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Title: Tax Compliance Behavior Among Malaysian Taxpayers: A Dual-stage PLS-SEM and ANN Analysis
Authors: Hayat, N. 
Salameh A.A. 
Mamun A.A. 
Helmi Ali M. 
Makhbul Z.K.M. 
Keywords: artificial neural network analysis;Malaysia;structural equation modeling;tax compliance
Issue Date: Jul-2022
Publisher: SAGE Publications Inc.
Journal: SAGE Open 
The tax system provides the necessary financial resources to a country’s administration to use the collected resources for the welfare of the general public and the development of general infrastructure. Therefore, compliance with the prevailing tax system is necessary for a country’s political and administrative system to survive. The current study aims to explore the intention to comply and the compliance behavior toward the tax system among Malaysian taxpayers. The data were collected using the survey method, and quantitative data were analyzed using the dual-stage methods of partial least squares structural equation modeling (PLS-SEM) and artificial neural network (ANN). The analysis results showed that the perceived fairness of the tax system, tax penalties, and tax awareness were significantly related to the intention to comply with the tax rules and regulations. Furthermore, the intention to comply with the tax system significantly influenced tax compliance behavior. The ANN analysis confirms that tax awareness, tax penalties, and fairness perception are the three most important factors influencing tax compliance. The tax authorities need to build the taxpayers’ confidence in the prevailing tax system and streamline the tax system to reduce tax complexity. Consequently, the taxpayers will start paying the correct and timely tax liabilities. The study’s limitations and future research avenues are documented at the end of this paper.
Web of Science / Scopus
ISSN: 21582440
DOI: 10.1177/21582440221127190
Appears in Collections:Faculty of Entrepreneurship and Business - Journal (Scopus/WOS)

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