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中国农机化学报

中国农机化学报 ›› 2024, Vol. 45 ›› Issue (7): 302-309.DOI: 10.13733/j.jcam.issn.2095-5553.2024.07.044

• 农业机械化综合研究 • 上一篇    下一篇

生计分化下农户低碳生产技术采纳行为绩效研究

杨义风1,张利新1,王桂霞2   

  1. 1. 河北北方学院经济管理学院,河北张家口,075000; 2. 吉林农业大学经济管理学院,长春市,130118
  • 出版日期:2024-07-15 发布日期:2024-06-25
  • 基金资助:
    河北省教育厅高等学校科学研究项目资助(BJS2023004)

Research on the behavioral performance of farmers low carbon production technology adoption under livelihood differentiation

Yang Yifeng1, Zhang Lixin1, Wang Guixia2   

  1. 1. School of Economics and Management, Hebei North University, Zhangjiakou, 075000, China; 
    2. School of Economics and Management, Jilin Agricultural University, Changchun, 130118, China
  • Online:2024-07-15 Published:2024-06-25

摘要: 为明晰低碳技术采纳行为绩效,推进农户参与低碳化建设,基于695份稻农调研数据,综合运用数据包络分析法和倾向得分匹配法,测算农户低碳生产采纳行为绩效及群体间差异性。结果表明:样本农户的平均生产绩效为0.777 4,消除生产要素错配的影响,尚存在0.222 6的上升空间。低碳农业生产技术影响总样本农户农业生产绩效处理效应系数值均为正,但不显著。不同类型农户低碳农业生产技术采纳对农业生产绩效的影响呈现异质性。生活型、生存型和生产型三类农户采纳技术对农业生产绩效的影响不显著,仅功能型农户可以显著促进农业生产绩效提升。并指出未来需要加强宣传教育技术培训、构建政府与市场协同的农业低碳转型补偿机制、基于农户经营目标异质性分类实施激励政策和配套措施。

关键词: 低碳行为, 技术采纳绩效, 农户生计分化, 数据包络分析法, 倾向得分匹配法

Abstract: In order to clarify the performance of lowcarbon technology adoption behavior and promote farmers' participation in low-carbon construction, based on 695 rice farmer survey data, data envelopment analysis and propensity score matching methods were comprehensively used to calculate the performance of farmers' low-carbon production adoption behavior and group differences. The results indicated that the average production performance of the sample farmers was 0.777 4, and there was still room for an increase of 0.222 6 to eliminate the impact of production factor mismatch. The impact of lowcarbon agricultural production technology on the overall agricultural production performance of sample farmers was positive, but not significant. The impact of lowcarbon agricultural production technology adoption by different types of farmers on agricultural production performance showed heterogeneity. The adoption of technology by three types of farmers such as life type, survival type and production type, had no significant impact on agricultural production performance. Only functional farmers could significantly promote the improvement of agricultural production performance. The research put forward policy recommendations such as strengthening publicity education and technology training, building a collaborative compensation mechanism between the government and the market for agricultural low-carbon transformation, implementing incentive policies and supporting measures based on the heterogeneity of farmers' business objectives.

Key words:  low carbon behavior, technology adoption performance, differentiation of farmers' livelihoods, data envelopment analysis, propensity score matching method

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