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Enregistrement W4394793598 · doi:10.52783/jier.v4i2.772

GST A Robust Tax Regime: A Bibliometric Analysis on GST

2024· article· en· W4394793598 sur OpenAlexaboutno aff
Bindu Arora Yashraj Sharma

Notice bibliographique

RevueJournal of Informatics Education and Research · 2024
Typearticle
Langueen
DomaineEconomics, Econometrics and Finance
ThématiqueTaxation and Compliance Studies
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésIndirect taxValue-added taxAd valorem taxGoods and servicesTax reformTax creditPublic economicsBusinessSales taxDirect taxTax revenueTax avoidanceEconomicsMarket economy

Résumé

récupéré en direct d'OpenAlex

A value-added tax placed on the delivery of goods and services is known as the goods and services tax (GST), and it is one of the most critical tax changes implemented in many countries worldwide. Indirect taxes, including sales tax, service tax, excise duty, and value-added tax, will be rolled into a single, all-encompassing tax system called the goods and services tax (GST). The introduction of the Goods and Services Tax (GST) has been the topic of substantial study and analysis. This literature review aims to summarise the most important results and insights from the existing literature on GST. This review will focus on the research that has been conducted. The goods and services tax, sometimes known as the GST, has been adopted by several countries worldwide, including Australia, Canada, New Zealand, Malaysia, Singapore, and India. The evolution of the Goods and Services Tax (GST) has been affected by several issues, including the necessity to simplify the tax system, expand the tax base, increase revenue collection, encourage economic development, and make it easier to do business across international borders. In addition, the research underlines that the design and execution of the Goods and Services Tax (GST) differ from country to country due to each nation's specific economic, social, and political conditions. Increasing the amount of money that the government takes in is one of the most important objectives of the GST. According to the research findings, the GST's effects on the income collected are complex. While some studies suggest that an increase in revenue collection has occurred as a result of the adoption of the Goods and Services Tax (GST), other studies highlight the challenges that have arisen as a result of the GST, including revenue leakage, compliance concerns, and the requirement for ongoing monitoring and enforcement. In addition, the research analyses elements that impact revenue collection, such as the tax rate, tax base, exemptions, and the efficiency of tax administration. These factors all have a role in determining how much money is brought in. This study focuses on scientific visualization based on the bibliometric analysis of 426 publications, of which 180 were completed after applying the filters on the keywords "Goods and services tax" in the Scopus database from 2017 to 2022. The articles were analyzed for a period ranging from 2017 to 2022. Bibliometric analysis, appraisal, and visualization are some of the uses that R has seen. The examination produced a scientific map that included co-occurrence analysis, network analysis, a co-citation network, and a collaboration network. These elements contributed to a better understanding of the research topic as conceptual, intellectual, and social structures. The outcome of the bibliometric analysis demonstrates that the evolution of the Goods and Services Tax (GST) has resulted in the introduction of a new tax regime in several nations. Furthermore, the outcome of the social collaboration analysis demonstrates that many nations, including India, the United Kingdom, Canada, and Australia, are collaborating to conduct more fruitful research.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,002
score de la tête « metaresearch » (Gemma)0,001
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesBibliométrie
Catégories consensuellesBibliométrie
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,428
Score d'incertitude au seuil0,972

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0020,001
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0610,048
Études des sciences et des technologies0,0000,000
Communication savante0,0010,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,117
Tête enseignante GPT0,372
Écart entre enseignants0,255 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; les deux têtes enseignantes s’accordent sur ce qui est montré ici.

Devis d'étudeSans objet
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations2
Publié2024
Routes d'admission1
Résumé présentoui

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