Platform-led or firm-led? An analysis of artificial intelligence development strategies in agricultural supply chains

Agriculture experiences substantial yield losses due to pests and diseases, underscoring a need for advanced solutions such as artificial intelligence (AI). This study examines a contract farming supply chain with an agriculture firm and a platform, focusing on AI’s role in reducing these losses. Using game theory, we explore AI development conditions and compare two AI development modes: one where the agriculture firm develops AI (firm-led), and another where the platform undertakes AI development (platform-led). We also evaluate the effects of yield uncertainty, AI development efficiency, and firm’s planting effort efficiency on these strategies. Our findings reveal several key insights. First, in the firm-led mode, when AI enhances the firm’s planting effort efficiency, the firm always benefits, whereas only low AI development efficiency is beneficial to the platform. When AI reduces effort efficiency, only high development efficiency is advantageous to both parties. Second, in the platform-led mode, when AI improves planting effort efficiency, the outcomes are reversed compared to the firm-led mode. When AI reduces effort efficiency, only a moderate development efficiency is beneficial to the firm. Interestingly, in cases where AI significantly lowers effort efficiency, the platform consistently benefits. Third, the platform always tends to choose the platform-led mode, whereas the firm chooses this mode only when AI development efficiency is low. Additionally, the higher the average yield reduction rate, the greater the role of AI, the more likely the firm is to choose the firm-led mode. These insights contribute to a deeper understanding of AI development strategies in agricultural supply chains. • We investigate a contract farming supply chain that uses AI to mitigate yield losses. • We analyze two AI development modes: platform-led and agricultural firm-led modes. • An extremely high development efficiency can harm the platform in the firm-led mode. • Only platform-led mode can achieve win-win situation and raise AI development level. • Higher disaster occurrence probability, more likely firm is to choose firm-led mode.

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Publication Details

Journal
International Journal of Production Economics
Published
2025-11-20
DOI
https://doi.org/10.1016/j.ijpe.2025.109861
Citations
1
Primary Topic
Supply Chain and Inventory Management
Type
article
Field-Weighted Citation Impact
2.28
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article

Platform-led or firm-led? An analysis of artificial intelligence development strategies in agricultural supply chains

Yanglei Li, Changhua Liao, Victor Shi, Qihui Lu
1 citations
International Journal of Production Economics
Supply Chain and Inventory Management
2.28
article

Platform-led or firm-led? An analysis of artificial intelligence development strategies in agricultural supply chains

Yanglei Li, Changhua Liao, Victor Shi, Qihui Lu
article en
1 citations

Abstract

Agriculture experiences substantial yield losses due to pests and diseases, underscoring a need for advanced solutions such as artificial intelligence (AI). This study examines a contract farming supply chain with an agriculture firm and a platform, focusing on AI’s role in reducing these losses. Using game theory, we explore AI development conditions and compare two AI development modes: one where the agriculture firm develops AI (firm-led), and another where the platform undertakes AI development (platform-led). We also evaluate the effects of yield uncertainty, AI development efficiency, and firm’s planting effort efficiency on these strategies. Our findings reveal several key insights. First, in the firm-led mode, when AI enhances the firm’s planting effort efficiency, the firm always benefits, whereas only low AI development efficiency is beneficial to the platform. When AI reduces effort efficiency, only high development efficiency is advantageous to both parties. Second, in the platform-led mode, when AI improves planting effort efficiency, the outcomes are reversed compared to the firm-led mode. When AI reduces effort efficiency, only a moderate development efficiency is beneficial to the firm. Interestingly, in cases where AI significantly lowers effort efficiency, the platform consistently benefits. Third, the platform always tends to choose the platform-led mode, whereas the firm chooses this mode only when AI development efficiency is low. Additionally, the higher the average yield reduction rate, the greater the role of AI, the more likely the firm is to choose the firm-led mode. These insights contribute to a deeper understanding of AI development strategies in agricultural supply chains. • We investigate a contract farming supply chain that uses AI to mitigate yield losses. • We analyze two AI development modes: platform-led and agricultural firm-led modes. • An extremely high development efficiency can harm the platform in the firm-led mode. • Only platform-led mode can achieve win-win situation and raise AI development level. • Higher disaster occurrence probability, more likely firm is to choose firm-led mode.

International Journal of Production EconomicsVol. 291
Southwestern University of Finance and Economics (CN), Zhejiang Gongshang University (CN), Wilfrid Laurier University (CA), South China University of Technology (CN)
Openalex Percentile: Top 8%
Supply Chain and Inventory Management
2.28
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