Determinant Factor of Individual Taxpayer Compliance in Indonesia: Integrates of TPB Theory and Social Identity Theory
Bibliographic record
Abstract
Studies on tax compliance have predominantly used the theory of planned behavior. This study combines the theory of planned behavior with social identity theory. This study examines tax fairness (subjective norms), tax complexity (perceived behavioral control), tax morality (attitudes toward behavior), and national pride as social identity theory that explain their impact on tax compliance levels. Using non-probability random sampling, this study successfully collected 401 individual taxpayer respondents and analyzed them using PLS-SEM. The results of this study revealed that national pride is a crucial component in improving taxpayer compliance behavior. TPB theory still makes a significant contribution to tax compliance intentions through tax fairness and tax morality. This research suggests that tax authorities should manage tax funds by providing a sense of fairness and improving taxpayer morality. On the one hand, the government needs to promote national pride among taxpayers. This has the potential to remind taxpayers of the presence of taxes and encourage the mobilization of funds from the tax sector for national development.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".