Critical success factors in implementing knowledge management in consultant firms for Malaysian construction industry
Bibliographic record
Abstract
In Malaysia, there has been an argument that the Knowledge Management (KM) practice especially in construction industry has not been commensurable with its status as a developing country. Hence, an initiative that aims to appraise the KM practice amongst consultant firms working in industry of construction in Malaysia becomes the focal point of this study. This aim is achieved by fulfilling its objectives of delving into the understanding of consultant firms on KM practices and exploring the critical success factors (CSFs) of KM implementation in Malaysia. In this paper, the data is studied on a number of statistical analysis tools, namely descriptive analysis, reliability analysis and relative important index (RII). The results obtained from the questionnaire survey clearly showed that most respondents made a claim that KM enhances the decision making in the organization and KM spurs innovations. Few respondents disagreed with the components of KM practices, indicating that these respondents may not be well aware of the importance of KM. About the top ranking of CSFs for KM practices implementation, it is found that "continuous organization support", "leadership demonstration by senior staff/management", "knowledge and sharing culture", "execution of plan", and "continuous learning" make the top five factors very vital to the effective execution of KM by the consultant firms in the construction industry.
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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 | 0.006 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.002 | 0.001 |
| 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".