平台经济下农产品供需匹配模式研究  被引量:2

Research on the Supply and Demand Matching Model of AgriculturalProducts under the Platform Economy

在线阅读下载全文

作  者:张成鹏 张义博[1] 宋霞[2] ZHANG Chengpeng;ZHANG Yibo;SONG Xia

机构地区:[1]国家发展和改革委员会产业经济与技术经济研究所 [2]山东农业大学经济管理学院

出  处:《价格理论与实践》2023年第3期38-43,共6页Price:Theory & Practice

基  金:国家社科基金重大项目“推动现代服务业同先进制造业、现代农业深度融合研究”(批准号:21ZDA027)。

摘  要:农产品线上市场信息不对称导致的逆向选择问题突出,为了满足消费者多样化农产品需求,电商平台探索了分类营销型、主播带货型、线下引流型和数据赋能型为代表的农产品供需匹配新模式。为此,本文以信息经济学中的“信息不对称—逆向选择—信号传递”为理论基础,分别揭示四种农产品新型供需匹配模式的作用机制,并分析四种供需匹配模式的风险点,从而有针对性地提出优化建议:一是建立健全产品品控机制,树立良好信誉;二是加强农民主播扶持力度,优化发展环境;三是减少商品运输销售损耗,降低运营成本;四是优化信息搜集处理方式,避免数据滥用;五是加强政府部门监管力度,保护消费者权益。The adverse selection problem caused by asymmetric information in the online market of agricultural products is promi-nent.In order to meet the diversified agricultural product needs of consumers,the e-commerce platform has explored a new model of agri-cultural product supply and demand matching represented by classified marketing,anchor with goods,offline drainage and data enabling.Therefore,based on the theory of"information asymmetry-adverse selection-signal transmission"in information economics,this paper reveals the mechanism of four new supply and demand matching modes of agricultural products.In addition,this paper analyzes the risk points of the four supply and demand matching models,thus,five targeted optimization suggestions are proposed:First,establish a sound product quality control mechanism and establish a good reputation;Second,strengthen the support for farmers'anchors and optimize the development environment;Third is to reduce the loss of goods transportation and sales,and reduce operating costs;Fourth,optimize infor-mation collection and processing methods to avoid data abuse;Fifth is to strengthen the supervision of government departments and protect consumer rights.

关 键 词:平台经济 农产品 供需匹配 信号传递 

分 类 号:F323.7[经济管理—产业经济] F724.6

 

参考文献:

正在载入数据...

 

二级参考文献:

正在载入数据...

 

耦合文献:

正在载入数据...

 

引证文献:

正在载入数据...

 

二级引证文献:

正在载入数据...

 

同被引文献:

正在载入数据...

 

相关期刊文献:

正在载入数据...

相关的主题
相关的作者对象
相关的机构对象