sufficient
The condition is necessary
The configuration is robust

What’s the practical risk of defining too many conditions in a QCA model?

The number of possible configurations increases exponentially, making interpretation difficult
It becomes more precise
It increases sample size
It removes logical remainders

In a QCA study of educational outcomes, two configurations lead to high student performance:

Configuration 1: Strong teacher support AND High parental involvement

Configuration 2: Access to resources AND High student motivation

This best reflects which concept?

Equifinality
Causal asymmetry
Redundancy
Set intersection

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Qualitative Comparative Analysis (QCA) – Dr. Thomas Greckhamer

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