Impact of Organizational Culture on Knowledge Management Process in Construction
Bibliographic record
Abstract
One of the key global pressures of knowledge management practice is knowledge acquisition, creation, sharing,storing and dissemination. The global business is reflecting a throng of culture, leadership and culturalupbringings which warrant bringing into line consistent alterations in management of knowledge because ofdiversity of workforce in construction organization. Theoretically, the study predicts the empirical role of culture(managerial learning and trust) with reference to knowledge management process. This paper presents aknowledge management (KM) model that comprises a set of KM hypothesis model and measurement models forunderstanding and applying these KM models to boost the application of KM in the construction organization.76 private construction organization was investigated with 323 questionnaire surveys. A hypothesized model ofKM process and culture was tested using structural equation modelling approach and a proposed model wastherefore developed. Likewise, all fit indices for KM process and factor loadings shows the significant impact ofculture on KM process, leading to a thrifty model achievement. The study shows that culture demonstrated 0.73significant influence on the knowledge management process. The analysis revealed that managerial learning andtrust were key factors that impact positively on KM process within the construction organization underinvestigation.
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 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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.006 |
| 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".