BUSINESS INTELLIGENCE U HRVATSKOM GOSPODARSTVU – REZULTATI ISTRAŽIVANJA 2017.
Bibliographic record
Abstract
Business intelligence (BI) or the system for collecting data from the business environment, and a basis for business decision making, is a management resource whose advantages have long been well-known to the economies of developed countries. Th e fi rst comprehensive study on the application of BI within companies that operate in Croatia was conducted in 2010/2011 and showed that only 19% of companies systematically conducted BI system activities. Th e repeated research conducted in the fi rst half of 2017 did not show any signifi cant changes. Still less than a quarter (24%) of the companies from the list of 1000 largest apply BI systematically. Responsiveness in the research as well as plans related to the BI system indicate that the general climate among the surveyed companies is not positive. Th is paper explains several possible reasons for such results, one of which is the so-called crisis in the largest Croatian company – Agrokor. Th e media coverage of this crisis started at the same time as the research on the implementation of BI in the 1000 largest companies. // Business intelligence (BI) ili sustav za prikupljanje podataka iz poslovne okoline na temelju kojih se donose poslovne odluke menadžerski je resurs čije su prednosti gospodarstva razvijenih zemalja davno upoznala. Prvo sveobuhvatno istraživanje o primjeni BI u tvrtkama koje posluju u Republici Hrvatskoj, provedeno 2010./2011., pokazalo je da tek 19% kompanija sustavno provode aktivnosti BI sustava. Ponovljeno istraživanje provedeno u prvoj polovici 2017. nije ukazalo na značajne promjene. I dalje manje od četvrtine (24%) tvrtki koje spadaju u red 1000 najvećih primjenjuju BI sustavno. Responzivnost u istraživanju kao i planovi vezani za BI sustav ukazuju da opća klima među ispitivanim tvrtkama nije odveć pozitivna, što se u radu objašnjava s nekoliko mogućih razloga od kojih je jedan tzv. kriza u najvećoj hrvatskoj kompaniji Agrokor, koja je (medijski) započela istodobno kada i istraživanje o primjeni BI-a u 1000 najvećih tvrtki.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.009 | 0.005 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.036 | 0.025 |
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".