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Abstract
The application of blockchain technology holds significant potential for improving efficiency, resilience, and transparency within the Fisheries Supply Chain (FSC). This study addresses the critical barriers hindering the adoption of blockchain technology (BT) in the Chinese FSC, recognizing the unique challenges posed by its intricacies. Through a comprehensive literature review, fourteen Critical Barrier Factors (CBFs) were identified, and a grey Delphi method was employed to distill this set. Five pivotal CBFs emerged, including "Regulatory Compliance," "Cost of Implementation," and "Complex Supply Chain Network". A subsequent grey Decision-Making Trial and Evaluation Laboratory (DEMATEL) analysis revealed the causal relationships among these factors, categorizing them into effect and cause groups. "Regulatory Compliance," "Cost of Implementation," and "Complex Supply Chain Network" were identified as primary influencing factors demanding attention for effective BT integration in the FSC. The findings serve as a valuable resource for FSC stakeholders, assisting in prioritizing efforts to address these barriers. The discerned causal relationships provide guidance for managers in optimizing resource allocation. Ultimately, this research advocates for the adoption of blockchain technology in the fisheries supply chain to enhance overall performance and operational efficiency.
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Details
1 Shandong University of Technology, School of Economics, Zibo, People’s Republic of China (GRID:grid.412509.b) (ISNI:0000 0004 1808 3414)
2 United Arab Emirates University, College of Business and Economics, Al Ain, UAE (GRID:grid.43519.3a) (ISNI:0000 0001 2193 6666)
3 Shandong University of Technology, School of Mechanical Engineering, Zibo, China (GRID:grid.412509.b) (ISNI:0000 0004 1808 3414)
4 Shandong University of Technology, College of Agricultural Engineering and Food Science, Zibo, China (GRID:grid.412509.b) (ISNI:0000 0004 1808 3414)
5 King Saud University, Department of Agricultural Economics, College of Food and Agricultural Sciences, Riyadh, Saudi Arabia (GRID:grid.56302.32) (ISNI:0000 0004 1773 5396)
6 King Saud University, Plant Production Department, College of Food and Agricultural Sciences, Riyadh, Saudi Arabia (GRID:grid.56302.32) (ISNI:0000 0004 1773 5396)