Knowledge Management Implementation, Strategic Human Resource Practices and Organizational Performance Mediated by Strategic Planning
Bibliographic record
Abstract
This study purpose is to determine the direct effect of strategic HR practices and knowledge management on organization performance, and to examine whether the strategic planning is a mediating variable. This study is conducted at Mandiri Islamic Bank in Malang, East Java. This is explanatory research type, with questionnaire as a tool for data collection. Analysis unit is employee of Independent Islamic banks in Malang. Data is analyzed by path analysis using SPSS. Analysis results showed that knowledge management affect on strategic planning, while strategic HR practices has no effect. Strategic HR practices directly affect on organization performance. Strategic planning mediates the affect of knowledge management on organizational performance. Knowledge management has indirect effect on organizational performance. It is necessary for good planning strategy. Using innovation, opinions sharing, employee’s involvement in decision making process will create better strategic planning, which in turn will affect on organizational performance. Strategic HR practices affect on organization performance because HR become vital resource for companies. Without HR role, automatically organizational performance can not be maximized. Islamic banking leader need to socialize to employees how to apply knowledge management rightly. High SOP allows a leader to motivate and affect subordinates by exchanging rewards with specific performance.
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 | 0.002 | 0.006 |
| 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 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".