A Theoretical Framework for Enterprise Risk Management and Organizational Performance
Bibliographic record
Abstract
The implementation of holistic risk management, enterprise risk management (ERM), is believed to contribute significantly to the successful performance of modern-day organizations that operate in an increasingly volatile and dynamic environment. In an environment of scarce resources and information uncertainty, ERM, risk culture, and strategic planning is required to face an unstable business environment to achieve organizational goals. Several conceptual and empirical studies have provided mixed evidence on the value relevance of ERM. Scholars have also demonstrated that the effects of ERM on performance are contingent upon certain contextual variables. Currently, the academic literature is silent on the joint relationship of ERM, risk culture, strategic planning, and organizational performance. The purpose of this study is to uncover this research gap by analytically reviewing pertinent conceptual and empirical literature to establish the possibility that the impact of ERM on organizational performance is transmitted through risk culture and strategic planning. This paper advances these evolving suggestions, which hinges on the conclusion that the direct effect of ERM on organizational performance is debatable and hence inconclusive due to the possible mediating influence of risk culture and strategic planning. A framework is conceptualized to examine the mediating effects of these two constructs on the relationship. The study proposes partial least squares structural equation modeling for statistical analysis using the unexplored multiple mediation analysis in the ERM academic literature. This paper’s postulations would guide empirical research in various contexts to address the knowledge gaps in the extant literature.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.001 | 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".