Research On Customer Perceived Value Under The Community Supported Agriculture Model

As the people pay more and more attention to the quality and safety of agricultural products,a new agricultural business model that originated in Japan to solve food safety problems began to be introduced to China and developed rapidly.The community-supported agricultural model is a healthy,mutually beneficial and win-win urban-rural integration development model for agricultural consumers and producers.The problem about lack of trust between agricultural producers and consumers and promote the green and healthy development of agriculture will be solved effectively.Sanming is located in a mountainous area.It is the main grain and forest area in Fujian.It has a rich variety of agricultural products.How to promote the high-quality and sustainable agricultural development of Sanming through the community support model has important practical significance.Existing empirical research on customer perceived value under the community-supported agriculture model mainly focuses on the relationship between customer perceived value and consumer behavior,while ignoring the empirical research on the driving factors of customer perceived value.This research uses empirical research on the internal driving factors of customer perceived value under the community-supported agriculture model to further supplement and improve the existing research results in the field of community-supported agriculture.First of all,based on existing research on the theory of customer perceived value,combining with the particularity of community-supported agriculture and related researchers' exploration of customer-perceived value models and factors,a community-supported agriculture model from the two dimensions of profit and loss is designed.The theoretical model of customer perceived value under the CSA customer perception value dimension and hypothesis involved in the model study have two parts.One part is the core variables of the six dimensions of perceived quality value,service value,environmental value and emotional value,price cost and physical cost,and the other part is the structure and assumptions of the influencing factors related to demographic characteristics.So a questionnaire survey to Sanming CSA customers islaunched.Secondly,field investigations on Sanming CSA-type farms are conducted,the status quo of community-supported agricultural development in Sanming City is analyzed,pre-surveys on Shaxian Mayan Farm and Qingfeng Valley Ecological Farm are conducted,and then all CSA-type farm customers in Sanming 284 valid questionnaire data are collectted.The hypothesis was tested by regression analysis,and the empirical results were analyzed.It is found that the factors that affect customer perceived value under the community-supported agriculture model are in descending order: emotional value,environmental value,quality value,service value,physical cost,and price cost.At the same time,SPSS 26.0 statistical software is used to analyze the difference in customer perceived value under demographic sociological variables through independent sample T-test or one-way analysis of variance,it is concluded that women,high monthly incomes,and freelancers have a more significant impact on customer perceived value,There is no significant difference in age and education.Finally,based on the research experience and empirical research results of scholars,and combining with the regional characteristics of Sanming City,using agricultural product traceability and customized production to enhance product value perception,doing a good job in information upgrading and logistics services to enhance service value,and combining local characteristics to achieve brand benefits,improving the image value,strengthening the social attributes of the community,and enhancing the emotional value are proposed.Besides,the cost value perception through personalized pricing is improved and the attractiveness of activities are increased,etc.It is benifical to promote the effectiveness of CSA Sanming's "localization" application.