Environmental Scanning and Business Insight Capability: _x000D_ The Role of Business Analytics and Knowledge Integration.
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
Environmental scanning is an important process that helps organizations sense what is happening in their environments. However, environmental scanning has been found to be less effective than its proponents had hoped for. The problem appears to be that environmental scanning does not lead to the business insights that managers need to help their organizations survive and grow. This paper reports a study into the role of data analytics and knowledge management on environmental scanning and business insight capability. Fifteen indepth interviews were conducted with data analytics professionals to get a deeper understanding of how what they did impacted the results of environmental scanning processes and the generation of business insights. The results indicate data analytics and knowledge management need to play a bigger role in the environmental scanning process if greater business insights are to be generated.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.003 |
| 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 it