The Relation between Learning Orientation and Variables of Firm Performance with Strategic Human Resources Management Applications in the Islamic Banks in Turkey
Bibliographic record
Abstract
This study is aimed to research the relation between learning orientation and variables of firm performance with Strategic Human Resources Management (SHRM) Applications in the participation banks in Turkey. Labor force planning, education-development, assessing performance, reward system, and withholding employee are used as SHRM Applications. Firm performance is selected as only variable. It has been surveyed on participation banks in Turkey. Results inside the Strategic Human Resources Applications; it was detected that labor force planning is meaningfully impacting on labor force productivity and sales. On the other hand, labor force planning has no correlation with employee turnover rate which is one of the variable of organizational performance. Indeed, employee turnover rate is inversely correlated with sales of the company is detected. This study is aimed to explore the impact of Strategic Human Resource Management Applications (SHRMA) on learning orientation and firm performance under the conditions of intensive competitive business world where we live today. The variables of the study are Strategic Human Resource Applications, learning orientation, and firm performance. In the analysis, high constative relations of these variables were discussed with a reductant approach. When all the factors are fixed except the variables learn orientation, SHRMA and firm performance, the results of the correlation analyses gives us that the learning orientation, has a significant one to one effect on SHRMA and Firm Performance factors. Moreover, the results of the analyses that SHRMA has a complete mediator variable effect on the relation between Learning Orientation and Firm Performance. This results state a high arity between the variables that we procured via the corresponding structure equation model.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".