The effect of knowledge management on organizational performance in the service sector: The role of transformational leadership as the moderating
Bibliographic record
Abstract
The main aim of the current study is to assess the relationship between knowledge management (KM) capabilities and organizational performance (OP) in developed nations. In addition, this study also aims to assess the moderating influence of transformational leadership (TL) between KM infrastructure (KMCI) and organizational performance (OP) of the Jordanian service and tourism sectors. In this study, it’s suggested that KMCI and its components will directly affect OP. In addition, it’s expected that TL moderates the relation between study variables. Purposive sampling was used to gather data from the service and tourism sectors in Jordan, as it is the population of this study. Partial Least Squares was used to analyze the data. The findings indicate that KMCI and its components significantly affect OP. TL moderated the effect of KMCI on OP. It is advised for decision-makers to concentrate on KMCI, create the proper culture and organizational structure, and improve its technologies to support the growth of KM activities in Jordanian service and tourism sectors.
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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 | 0.004 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".