The Adoption Factors and Effects of Digital Technologies on Auditors' Performance in Sub-Saharan Africa
Bibliographic record
Abstract
This paper examines the factors driving the adoption of digital technologies and their impact on auditors’ performance. It empirically validates a research model grounded in the Unified Theory of Acceptance and Use of Technology (UTAUT) and the Theory of Action and Transformation Control (TACT). The study involved 120 auditors (seniors, managers, and senior managers) from audit firms within the OHADA region and employed Partial Least Squares Structural Equation Modeling (PLS-SEM).The findings reveal that expected performance, expected effort, and facilitating conditions are key determinants of digital technology adoption among auditors. Moreover, the adoption of these technologies significantly enhances auditors’ performance, particularly in fostering innovative performance. These results provide a novel contribution to audit literature by being the first to integrate UTAUT and TACT in this context, offering insights into adoption factors and performance dimensions.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".