Efficiency Evaluation and Regional Disparities of Green Agricultural Product Supply Chains: A Case Study of Hebei Province, China

Building a sustainable and efficient green agricultural product supply chain (GASC) is crucial for ensuring global food security and promoting environmental sustainability. However, at the regional level, the spatial differentiation patterns of its efficiency and underlying driving mechanisms—particularly the synergistic relationship between technical efficiency and scale efficiency—remain to be elucidated. This study focuses on Hebei Province, a key agricultural region in China. By constructing a multidimensional evaluation index system and employing a two-stage approach combining Principal Component Analysis (PCA) with Data Envelopment Analysis (DEA), we measure and analyze the operational efficiency and regional disparities of green agricultural product supply chains across 11 prefecture-level cities. Findings revealed that the overall efficiency of Hebei’s green agricultural product supply chains required improvement and exhibited a distinct spatial pattern characterized by “high-efficiency dominance with localized lags.” The core bottleneck lies in the failure of most regions to achieve effective synergy between technology and scale, resulting in widespread resource misallocation—either “technology without scale” or “scale without technology”—and causing some areas to experience diminishing returns to scale. Furthermore, excessive reliance on single factor advantages in many cities reveals structural vulnerabilities within their supply chain systems. This study’s primary contribution lies in deepening the understanding that efficiency cannot be driven by technology or scale alone. It theoretically emphasizes that the synergistic coupling of “technology-scale” is key to enhancing the efficiency of regional green agricultural product supply chains. These findings provide empirical evidence and policy insights for building a more resilient and balanced regional green agricultural system.