The effect of tacit knowledge on firm performance
Why this work is in the frame
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Bibliographic record
Abstract
Purpose The purpose of this paper is to propose the use of the tacit knowledge index (TKI) to assess the level of tacit knowledge within firms and its effect on firm performance. Design/methodology/approach A sample of 108 US and Canadian firms that are using knowledge management was surveyed to determine each firm's TKI. This measure includes both the degree of usage and the tacitness of the knowledge management method. Regression and correlation were used to statistically analyze the innovation and financial outcomes. Findings Significant relationships were found between a firm's level of TKI and the firm's innovation performance. Less clear is the relationship between a higher TKI and financial measures. Research limitations/implications This research gives managers a way to structure their use of knowledge management methodology and use of resources in a way that may maximize performance, either as stand alone systems or as part of the Balanced Scorecard. Practical implications The use of this research could greatly reduce the uncomfortable gut feeling that many managers have in funding so‐called soft tacit‐based knowledge management systems rather than invest in easier to assess hardware systems. Originality/value This pioneering research develops tacit knowledge as a measurable quantity and links this metric to firm performance.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| 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 | 0.001 |
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 it