The Extent of Using and Trusting Capital Budgeting Methods in Projects Appraisal in Palestinian Corporations
Bibliographic record
Abstract
This research paper aims to find the degree of the use as well as the trust of the Net Present Value (NPV), Payback Period (PBP), Internal Rate of Returns (IRR) and Accounting Rate of Returns (ARR) as a key capital budgeting method. The research conducted on the listed corporations in Palestine which are 48 company. A questionnaire distributed on 77 financial and project/operations managers in these corporations with 67 responds. The result shows that both discounted and non-discounted cash flows methods are used and trusted by Palestine public corporations. However, on the other hand, the above four methods are volatile in term of use and trust. The most used and trusted capital budgeting method is the Payback period (PBP). This followed by the Net Present Value (NPV). Accounting Rate of Retunes (ARR) becomes third. Thus the least used and trusted method is the Internal Rate of Returns (IRR).
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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 | 0.014 | 0.027 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".