Influence of Organizational Leadership on Knowledge Transfer in Construction
Bibliographic record
Abstract
Organizations are becoming more cognizant that transferring the supremacy of knowledge in business is precarious to attaining reasonable modifications. This research investigates the significant role of organizational leadership on knowledge transfer in the multinational construction organization in Nigeria. Thus, this research was based on the multinational construction organization as a result of their technological advancement on knowledge management, knowledge transfer and development process. The research study adopted empirically validated measures’ variables and established a hypothetical framework that links organizational leadership with knowledge transfer variables. 220 survey questionnaires were distributed to knowledge workers of 35 multinational construction organization, and the research validated the framework with structural equation modeling (SEM). The factor’s loadings for the variables measures were significant and Cronbash Alpha factors of 0.903 and 0.747 for organizational leadership and knowledge transfer respectively was achieved. The research finding display that organizational leadership demonstrated significant influence on knowledge transfer.
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How this classification was reachedexpand
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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.005 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".