基于熵权-TOPSIS法的农业新质生产力评价与障碍分析

Multidimensional measurement and obstacle mechanisms of new quality productive forces in agriculture based on entropy weight-TOPSIS method

  • 摘要: 农业生产力是社会生产力中最传统、最基础, 也是最薄弱的部分, 因而农业也是发展新质生产力任务最繁重、前景最广阔的领域。为探究农业新质生产力发展水平, 本文从高素质劳动者、高科技含量劳动资料、广范围劳动对象入手构建农业新质生产力评价指标体系, 运用2013—2022年省际面板数据对农业新质生产力展开测度及时空特征分析。研究发现: 1)全国农业新质生产力发展在总体上呈现出增长趋势, 年均增长率为3.26%, 但整体水平偏低, 在0.12~0.18之间; 农业新质生产力发展水平一直表现为东部>中部>东北部>西部。2) 2013—2022年农业新质生产力各地区内部不平衡趋势逐渐扩大, 尤其是西部和东北地区多极分化明显。3)影响农业新质生产力发展的主要因素依次为产业融合水平、机械化、数字化和农村教育水平。基于此得出以下政策启示: 加强数据监测与评估机制, 制定地区发展差异化政策, 支持农业农村产业集群发展, 推动农业科技创新与人才培养协同发展。

     

    Abstract: Agricultural productivity represents the most traditional, fundamental, and yet most vulnerable component of social productivity, making agriculture both the most challenging and the most promising field for developing new quality productive forces. To explore the development level of new quality productive forces in agriculture, this study constructs an evaluation index system from three dimensions: a high-caliber workforce, technology-intensive means of production, and diverse subjects of labor. Using inter-provincial panel data from 2013 to 2022, we measure the new quality productive forces in agriculture and analyze their spatiotemporal characteristics and obstacle factors. The findings are as follows: 1) the development level of new quality productive forces in agriculture shows an overall upward trend nationwide, with an average annual growth rate of 3.26%. However, the overall level remains relatively low, ranging between 0.12 and 0.18. Regionally, the development level consistently follows the pattern: Eastern China > Central China > Northeastern China > Western China. 2) From 2013 to 2022, regional disparities within each area had gradually widened, with notable polarization in Western and Northeastern China. There had been positive spatial correlation among provinces (autonomous regions and municipalities), indicating strong spatial clustering. 3) The primary factors influencing the development of new quality productive forces in agriculture are, in descending order, industrial integration level, mechanization, digitization, and rural education level. Based on these findings, the following policy implications are proposed: to strengthen the data monitoring and evaluation mechanisms; to formulate differentiated regional development policies; to support the development of agricultural and rural industrial clusters; and to promote the coordinated advancement of agricultural technological innovation and talent cultivation.

     

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