The study of relationship between organizational structure and strategic knowledge management in Islamic Azad University, Kermanshah Branch
Bibliographic record
Abstract
The application of strategic knowledge management requires specific organization structure due to unique and particular characteristics of knowledge.In other words, by passing through industry age toward knowledge age, strategic knowledge management is considered by organizations dramatically and by considering this new competitive edge, universities should prepare an appropriate background for strategic knowledge management (encoding strategy and personalizing strategy).The primary purpose of this research is to find out whether there is a meaningful relationship between organizational structure (recognition, focus and complexity) and strategic knowledge management (codification strategy and personalization strategy) in Azad University, Kermanshah.Organizational structure is considered as independent variables and strategic knowledge management is dependent variables.When it comes to the purpose, present research is an applicable research and based on its nature and method, it is descriptive and survey research.Statistical society consists of university president, vise-president and dean of faculties of Azad University, Kermanshah; during a period of the first half of the year of 2011.Therefore, the sampling method is stratified sampling.Statistical society contains 60 people who are adjusted to 52 sample people by the use of Morgan table.Data collection tool is questionnaire structure questionnaire of Robbins and strategic knowledge management questionnaire of Carolina & ÁngelL.The results of the research show that there is a meaningful relationship between organizational structure and strategic knowledge management in Azad University, Kermanshah, according to codification and personalization strategy.Some suggestions are offered at the end of this research.
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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 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".