ORIGINAL RESEARCH article
Front. Sustain. Food Syst.
Sec. Agricultural and Food Economics
Volume 9 - 2025 | doi: 10.3389/fsufs.2025.1591350
This article is part of the Research TopicHarnessing Digital Innovation for Sustainable Agricultural DevelopmentView all 31 articles
"GenAI + Blockchain" to coordinate agricultural supply chains to improve quality trust: an agent-based simulation study
Provisionally accepted
- 1Harbin University of Commerce, Harbin, China
- 2Shandong Technology and Business University, Yantai, Shandong Province, China
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It is important to enhance consumer trust in the product quality of a sustainable agricultural supply chain. However, the frequent occurrence of food safety problems in practice leads to the a lack of public confidence in food safety. To tackle the challenge of quality distrust, we harness the synergistic potential of 'GenAI + Blockchain' technology among industryleading agribusinesses. Three distinct models are constructed to explore the impact of various technological integrations, with a focus on analyzing inventory management, operational efficiency, and precision technology adoption using AnylogicAnyLogic. Our study reveals that (1) Integrating AI and blockchain technology can modulate minimum safety stock, catalyzing leapfrog revenue growth for enterprises. (2) Harnessing artificial intelligence can bolster the agricultural supply chain's overall efficiency, but striving to achieve the highest possible accuracy is not feasible. (3) Gauging consumers' premium for freshness aids companies in targeting key demographics and bolstering quality trust, thus fostering a stable upward trend in sales. By demystifying the underpinnings of minimum safety stock adjustments and the subtle effects of precision technology, our study steers the crafting of advanced inventory strategies and astute technology decisions for innovative agribusinesses.
Keywords: Agricultural supply chain, Quality trust, Blockchain, GenAI, agent-based simulation
Received: 11 Mar 2025; Accepted: 08 Jul 2025.
Copyright: © 2025 Bai, Liu, Wu, Xu and Jiang. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: Wenya Wu, Harbin University of Commerce, Harbin, China
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