Knowledge creation capability and the impact on innovation performance in global consulting firms: The role of human and social capital
Bibliographic record
Abstract
Abstract The purpose of this study is to identify the relationships between knowledge creation capability and innovation performance in multinational consulting organizations. We introduce two important but conceptually distinct, intellectual attribute constructs—human and social capital—as mechanisms that moderate the relationship. Survey data from 172 professional consultants in subsidiaries of multinational management consulting firms was empirically analyzed. This study confirms the importance of tacit knowledge creation capability for innovation and finds that explicit knowledge creation does not have substantial effects on innovation performance. Human capital has negative moderating effects on how tacit knowledge creation influences innovation performance, but it has a positive moderating effect on the relationship between explicit knowledge creation and innovation. The negative moderating effect of human capital appears stronger in the senior consultant groups. On the other hand, social capital has no moderating effects on knowledge creation capability and innovation. These results provide managerial implications for global subsidiaries' knowledge‐creating capabilities as drivers of successful, innovative change.
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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 | 0.005 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 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; both teacher heads agree on what is shown here.
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".