Risk Management of Import and Export Products Based on Big Data Analysis: Assessment Model with IndetermSoft Set - Ling Chen; Chunpeng Liu (Neutrosophic Sets and Systems)
Risk management in the import and export sector has become increasingly complex due to globalization, technological advancements, and evolving regulatory landscapes. The integration of big data analytics into risk evaluation processes has revolutionized the ability to detect, assess, and mitigate potential threats across international trade operations. This study explores the application of multi-criteria decision-making methods methodologies for assessing risks associated with import and export products, focusing on quality compliance, supply chain vulnerabilities, cybersecurity threats, and regulatory adherence. By leveraging data analytics, businesses and regulatory bodies can enhance decision-making processes, reduce financial losses, and maintain high-quality standards in cross-border trade. We use the IndetermSoft set to deal with indeterminacy in the criteria values. Two MCDM methods are used in this study such as SWARA method to compute the criteria weights and the COPRAS method to rank the alternatives.