农机技术创新影响因素研究综述——基于供给–需求–政策–市场–环境框架

A Review of Factors Influencing Agricultural Machinery Technology Innovation—Based on the Supply-Demand-Policy-Market-Environment Framework

摘要: 农机技术创新是农业机械化高质量发展的核心驱动力，系统梳理其影响因素对推进农业现代化建设具有重要的学术价值。本文从概念内涵与测度方式出发，构建供给–需求–政策–市场–环境五维分析框架，对农机技术创新影响因素的理论机制与实证证据进行了系统综述。研究发现：(1) 研发投入、人力资本和产学研合作构成技术供给端的核心驱动力，其中人力资本的边际贡献高于研发经费；(2) 农业劳动力成本上升与规模化经营通过诱致性技术创新机制显著拉动农机创新需求，但该效应受地形条件约束；(3) 农机购置补贴具有市场扩大与逆向选择的双重效应，知识产权保护薄弱则导致企业倾向于低质量微创新；(4) 市场竞争与创新呈倒U型关系，适度的行业集中有利于提升创新动力；(5) 金融发展、数字技术渗透和农田宜机化条件等外部环境因素的作用日益凸显。在方法层面，现有研究以面板回归和空间计量为主，因果推断方法应用尚处于起步阶段。未来研究应着力于构建整合性理论框架、推进微观层面实证、强化因果识别设计，并重点关注数字技术推动和绿色农机等新兴议题。本文为后续实证研究提供了结构化的文献坐标与方向指引。

Abstract: Agricultural machinery technology innovation is the core driving force for the high-quality development of agricultural mechanization. Systematically sorting out its influencing factors has important academic value for promoting the construction of modern agriculture. Starting from the conceptual connotation and measurement methods, this paper constructs a five-dimensional analysis framework of supply-demand-policy-market-environment, and provides a systematic review of the theoretical mechanisms and empirical evidence of the influencing factors of agricultural machinery technology innovation. The study finds that: (1) R&D investment, human capital, and industry-university-research cooperation constitute the core driving forces on the technology supply side, with the marginal contribution of human capital exceeding that of R&D funding; (2) Rising agricultural labor costs and large-scale operations significantly drive the demand for agricultural machinery innovation through inducement-based technological innovation mechanisms, but this effect is constrained by terrain conditions; (3) Agricultural machinery purchase subsidies have dual effects of market expansion and adverse selection, while weak intellectual property protection leads enterprises to lean toward low-quality incremental innovation; (4) The relationship between market competition and innovation follows an inverted U-shape, and moderate industry concentration is conducive to enhancing innovation motivation; (5) The role of external environmental factors such as financial development, digital technology penetration, and farmland suitability for mechanization is increasingly prominent. Methodologically, existing studies mainly rely on panel regression and spatial econometrics, and the application of causal inference methods is still in its initial stages. Future research should focus on constructing integrated theoretical frameworks, advancing micro-level empirical studies, strengthening causal identification designs, and paying special attention to emerging topics such as digital technology promotion and green agricultural machinery. This paper provides a structured literature map and directional guidance for subsequent empirical research.