1- University of Tehran, Tehran, Iran. , Yaser.shojae@ut.ac.ir
2- University of Tehran, Tehran, Iran.
2- University of Tehran, Tehran, Iran.
Abstract: (14 Views)
This research aimed to predict the compliance of taxpayers through the imposition of various tax penalties. The study examined the impact of different types of tax offenses and the general status of manufacturing and trading companies in Lorestan Province from 2017 to 2019. Using data from 125 active companies, the research design employed Rough Set Theory (RST) for analysis. Instruments included financial records, tax penalties, and company profiles. Data were analyzed through decision rules extracted via RST. Results indicated that four variables—penalties for non-submission of financial statements, lack of legal bookkeeping, annual financial turnover, and company activity history—had the [*]
most significant influence on taxpayer compliance. Conclusions emphasized that these variables reduce tax evasion and encourage adherence to tax laws.
Type of Study: Research |
Subject:
Accounting
Received: 2025/08/1 | Accepted: 2026/09/1 | Published: 2026/09/1
Received: 2025/08/1 | Accepted: 2026/09/1 | Published: 2026/09/1
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