Analysis of Smart Tax System Scenarios and Executive Strategies in Iran
Keywords:
Futures Studies, Tax System, Smartization, Scenario WritingAbstract
This study aimed to identify potential scenarios for the smart transformation of Iran’s tax system and formulate corresponding executive strategies. This applied research employed a descriptive–survey design in both qualitative and quantitative phases. In the qualitative phase, a meta-synthesis of academic and research papers was conducted, selecting 10 key studies, followed by targeted interviews with 20 experts, including university professors and tax administration managers. In the quantitative phase, the Delphi method was used to refine and validate initially identified factors. Foresight and scenario planning techniques, supported by statistical analysis and specialized software, were applied to screen and confirm 57 components and 11 core indicators. The analysis revealed that smart tax system development in Iran involves scenarios such as digital transformation, strengthening intelligent human resources, applying emerging technologies like artificial intelligence and blockchain, enhancing transparency in tax processes, improving organizational structures, and advancing data and IT infrastructures. Expert consensus on the selected indicators was strong, with Kendall’s coefficient reaching 0.64 in the second Delphi round. The proposed scenarios are expected to increase voluntary tax compliance, reduce administrative and collection costs, improve equitable tax distribution, enable accurate identification of high-risk taxpayers, and strengthen public trust. Implementing a data-driven, stepwise smart tax system can fundamentally transform tax administration in Iran by improving efficiency, transparency, and fairness. Such reform will reduce administrative corruption, enhance sustainable government revenue, promote social justice, and lessen dependence on oil income, contributing significantly to long-term economic stability and growth.
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Copyright (c) 2025 Iesa Hashemi Ghandali (Author); Foad Makvandi; Reza Rostaminia, Vahid Chenari, Ezzatollah Kiani (Author)
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