A Conceptual Model of Sales Tax Compliance among Jordanian SMEs and Its Implications for Future Research
Bibliographic record
Abstract
Tax compliance is a serious and growing issue all over the world. The government of Jordan undertakes various fiscal measures to maximize domestic throughout the past few decades but according to the annual reports, the country still faces a sharp increase in net public debt and fiscal deficit brought about by the increase in the rate of tax non-compliance, and this particularly holds true for sales tax. Therefore, this study generally focuses on the topic of tax non-compliance, specifically sales tax in the Jordanian context. Literature is still lacking of studies that examined determinants of sales tax compliance and several determinants may be the causes behind the non-compliance phenomenon but a general tax compliance model is not effective in explaining the issue. Therefore, for an in-depth understanding of sales tax compliance determinants in Jordanian SMEs, the present research brings forth an extension of Fischer’s model of tax compliance, with the addition of the moderating influence of tax services quality. The proposed model takes social, psychological and economic factors into consideration within one comprehensive model to provide insight into sales tax compliance among SMEs in Jordan.
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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 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".