The digital economy is emerging as a crucial force restructuring global agricultural resources,reshaping the global agricultural economic landscape,and altering the global agricultural competitive dynamics.For Cross-border Agri-food Supply Chains(CASCs),the chain structure of cross-bor-der agricultural products is more vulnerable compared to other supply chains due to the inherent char-acteristics of agricultural products,including perishability,seasonality,and cyclicality.To propel the digital transformation of cross-border agricultural products,it is essential to effectively identify and predict the risk factors during the digitalization process.Based on the TOE framework,this paper cate-gorizes three dimensions of risk manifestations in enterprise digital transformation.Drawing on surveys of core enterprises and members of cross-border agri-food supply chains,Principal Component A-nalysis(PCA)is employed to reduce the dimensionality of the raw data.Subsequently,a Backpropaga-tion Neural Network(BPNN)is constructed to predict the risks in the digitalization of CASCs.The re-sults indicate that the chosen four principal components are reasonable,and the evaluation indicator system is valuable.The study provides new insights for cross-border agricultural supply chains.
维普
万方数据