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<ArticleSet>
<Article>
<Journal>
				<PublisherName>University of Qom</PublisherName>
				<JournalTitle>Journal of Data Analytics and Intelligent Decision-making</JournalTitle>
				<Issn>3115-8161</Issn>
				<Volume>2</Volume>
				<Issue>3</Issue>
				<PubDate PubStatus="epublish">
					<Year>2026</Year>
					<Month>07</Month>
					<Day>01</Day>
				</PubDate>
			</Journal>
<ArticleTitle>An Integrated Fuzzy Expert-Based Decision Framework for Prioritizing Financial Risk Mitigation Strategies in Uncertain Business Environments</ArticleTitle>
<VernacularTitle></VernacularTitle>
			<FirstPage>256</FirstPage>
			<LastPage>297</LastPage>
			<ELocationID EIdType="pii">4883</ELocationID>
			
<ELocationID EIdType="doi">10.22091/jdaid.2026.17089.1115</ELocationID>
			
			<Language>EN</Language>
<AuthorList>
<Author>
					<FirstName>Majid</FirstName>
					<LastName>Abdi</LastName>
<Affiliation>Assistant Professor, Faculty of Management and Industrial Engineering, Malek Ashtar University of Technology, Tehran</Affiliation>

</Author>
</AuthorList>
				<PublicationType>Journal Article</PublicationType>
			<History>
				<PubDate PubStatus="received">
					<Year>2026</Year>
					<Month>06</Month>
					<Day>05</Day>
				</PubDate>
			</History>
		<Abstract>Objective: This study introduces a fuzzy expert-based framework to prioritize financial risk mitigation strategies under uncertainty. By structuring qualitative expert inputs, the model bridges risk identification with strategic response, offering a transparent, analytical tool for complex financial environments. It enables managers to effectively address critical vulnerabilities and improve organizational resilience. Ultimately, this approach provides a robust, flexible methodology for intelligent financial management and serves as a strong foundation for future research.&lt;br /&gt;Method: The proposed framework establishes a structured, fuzzy multi-criteria decision process to prioritize financial risk mitigation strategies. After identifying key risks and strategies through literature review and expert consultation, financial professionals provide linguistic assessments, which are modeled as fuzzy values to preserve uncertainty. The framework’s logic synthesizes these inputs by deriving risk importance and aggregating strategy performance. This integrated mechanism effectively handles conflicting expert judgments, generating a stable, interpretable ranking that serves as an intelligent prioritization tool for complex financial contexts.&lt;br /&gt;Results: The framework successfully prioritizes financial risk mitigation strategies under uncertainty. Findings identify liquidity risk, inflation, and volatility as critical challenges, while intelligent forecasting, scenario planning, and dynamic cash-flow management emerge as primary mitigation responses. &lt;br /&gt;Conclusions: This study proposes a fuzzy expert-based framework for prioritizing financial risk mitigation strategies under uncertainty. It connects risk identification with strategy evaluation in a transparent model that captures uncertainty and integrates differing expert views. The framework helps managers identify critical vulnerabilities, allocate resources more effectively, and improve financial resilience.</Abstract>
		<ObjectList>
			<Object Type="keyword">
			<Param Name="value">Financial Risk Mitigation</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">Fuzzy Decision-Making</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">Expert-Based Evaluation</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">Multi-Criteria Decision Analysis</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">Financial ResilienceProvide</Param>
			</Object>
		</ObjectList>
<ArchiveCopySource DocType="pdf">https://jdaid.qom.ac.ir/article_4883_8b47cb0e933db644d503132fc3a1d239.pdf</ArchiveCopySource>
</Article>
</ArticleSet>
