Government subsidy strategy for fresh produce supply chain with AI technology

Purpose This study considers the artificial intelligence (AI) innovation effort and consumers' sensitiveness of the AI innovation effort and aims to investigate the impact of three government subsidy strategies on the decisions of the fresh produce supply chain (FPSC) members and social welfare. Design/methodology/approach The study constructs Stackelberg game models under three scenarios: innovation subsidy, tax subsidy and combined subsidy. The research explores the optimal government subsidy strategy to enhance societal welfare and focus on how different strategies affect equilibrium decisions in the supply chain. Findings The findings reveal that the innovation subsidy prompts the supplier and the retailer to increase the wholesale price and the retail price while encouraging greater AI investment. In contrast, the tax subsidy stabilizes these two prices, reduces fluctuations and preserves market balance. In addition, when the unit subsidy ratio is low, the combined subsidy strategy surpasses a single subsidy by promoting AI adoption and improving supply chain efficiency. As the combined subsidy ratio increases, its marginal contribution to social welfare declines, making the innovation subsidy strategy and the tax subsidy strategy more effective for decision optimization. Originality/value This study contributes to the research on FPSC with AI technology by emphasizing the importance of considering consumer sensitiveness and the unit subsidy ratio as key factors that shape AI innovation effort and government subsidy strategy, ultimately influencing the supply chain efficiency and social welfare. Additionally, it provides a theoretical basis for the government to develop reasonable subsidy strategies.