Translating knowledge management into performance
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Purpose This paper aims to tie together insights from the body of research on knowledge management (KM) and management accounting control systems to propose a conceptual model in which performance measurement systems (PMS) can play a role in translating knowledge resources into enhanced performance. Design/methodology/approach The underlying assumption of the “fit-as-mediation” approach signifies that knowledge features can play a role in the determination of the structure and implementation of particular managerial processes and this, in turn, may support information processing and lead to desirable results within organizations. Findings Synthesizing theory from performance measurement and the knowledge-based view of the firm, the paper’s analysis and discussions elucidate how the implementation of an overarching PMS, i.e. diversity of measurement, could translate the knowledge-related factors, i.e. knowledge resources and knowledge process capabilities, into enhanced performance. In particular, the proposed model shows that a comprehensive PMS plays an intervening role between KM and organizational performance. Research limitations/implications The proposed model may inspire a new research agenda to show how knowledge initiatives are managed and measured in organizations and how they are properly aligned with specific managerial processes to deliver real value. Practical implications Drawing upon the conceptualized associations among KM, PMS and organizational performance, this paper recommends some practical guidelines by highlighting the importance of PMS whereby organizations may reap maximum benefit from their KM initiatives. Originality/value This paper sheds new light on the links between KM and organizational performance, and it appears to be the first study to propose an intervening effect of PMS between KM and organizational performance.
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.
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 | 0.004 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.029 |
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