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Record W4296004429 · doi:10.3390/jrfm15090407

The Effect of Tax Fairness, Peer Influence, and Moral Obligation on Sales Tax Evasion among Jordanian SMEs

2022· article· en· W4296004429 on OpenAlexvenueno aff
Nayef Mohammad Al-Rahamneh, Zainol Bidin

Bibliographic record

VenueJournal of risk and financial management · 2022
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicTaxation and Compliance Studies
Canadian institutionsnot available
Fundersnot available
KeywordsBusinessTax avoidanceMoral obligationPublic economicsRevenueEvasion (ethics)Tax reformSales taxTax evasionAd valorem taxIndirect taxDouble taxationAccountingEconomicsFinanceLawPolitical science

Abstract

fetched live from OpenAlex

Tax evasion remains a complex issue for tax authorities, policymakers, and researchers. While socio-psychological factors have been researched, their impact on tax evasion among SMEs has not yet been determined. This paper empirically analyses the effects of tax fairness, peer influence and moral obligation, on sales tax evasion among Jordanian SME owners/managers. A survey was used to obtain data from three regions of Jordan (north, middle, south). Random sampling was utilized in selecting the prospective respondents from SMEs in three sectors (trade, service, manufacturing). A total of 212 usable questionnaires retrieved from the SMEs were analysed using Smart-PLS 3.0. The results revealed that tax fairness and moral obligation had a significant negative effect on sales tax evasion behaviour among SME owner-managers. On the other hand, peer influence positively and significantly impacted sales tax evasion behaviour. Thus, policymakers and tax authorities should incorporate these factors in developing effective strategies to reduce tax evasion in Jordan, which could result in an improvement in the country’s overall revenue collection. The findings also contribute to the scarcity of literature about the significance of socio-psychological factors in mitigating tax evasion by examining the effects of tax fairness, peer influence, and moral obligation on sales tax evasion.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.059
Threshold uncertainty score0.344

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.009
GPT teacher head0.204
Teacher spread0.194 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations32
Published2022
Admission routes1
Has abstractyes

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