Investigating the effect of connectivity of top management team on their resilience
Bibliographic record
Abstract
Nowadays, organizations are operating in a full of complex, ever changing and unpredictable environment, so that technological changes in providing goods and services, creating new organizational structures, new competitive methods and unique methods of sales indicate the importance of planning of top management team in line with the organizational success. Therefore, an attribute, which is important more than ever is resilience of top management team from two dimensions of its beliefs and adaptive capacity with these environmental events. Therefore, in this paper, the effect of connectivity of top management team on their resilience was investigated amongst 500 industrial active units located in northeast of Iran as the statistical population. Statistical sample was comprised of 139 organizations. Analysis results using structural equation modeling showed that the tested model had a goodness of fit to data. The effect of connectivity of top management team on efficacious beliefs of resilience and adaptive capacity of resilience was confirmed in line with related previous studies.
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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 | 0.003 | 0.000 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".