The Impact of the General Level of Prices and Operating Profit on Economic Value Added (EVA) (Analytical Study: ASE 2001 - 2015)
Bibliographic record
Abstract
This study aims to show the importance of the economic value added as one of the most modern to measure the financial performance for firms, then to know the effect of the general prices level and earnings before interest and taxes on EVA in the companies listed in (ASE) (2006-2015), the researcher addresses a random sample consisting of (46) Company, and uses regression model, which connects the dependent and independent variables.The results of the study shows that There is a significant impact for the general prices level and the earnings before interest and taxes on the economic value added, and also shows that 22% of the changes in the economic value added are due to general prices level and earnings before interest and taxes, and 78% of the changes are due to other factors.This study also recommends the need to manage of operating expenses because of the positive impact of operating profit on EVA value, and to take inflation into account when calculating the value of EVA, and also searching for other factors that could affect the value of EVA such as sales volume, cost of capital, and the growth in the total assets of the company's financial leverage, etc…
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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 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".