关键词: 数字物流, 农业产业链现代化, 资源配置效率, 市场可达性, 创业活跃度, 中介效应模型

Abstract:

[Objective] Enhancing the modernization level of China's agricultural industry chain and supply chain is a crucial strategy for enabling the high-quality development of the rural economy. In the context of digital transformation, understanding the role of digital logistics in this process is of paramount importance. The purpose of this research is to systematically investigate the impact, mechanisms, heterogeneity, and spatial spillover effects of digital logistics on the modernization of the agricultural industry chain. [Methods] Panel data from 280 prefecture-level cities in China spanning the period from 2011 to 2023 were used as the basis for this research. Firstly, the entropy method was employed to construct comprehensive measurement indices for digital logistics and the modernization level of the agricultural industry chain. To empirically examine the relationship between digital logistics and agricultural industry chain modernization, a panel fixed-effects model was utilized. Furthermore, a mediation effect model was constructed to explore the underlying mechanisms through which digital logistics exerts its influence. Finally, to account for spatial interdependence, a spatial Durbin model (SDM) was applied to analyze the spatial correlation characteristics and spillover effects of digital logistics on agricultural industry chain modernization. [Results and Discussions] The empirical analysis yielded several key findings: (1) Baseline effect: Digital logistics significantly contributed to advancing the modernization of the agricultural industry chain. This positive effect remained robust and valid after a series of rigorous robustness checks, including substituting variables, adjusting sample periods, and excluding particular cities, as well as after addressing potential endogeneity concerns through instrumental variable methods. (2) Mechanism analysis: The mediation effect analysis revealed that digital logistics promoted agricultural industry chain modernization through three primary channels of improving resource allocation efficiency, enhancing market accessibility, and boosting entrepreneurial activity. Specifically, digital logistics reduced information asymmetry and transaction costs, leading to a more efficient distribution of production factors; extended market reach for agricultural products; and lowered entry barriers, stimulating local entrepreneurship. (3) Heterogeneity analysis: The impact of digital logistics was not uniform across different regions. The heterogeneity test results demonstrated that the promoting effect of digital logistics on agricultural industry chain modernization was significantly stronger in the southern region compared to the northern region. Additionally, the effect was more pronounced in non-major grain-producing areas than in major grain-producing areas. Regarding the level of agricultural agglomeration, the positive impact of digital logistics was greater in regions with a high degree of agricultural industry agglomeration, suggesting that the benefits of digital logistics were amplified in areas with established industrial clusters. (4) Spatial spillover effects: The spatial econometric analysis revealed a non-linear spatial spillover pattern. The results indicated that the spatial spillover effect of digital logistics on the modernization of the agricultural industry chain in neighboring regions shifted from a negative effect to a positive effect as the spatial distance increased. This transition was observed approximately within the range of 0 to 600 km. Notably, the largest positive spatial spillover effect was detected at a distance of around 800 km, implying that the beneficial impacts of digital logistics in one city could significantly enhance the agricultural industry chain modernization of other cities located approximately 800 km away. [Conclusions] Based on these findings, several policy recommendations are proposed. First, it is essential to strengthen the empowerment of digital and intelligent technologies within the agricultural logistics system. Second, efforts should be made to dismantle "institutional barriers" and eliminate external obstacles that hinder the improvement of resource allocation efficiency. Third, policies should be tailored to local conditions, leveraging the role of digital logistics in optimizing the modernization of the agricultural industry chain according to the specific characteristics of different production areas.

Key words: digital logistics, modernization of the agricultural industry chain, resource allocation efficiency, market accessibility, entrepreneurial activity, mediation effect model