Material and Immaterial Compensation as a Determinant of Employee Organizational Commitment
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The success and failure of any organization largely depend on talented and competent employees. Through human resource management (HRM) practices and policies, organizations strive to ensure committed employees. One of the fundamental practices they use is undoubtedly material and immaterial compensation. Adequate management of such compensation may contribute to greater employee engagement in achieving the set goals, realizing the mission, and fulfilling the vision of the organization. In such ways employees confirm their affiliation with the organization, which classifies them as committed employees. The paper assumes that the adequate application of material and immaterial compensation in organizations in Bosnia and Herzegovina (BiH) may improve employee organizational commitment. This ultimately has a positive impact on the effectiveness and efficiency of organizations. The research was conducted in 128 BiH organizations with more than 50 employees across four sectors. The hypotheses were tested applying the Principal Components Analysis (PCA) through the Kaiser-Meyer-Olkin (KMO) values and Bartlett's test of sphericity and the regression analysis. The results show a statistically significant positive impact of material and immaterial compensation on employee organizational commitment. Creating more agile policies and practices of human resource management, especially those related to material and immaterial compensation, can significantly improve employee commitment as well as the entire organizational effectiveness.
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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 | 0.000 | 0.000 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 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 it