Factors influencing the value added tax compliance in small and medium enterprises in Jordan
Bibliographic record
Abstract
This study aims to obtain the results of value added tax (VAT) compliance through behavioral decision theory with work personal attributes of the taxpayer's, tax understanding and taxpayer education, and ability to pay theory with tax compliance cost and audit system as a connecting variable to VAT compliance. The researcher randomly selected sample of n= 172 small and medium enterprise owners from Jordan by using web-based survey questionnaires. Data analysis uses the SPSS 23.0 and validates the relationship between study variables. The researchers also propose a research model support by the behavior decision theory and the ability to pay approach. Findings reveal a strong positive relationship between personal characteristics, VAT education and tax compliance under both theoretical grounds and also indicate a positive correlation between VAT compliance cost, audit system and VAT compliance in Jordan. Addressing the understudies, this study extends the role of value added tax practices in SMEs. It provides some useful information to the government and policy makers to develop and impose the value added tax law on SMEs Level. Therefore, the researcher suggests more studies to investigate the factors affecting VAT compliance in Jordan by using the proposed conceptual model under consideration.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 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".