小农户与大市场的社会网络衔接——以海南省芒果种植户为例
Articulation of Social Networks between Small Farmers and Large Markets:An Empirical Analysis of Mango Growers in Hainan Province
乔丹 1王晓 1徐涛1
作者信息
- 1. 海南大学国际商学院 海南海口 570228
- 折叠
摘要
促进小农户市场参与是推进农业农村现代化和实施乡村振兴战略的重要内容.基于海南省 518 户芒果种植户的实地调查数据,运用有序多分类 Logistic 回归模型,实证分析了社会网络对农户市场参与的影响,并在此基础上检验了市场信息获取的中介作用机制.结果表明:(1)社会网络对农户在生产资料购买和农产品销售方面的市场参与均有显著的正向促进作用;(2)社会网络能够借助中介变量市场信息获取对农户农产品销售产生间接影响,但对生产资料购买则表现为直接影响;(3)年龄、民族和经营规模会带来一定的异质性影响.据此建议:充分发挥农村社会网络的积极作用,完善网络通讯基础设施建设,组织农户开展信息技术应用培训,并将其纳入农户差异化的政策需求,促进小农户与大市场有机衔接.
Abstract
Promoting smallholder market participation is crucial in promoting agricultural and rural modernization and im-plementing the rural revitalization strategy.Based on field survey data from 518 mango farmers in Hainan Province,the im-pact of social networks on farmers'market participation was empirically analyzed using ordered multiclassified logistic re-gression models,and the mediating mechanism of market information acquisition was tested on this basis.The results show that(1)social network has a significant positive effect on farmers'market participation in both the purchase of means of pro-duction and sales of agricultural products;(2)social networks can indirectly affect farmers'sales of agricultural products through the mediating variable of access to market information,but directly affects the purchase of means of production;(3)age,ethnicity,and scale of operation have some heterogeneous effects.Accordingly,it is recommended to give full play to the positive role of rural social networks,improve the construction of network communication infrastructure,organize training in information technology applications for farmers,and incorporate it into the differentiated policy needs of farmers to promote the organic connection between small farmers and large markets.
关键词
市场参与/社会网络/信息获取/芒果种植户/海南省Key words
market participation/social networks/information acquisition/mango growers/Hainan Province引用本文复制引用
基金项目
教育部人文社会科学研究青年基金(19XJC790011)
海南省自然科学基金高层次人才项目(720RC576)
出版年
2023
国家科技期刊平台
NSTL
万方数据