Strategic knowledge management and enterprise social media
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 examine if (and how), enterprise social media (ESM) can be understood as a strategic knowledge management phenomenon to improve organizational performance. Design/methodology/approach This paper uses intellectual capital theory and its functional building blocks to organize different types of the ESM platforms, based on secondary data. It then connects these findings to the underling intellectual capital tenets to introduce a conceptual model that explicates how ESM impacts strategic knowledge management, and vice versa. Findings This paper concludes that ESM provides a unique complement to traditional strategic knowledge management. The authors argue that ESM differs substantially from other contexts in which intellectual capital has been applied, and extend intellectual capital with three appropriate dimensions (human, social and structural capital). Given the potentially disruptive nature of ESM, this framework helps firms understand the nature of the changes that are needed. Originality/value The paper provides the first review of the business needs that are served by the software functions and management processes under the ESM banner. This original contribution takes the intellectual capital and strategic knowledge management discussions from their usual high levels of abstraction and relates them to the real world of ESM, focusing on outcomes. Its unique “Intellectual Capital Framework for the Socially Oriented Enterprise” includes distinct, testable propositions that provide a practical approach to strategically planning, implementing and optimizing ESM.
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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 | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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