Web 2.0 Use and Organizational Innovation: A Knowledge Transfer Enabling Perspective
Bibliographic record
Abstract
Over the last several years, a variety of Web 2.0 applications has been widely adopted by individual users and recently has received great attention from organizations. While an increasing number of organizations have started utilizing Web 2.0 applications in hopes of boosting collaboration and driving innovations, only a small number of different theoretical perspectives are available in the literature that facilitate a further understanding of the phenomenon of organizational adoption of Web 2.0 to drive innovation. In this paper, we propose a theoretical model explicating this phenomenon from the perspective that Web 2.0 use enhances knowledge transfer by fostering the emergence of informal networks, weak ties, boundary spanners and social capital. This model conceptualizes the process through which organizations drive innovations by utilizing Web 2.0 applications. Based on this perspective, suggestions for organizations to facilitate this process are also provided.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.003 | 0.009 |
| Scholarly communication | 0.008 | 0.011 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 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 source (direct Gemma or distilled Codex), 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".