Human Resource Strategies as a Mediator between Leadership and Organizational Performance
Bibliographic record
Abstract
Leadership style is a kind of method that aims to realize organizational targets and affect all organizational activities. This quantitative study focused on various business domains in Saudi Arabia to examine how leadership styles are related to human resource strategies and organizational performance. The study adopted the self-administered survey methodology technique using a pre-validated pre-piloted questionnaire. Data were analyzed using Structural Equation Modelling. A total of 270 questionnaires were distributed with a response rate 92.9% based on a convenience method. Our survey found a direct positive relationship between leadership style and organizational performance and an indirect relationship between leadership style and human resource strategy as a mediator, while human resource strategies contribute positively and significantly to organizational performance. The findings are relevant for operating human resource management strategies and for developing a style of leadership. An enterprise can use this information to promote recognition and devotion among its employees based on a range of strategies, and then creates overall performance of the organization. Also, it is possible to use different leadership styles for different strategies. Consequently, this study has both theoretical and practical reference value.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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 source (direct Gemma or distilled Codex), 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".