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Barrier Factor Structure

Published: April 2026

Prolific APPROVED + all quality checks (IRI, duration >= 540s, reCAPTCHA, straightlining, auth)

Sample size adequacy: Inadequate. N:parameter ratio 2.7:1 is well below minimum thresholds. CFA results are unreliable and provided for trend monitoring only as sample size grows.

The TABS Barriers scale includes 18 items and was developed through a concept-mapping process that identified four theoretical sub-constructs. Exploratory Factor Analysis (EFA) on the full TABS dataset included 124 responses, with 118 listwise valid responses for the factor analysis. An exploratory 3-group decomposition is also available for practitioner-oriented reporting.

See the Statistics Glossary for definitions of all psychometric terms used on this page, or the Instrument Validation page for the full results across all three constructs.

Level 1: Theory-Based Groupings (4 Groups)

The concept-mapping exercise (Appendix D) sorted the 18 barrier items into four sub-constructs based on thematic affinity and theoretical grounding in the adoption barriers literature.

Organizational & Cultural (2 items)

Internal cultural resistance and risk aversion

B1B3
Strategic & Operational (6 items)

Strategy gaps, legacy systems, governance

B2B7B9B10B11B12
Resource & Skill (4 items)

Workforce, training, cost, infrastructure

B4B5B6B8
Risk, Trust & External (6 items)

Security, privacy, regulation, vendors

B13B14B15B16B17B18

Total: 2 + 6 + 4 + 6 = 18 items. The four groups have unequal sizes by design because real-world barrier categories differ in breadth.

EFA with Promax rotation + Horn's Parallel Analysis

Level 2: EFA-Derived Structure (2 Factors)

Horn’s Parallel Analysis compared actual eigenvalues against the 95th percentile of random-data eigenvalues and retained one factor. The single factor explains 26.2% of variance.

StatisticF1
Eigenvalue5.431
Variance Explained26.2%
Items18
KMO (overall)0.842
Bartlett’s χ²576.7 (p < .001)
F1 (18 items)
B1B2B3B4B5B6B7B8B9B10B11B12B13B14B15B16B17B18
items: 18eigenvalue: 5.4311varianceExplained: 26.2%
Forced 2-factor extraction within F1 (exploratory)

Level 3: Exploratory 3-Group Decomposition

Because F1 contains 14 of the 18 items, we explored whether it could be meaningfully sub-divided. Horn’s Parallel Analysis on F1 alone recommends retaining only 1 factor, so any split is not statistically mandated. However, a forced 2-factor extraction within F1 produces two interpretable, closely related sub-groups.

Important methodological note

The 3-group solution is exploratory and intended for practitioner reporting, not as a replacement for the statistically supported 2-factor structure.

F1a β€” Strategy & Culture (9 items)
B1B2B3B5B9B10B11B15B17
items: 9alpha: 0.7995cr: 0.8023ave: 0.3167
F1b β€” Resources & Operations (5 items)
B4B6B7B8B12
items: 5alpha: 0.6103cr: 0.6158ave: 0.2493
F2 β€” External & Compliance (4 items)
B13B14B16B18
items: 4alpha: cr: ave:

3-Group Reliability Summary

GroupItemsΞ±CRAVE
F1a β€” Strategy & Culture90.7990.8020.317
F1b β€” Resources & Operations50.6100.6160.249
F2 β€” External & Compliance4β€”β€”β€”

Item-Level Factor Loadings

Full 18-item loading matrix from EFA with Promax rotation (ML estimation, N=118). Primary loadings are bolded. Items are grouped by their dominant factor assignment.

ItemBarrierF1 LoadingAssigned
B3Risk-Averse Culture0.693F1
B10No Clear Strategy/Roadmap0.658F1
B2Lack of Leadership Support0.648F1
B4Insufficient Workforce Skills0.631F1
B1Resistance to Change0.577F1
B8Inadequate IT Infrastructure0.565F1
B5Inadequate Training0.554F1
B15Lack of Trust in Tech/Vendors0.512F1
B11Insufficient Governance0.490F1
B9Difficulty Demonstrating Value0.459F1
B12Workflow Disruption0.455F1
B16Regulatory Complexity0.440F1
B7Legacy System Integration0.423F1
B14Data Privacy Compliance0.412F1
B17External Pressure Without Readiness0.404F1
B6High Implementation Cost0.379F1
B13Cybersecurity Concerns0.368F1
B18Vendor/Partner Difficulty0.355F1

Level 4: Multi-Group Stability and Cross-Validation

The 3-factor structure must hold across organizational subgroups (SMB vs Enterprise) and across random splits of the sample to support generalization. Multi-group CFA reports per-group fit; cross-validation reports Tucker congruence between independently estimated factor solutions.

Multi-group 3F CFA (SMB vs Enterprise)

GroupNCFIRMSEAchi-squareddf
SMB (n<1000)711.0540.00080.13132
Enterprise (n>=1000)471.1100.00095.81132

50/50 split-half cross-validation

SplitNCFITLIRMSEA
Calibration591.1101.1280.000
Validation591.0651.0760.000

Tucker's congruence: 0.964Factor equivalence(identical)

Tucker's congruence coefficient (Lorenzo-Seva & ten Berge, 2006): values β‰₯ .95 indicate factor equivalence, .85 to .95 indicate fair similarity, < .85 indicate dissimilar factors.

Level 5: ESEM Sensitivity (Exploratory Structural Equation Modeling)

ESEM (Asparouhov & Muthen, 2009) sits between EFA and CFA: it estimates a target-rotated factor solution with all cross-loadings free. Items whose dominant loading shifts relative to the canonical 3-group assignment are candidates for reassignment in future revisions.

N (listwise)118
Cumulative variance31.1%

Variance Explained per Factor

FactorVariance Explained
F115.0%
F28.1%
F38.0%

Factor Correlations

F1F2F3
F1β€”0.3610.561
F20.361β€”0.287
F30.5610.287β€”

No items shifted dominant loadings under ESEM relative to the canonical 3-group structure.

Interpretation and Implications

Why 4 Theory Groups Become 2 Factors

The concept-mapping sub-constructs represent distinct theoretical traditions, but organizational leaders perceive barriers through a simpler lens: things within their control (internal organizational challenges) versus things imposed from outside (regulatory and compliance mandates).

The 14/4 Imbalance

F1 containing 14 items while F2 has only 4 is a legitimate asymmetry, not a flaw. Internal organizational barriers are inherently more diverse while external compliance constraints cluster tightly. The 3-group decomposition offers a more balanced practitioner view (9 / 5 / 4) for organizations seeking targeted intervention.

Practical Application

For academic reporting, use the statistically supported 2-factor structure. For practitioner dashboards and action planning, the 3-group decomposition provides more granular and actionable groupings.