What Role is "Business Intelligence" Playing in Developing Countries? A Picture of Brazilian Companies
Bibliographic record
Abstract
Constant technological innovation and increasing competitiveness make the management of information a considerable challenge, requiring decision-making processes built on reliable and timely information from internal and external sources. Although available information increases, this does not mean that people automatically derive value from it. After years of significant investment to establish a technological platform that supports all business processes and strengthens the operational structure’s efficiency, most organizations are supposed to have reached a point where the implementation of information technology (IT) solutions for strategic purposes becomes possible and necessary. This explains the emergence of “business intelligence” (BI); a response to information needs for decision-making through intensive IT use. This chapter looks at BI projects in developing countries – specifically, in Brazil. If the management of IT is a challenge for companies in developed countries, what can be said about organizations struggling in unstable contexts such as those often prevailing in developing countries?
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How this classification was reachedexpand
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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".