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农业数字化驱动农业新质生产力培育的多元路径研究基于动态QCA的组态分析

Research on multiple paths of agricultural digitalization driving cultivation of new quality agricultural productivity: a dynamic QCA configuration analysis

  • 摘要: 随着数字技术快速发展和农业现代化需求不断提升,农业数字化成为推动农业高质量发展的关键路径。本文基于2016—2022年中国省级面板数据,依托“技术-组织-环境”框架(TOE框架),运用动态定性比较分析(QCA)方法,从时空维度系统考察了数字技术、数字组织与数字环境在农业数字化驱动农业新质生产力培育中的多因素联动效应,明确了培育高水平农业新质生产力的多元路径。研究发现,实现高水平农业新质生产力需依靠多因素协同作用,技术条件与组织条件存在一定替代效应,农业产业数字化转型在生产力培育中作用较弱;高水平农业新质生产力的培育路径多样,主要包括“技术-组织替代型”“环境主导型”及“技术主导型”三类组态;此外,农业新质生产力发展呈现明显时间效应,部分组态路径存在动态演化,且各省份在农业数字化高水平和低水平地区适用的组态路径存在差异。相关结论为各地因地制宜推进农业数字化发展、培育农业新质生产力提供了理论依据和政策参考。

     

    Abstract: With the rapid development of digital technology and the growing demand for agricultural modernization, agricultural digitization has become a critical pathway for promoting high-quality agricultural development. Based on provincial panel data from 30 provinces in China from 2016 to 2022, this study adopts the “Technology–Organization–Environment” (TOE) framework and applies a dynamic Qualitative Comparative Analysis (QCA) method to systematically examine the multi-factor linkage effects of digital technology, digital organization, and digital environment in driving the cultivation of new quality agricultural productivity from both spatial and temporal dimensions. The results identify multiple configurations for achieving high-level new quality agricultural productivity. The study finds that the cultivation of such productivity relies on the synergistic effects of multiple factors, with a substitution effect observed between technological and organizational conditions, while the digital transformation of the agricultural industry plays a relatively limited role. The identified configurations include three main types: technology–organization substitution, environment-led, and technology-led. Furthermore, the development of new quality agricultural productivity exhibits significant temporal characteristics, with some configurations undergoing dynamic evolution. There are also notable differences in applicable configuration paths between regions with high and low levels of agricultural digitization. These findings provide a theoretical foundation and policy reference for promoting region-specific digital agricultural development and cultivating high-level new quality agricultural productivity.

     

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