LAUSR

Based on Chinese provincial panel data (2011–2020), the CRITIC-EWM, kernel density estimation, Dagum Gini coefficient and a spatial Dubin model were used for analyzing endogenous and exogenous factors to enhance grain supply chain resilience. The results illustrated the following: (1) Ensuring the resilience of the grain supply chain’s ability to digest, recover and learn was fundamental to internal system robustness. (2) Overall, China’s grain supply chain resilience increased year over year, but the growth rate was low and showed an attenuation trend of east-middle-west. (3) There was a significant spatial positive correlation among provinces and grain supply chain resilience, however, the large gap and slow development led to the formation of polarization with high-high and low-low clusters. (4) The exogenous drivers were all significant and had a significant positive spillover effect on the grain supply chain resilience. (5) Subregional regressions reflected the heterogeneity of the influence factors, which highlighted the implementation of targeted strategies as the key to achieving synergy.