The Study Of Influencing Factors And Index System Of C2C Online Shop Sales Volume Based On The Soft Set Theory

With the constant improvement of electronic commerce and electronic business logistics,online shopping has become a national consumption habit in China.Among them,C2 C mode is the main mode of electronic commerce,which occupies half of the online shopping market share.With the influx of personal shops,the competition of C2 C e-commerce has become increasingly fierce.The steady growth of online sales has become the key for online shops to stand firm.However,there are a lot of stimulating factors on consumers in the online shopping,including customer service attitude,product description,shipping-free service,payment methods,etc.Consumers always tend to buy or give up buying due to one of the above factors.In the face of limited resources,the individual sellers cannot be good at all the simulating factors.Therefore,exploring the key factors affecting the net sales has become very necessary to help sellers achieve scientific decision-making.In addition,the influencing factors of the online shops have the characteristics of complexity and fuzziness in the C2 C e-commerce.So the traditional reduction methods are not applicable.In view of this,this paper attempts to use soft set,a new mathematical tool that can deal with uncertain problems,to study the key factors affecting the C2 C e-commerce shop sales,in order to provide some theoretical support and policy recommendations for the C2 C shop operators.Firstly,through the summary of related literature collation and personal interviews,this paper constructs an index system composed of 56 indicators,which can offer a comprehensive description of influencing factors on C2 C online shop sales.It lays the foundation of the reduction work.Secondly,by using the soft set theory,it builds a C2 C online shop sales volume influencing factor index system reduction model based on soft set step by step.The weight quantization model of the important index after reduction is also discussed.Subsequently,through a random survey of 80 Internet users,the first hand data has been collected for an empirical study.Through the application of C2 C online shop sales volume influencing factor index system reduction model based on soft set,the eight key indicators affecting the online shop sales volume have been determined.The objective weight of the eight reduction results has been obtained further.Finally,according to the results of this empirical study,the management inspiration for the shop operators is provided.The empirical research shows that the C2 C e-commerce online shop sales volume influencing factor index system reduction model based on soft set constructed by this paper can be applied in determining the important factors of the C2 C e-commerce online shop sales volume.The results of empirical research show that “the nice attitude and patience of customer service”,“the customer service sales”,“package discount” and other eight factors are important indicators affecting the online shop sales volume.Besides,the results of weight quantization of important indicators show that the service attitude is the most important.The second important is the package discount.The research results not only provide reference value and reference significance for the marketing of personal online shop operators,but also be beneficial to the development of electronic commerce and electronic commerce logistics.