The Relationship between Respondents’ Characteristics and Their Perceptions of Enterprise Risk Management. Results of a Survey
Bibliographic record
Abstract
The present study investigated whether responents’ socio-demographic characteristics influenced their personal views on the adoption and implementation of enterprise risk management. An online questionnaire was administered to employees of Italian artisan firms to collect data on the adoption and implementation of enterprise risk management, its determinants, and its relationship with organisational performance. Respondents’ responses were compared to their demographic characteristics to determine whether gender, age, education, position, and role may have influenced their opinions on enterprise risk management. The presence of a well-established risk culture in an organisation and the support of senior management were considered essential in the effective implementation of enterprise risk management in an organization and in positively influencing organisational performance. Select participant’s demographic characteristics had an influence on their views on the implementation of enterprise risk management. The results of this study add to the body of knowledge on enterprise risk management and can support risk managers to effectively and efficiently implement enterprise risk management.
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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 | 0.005 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".