Exploring the Relationships Among AI, Agri-food Supply Chain Management Practices, Resilience, and Performance

This study investigates the impact of artificial intelligence (AI) on agri-food supply chain resilience (ASCR) and performance in China's agricultural sector. Using data collected from 194 senior executives of Chinese agri-food companies during August-September 2024, the research examines how organizational factors-top management support (TMS), supplier integration (SI), internal management (IM), customer integration (CI), and supply chain collaboration (SCC)-influence ASCR, and how AI moderates these relationships. Employing partial least squares structural equation modeling (PLS-SEM), the findings reveal that TMS, IM, and CI significantly enhance ASCR, with AI demonstrating a significant moderating effect specifically on the IM-ASCR relationship. The study contributes to understanding how digital transformation through AI can enhance supply chain resilience and performance in the agri-food sector. These findings provide practical insights for agri-food executives in developing effective strategies to improve supply chain resilience and performance through AI integration, particularly in the context of emerging markets.

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Publication Details

Journal
PaperAsia
Published
2025-05-02
DOI
https://doi.org/10.59953/paperasia.v41i2b.364
Citations
1
Primary Topic
Supply Chain Resilience and Risk Management
Type
article
Field-Weighted Citation Impact
2.23

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article

Exploring the Relationships Among AI, Agri-food Supply Chain Management Practices, Resilience, and Performance

May‐Chiun Lo, Abang Azlan Mohamad, Kit Yeng Sin, Fengzhao Yin
1 citations
PaperAsia
Supply Chain Resilience and Risk Management
2.23
article

Exploring the Relationships Among AI, Agri-food Supply Chain Management Practices, Resilience, and Performance

May‐Chiun Lo, Abang Azlan Mohamad, Kit Yeng Sin, Fengzhao Yin
article en
1 citations

Abstract

This study investigates the impact of artificial intelligence (AI) on agri-food supply chain resilience (ASCR) and performance in China's agricultural sector. Using data collected from 194 senior executives of Chinese agri-food companies during August-September 2024, the research examines how organizational factors-top management support (TMS), supplier integration (SI), internal management (IM), customer integration (CI), and supply chain collaboration (SCC)-influence ASCR, and how AI moderates these relationships. Employing partial least squares structural equation modeling (PLS-SEM), the findings reveal that TMS, IM, and CI significantly enhance ASCR, with AI demonstrating a significant moderating effect specifically on the IM-ASCR relationship. The study contributes to understanding how digital transformation through AI can enhance supply chain resilience and performance in the agri-food sector. These findings provide practical insights for agri-food executives in developing effective strategies to improve supply chain resilience and performance through AI integration, particularly in the context of emerging markets.

PaperAsiaVol. 41(2b)
Universiti Malaysia Sarawak (MY), Weifang University of Science and Technology (CN), Weifang University (CN), Sunway University (MY)
Universiti Malaysia Sarawak
Openalex Percentile: Top 12%
Supply Chain Resilience and Risk Management
2.23
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