artificial intelligence capabilities and their influence on supply chain resilience and performance: insights from agri-food firms in an emerging economy

Artificial intelligence (ai) is emerging as a crucial tool to enhance supply chain performance and resilience in global agricultural supply chains, which are being disrupted by market volatility and climate change. this study examines how ai capabilities are used in agribusinesses in vietnam's mekong delta, a growing industry. the study intends to examine how supply chain collaboration (sc), environmental uncertainty (eu), and ai technological compatibility (at) affect willingness to adopt ai (wa), as well as how these factors affect supply chain resilience (sr) and supply chain performance (sp). utilizing the resource-based view (rbv) and the technology–organization–environment (toe) framework, the study sent a questionnaire to 223 businesses, obtaining a 94% valid response rate. this study employs smartpls software to perform analysis based on the partial least squares structural equation modeling (pls-sem) approach. the findings indicate that at, sc, and eu are significant determinants of the readiness for wa, with t-values of 4.822, 6.697, and 4.378, respectively. at the same time, wa has the strongest impact on sr (t-value = 8.031) and also influences sp (t-value = 4.482). the results emphasize the potential of ai to reduce disruptions and enhance operational efficiency, particularly in emerging markets. the study is constrained by its geographical focus on the mekong delta and the reliance on cross-sectional survey data, which limit generalizability and dynamic analysis. future studies should broaden their focus and investigate certain ai technologies to enhance comprehension of ai applications inside agricultural supply chains.