Barrier Factor Structure
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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.
Internal cultural resistance and risk aversion
Strategy gaps, legacy systems, governance
Workforce, training, cost, infrastructure
Security, privacy, regulation, vendors
Total: 2 + 6 + 4 + 6 = 18 items. The four groups have unequal sizes by design because real-world barrier categories differ in breadth.
Level 2: EFA-Derived Structure (2 Factors)
Hornβs 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.
| Statistic | F1 |
|---|---|
| Eigenvalue | 5.431 |
| Variance Explained | 26.2% |
| Items | 18 |
| KMO (overall) | 0.842 |
| Bartlettβs ΟΒ² | 576.7 (p < .001) |
Level 3: Exploratory 3-Group Decomposition
Because F1 contains 14 of the 18 items, we explored whether it could be meaningfully sub-divided. Hornβs 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.
3-Group Reliability Summary
| Group | Items | Ξ± | CR | AVE |
|---|---|---|---|---|
| F1a β Strategy & Culture | 9 | 0.799 | 0.802 | 0.317 |
| F1b β Resources & Operations | 5 | 0.610 | 0.616 | 0.249 |
| F2 β External & Compliance | 4 | β | 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.
| Item | Barrier | F1 Loading | Assigned |
|---|---|---|---|
| B3 | Risk-Averse Culture | 0.693 | F1 |
| B10 | No Clear Strategy/Roadmap | 0.658 | F1 |
| B2 | Lack of Leadership Support | 0.648 | F1 |
| B4 | Insufficient Workforce Skills | 0.631 | F1 |
| B1 | Resistance to Change | 0.577 | F1 |
| B8 | Inadequate IT Infrastructure | 0.565 | F1 |
| B5 | Inadequate Training | 0.554 | F1 |
| B15 | Lack of Trust in Tech/Vendors | 0.512 | F1 |
| B11 | Insufficient Governance | 0.490 | F1 |
| B9 | Difficulty Demonstrating Value | 0.459 | F1 |
| B12 | Workflow Disruption | 0.455 | F1 |
| B16 | Regulatory Complexity | 0.440 | F1 |
| B7 | Legacy System Integration | 0.423 | F1 |
| B14 | Data Privacy Compliance | 0.412 | F1 |
| B17 | External Pressure Without Readiness | 0.404 | F1 |
| B6 | High Implementation Cost | 0.379 | F1 |
| B13 | Cybersecurity Concerns | 0.368 | F1 |
| B18 | Vendor/Partner Difficulty | 0.355 | F1 |
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)
| Group | N | CFI | RMSEA | chi-squared | df |
|---|---|---|---|---|---|
| SMB (n<1000) | 71 | 1.054 | 0.000 | 80.13 | 132 |
| Enterprise (n>=1000) | 47 | 1.110 | 0.000 | 95.81 | 132 |
50/50 split-half cross-validation
| Split | N | CFI | TLI | RMSEA |
|---|---|---|---|---|
| Calibration | 59 | 1.110 | 1.128 | 0.000 |
| Validation | 59 | 1.065 | 1.076 | 0.000 |
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.
Variance Explained per Factor
| Factor | Variance Explained |
|---|---|
| F1 | 15.0% |
| F2 | 8.1% |
| F3 | 8.0% |
Factor Correlations
| F1 | F2 | F3 | |
|---|---|---|---|
| F1 | β | 0.361 | 0.561 |
| F2 | 0.361 | β | 0.287 |
| F3 | 0.561 | 0.287 | β |
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.