Business Zakat Compliance Behaviour in Malaysia: Insights from SME Owners
Bibliographic record
Abstract
This study investigates the factors influencing business zakat compliance behaviour among SME owners in Selangor, focusing on the components of the Theory of Planned Behaviour. The independent variables analysed include self-efficacy, peer influence, incentives, and knowledge level, while zakat compliance behaviour serves as the dependent variable. Utilizing a quantitative approach, data were collected through questionnaires distributed to Malay business owners registered with the Selangor Malay Chamber of Commerce (DPMMNS). Empirical analysis conducted via SPSS reveals that self-efficacy, incentives, and knowledge level have a significant positive impact on zakat compliance, whereas peer influence exerts a negative effect. Despite zakat being a well-established religious obligation, the collection of business zakat remains disproportionately low compared to income zakat, as highlighted in a 2022 report by Lembaga Zakat Selangor. The findings emphasize the need for policymakers and zakat institutions to address these factors by developing targeted strategies to improve zakat compliance among SMEs, thereby enhancing zakat contributions and supporting the broader Muslim community.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".