摘要
通过对中部生态脆弱地区农民的调查,运用逻辑(Logistic)模型探讨农民采用农业新技术的影响因素。分析结果表明,中部生态脆弱地区农民已经深刻认识到农业科技对于脱贫致富的重要作用,但对农业新技术的采用意愿相对较低。通过进一步对农业新技术采用意愿的影响因素检验,结果发现,农民是否是科技示范户,是否是农业经营大户,是否可以便捷地获取农业科技信息,农民的性别、家庭人均收入、受教育程度,以及是否参加过农业科技培训等因素对农民采用新技术意愿有显著的影响,呈现正相关关系;年龄和外出务工时间对农民采用新技术也有显著的影响,呈现负相关关系;是否村干部,是否具有一定的专业技能对生态脆弱地区农民新技术的采用意愿影响不显著。在此基础上提出相关对策建议。
Based on the survey of farmers in China's central ecologically fragile areas,the influential factors on farmers' adopting new agricultural technologies from the use of Logistic Model is discussed.The results show that the farmers in China's central ecologically fragile areas have low will to use new agricultural technology,although they have a profound understanding of the important role of science and technology for poverty alleviation.Through further study of impact factors in farmers' will to use new agricultural technology,the following factors have significant effects on farmers' willing to adopt new agricultural technology are found,showing a positive correlation: whether the farmers were science and technology demonstration households or large agricultural operations,whether they could easily access information on agricultural technology,participate in agricultural training or not,farmers' sex,family income,and educational level,participate in agricultural training or not and other factors,have significant effects on farmers' willing to adopt new agricultural technology,showing a positive correlation.Age and migrant workers time have a significant impact for farmers to adopt new technologies,showing a negative correlation.Being village cadres or not,and having certain professional skills or not had no obvious effects upon the farmers' adoption of new agricultural technologies.Basing on the analysis we give some relevant suggestions.
出处
《生态经济》
北大核心
2011年第5期84-88,共5页
Ecological Economy
基金
农业部软科学"县域经济发展与中部崛起研究"(Z201011)
国家软科学"我国农业科技工作者知识创新行为研究:基于社会网络的视角"(2009GXQ6D175)
关键词
中部生态脆弱地区
农业新技术
采用意愿
影响因素
ecologically fragile areas in central China
new agriculture technology
adoption willingness
impact factors