The Mediating Role of Knowledge Management and the Moderating Part of Organizational Culture between HRM Practices and Organizational Performance
Bibliographic record
Abstract
The aim of this study was to investigate the relationship between human resource management (HRM) practices and organizational performance on the basis of 247 valid and reliable questionnaires distributed to managers at different management levels working in Jordanian manufacturing firms. The study also aimed to explore the mediating role of knowledge management as well as the moderating effect of organizational culture on the relationship between HRM practices and organizational performance. Ten HRM practices and 10 indicators of organizational performance were adopted for the purpose of this study. Knowledge management was measured by examining three processes; knowledge creation, sharing and utilization. Organizational culture was measured according to passive/defensive, aggressive/defensive and constructive cultures. The results of the study supported the presumed hypotheses. Hence, HRM practices significantly predicted organizational performance. Knowledge management mediated the relationship between HRM practices and organizational performance. Finally, it was found that organizational culture moderated the relationship between HRM practices and organizational performance as well as the relationship between HRM practices and knowledge management. Constructive cultures play a positive role in the relationship between HRM practices and organizational performance (OP), while defensive cultures negatively affect the relationship between HRM practices and knowledge management (KM). The main contribution of this study to the literature on HRM, KM and OP derives from the lack of prior studies addressing the same purposes as this study. The study informs researchers and managers that both knowledge management and organizational culture mediate and moderate the impact of HRM practices on organizational performance to a considerable extent.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".