The analysis of selected resource management tools used in the Czech republic
Bibliographic record
Abstract
This submitted paper deals with the selected tools that are a part of resource management in the context of sustainable development.These instruments mainly cover corporate social responsibility, enterprise resource planning systems and strategic management with selected management models.Enterprise resource planning systems are the information base and support tools that a company's management uses for making decisions.The aim of these tools is to support a decrease in the consumption of raw materials, energy and other limited resources, which in turn increases the company's performance.This is mainly due to lower costs and increased corporate profitability.On the other hand, all these activities help to reduce the unfavorable ecologic impacts of business activities.This paper discusses the various ways to increase business performance through selected strategic management models through improving a company's competitiveness.The last part of the article is aimed at looking at the results of a survey that was conducted in the Czech Republic at the beginning of 2013.The research was focused on companies located in this country and it answered questions that surrounded on how these companies improved and increased their business performance in the market from the sustainable development point of view.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".