Risk Management of Import and Export Products Based on Big Data Analysis: Assessment Model with IndetermSoft Set

Authors

  • Ling Chen School of Digital Trade, Zhejiang Yuexiu University, Shaoxing, 312000, Zhejiang, China
  • Chunpeng Liu PhD in Business Administration from Sehan University, Mokpo city, 58447, South Korea

Keywords:

Risk Management; Import and Export Products; Big Data Analysis; IndetermSoft Set

Abstract

: 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.

 

DOI: 10.5281/zenodo.15061751

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Published

2025-05-01

How to Cite

Ling Chen, & Chunpeng Liu. (2025). Risk Management of Import and Export Products Based on Big Data Analysis: Assessment Model with IndetermSoft Set. Neutrosophic Sets and Systems, 82, 742-756. https://fs.unm.edu/nss8/index.php/111/article/view/6053