Investigating the Relationship between Customer Knowledge Management and Knowledge Sharing among Insurance Companies in Malaysia
Bibliographic record
Abstract
Recently, customer knowledge management has been widely recognized as a determinant of business performance. However, knowledge of customers that the organization gathers is useless unless it is shared internally. Sharing of this knowledge among organizational members will greatly strengthen the competitiveness of the organization, which makes it possible to take advantage of the competitive dynamics in the business environment. Although the importance of knowledge sharing especially the one that is related to customers has long been recognized by the community of researchers, investigation in this area is very limited. Therefore, the present study was conducted to investigate the relationship between Customer Knowledge Management dimensions, which consist of knowledge for customers, knowledge about customers, knowledge from the customer and knowledge sharing among insurance companies in Malaysia. A total of 180 managers of insurance companies in Malaysia participated in the survey. The results show that the three knowledge dimensions are positively and significantly related to knowledge sharing. Moreover, the results indicate that the insurance companies have implemented knowledge sharing practices especially in securing and managing their customer data to ensure the currency, accuracy, uniqueness and completeness of the customer data. Finally, research and practical implications are discussed.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.001 | 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".