Research On The Influence Of E-commerce Platform Personalized Recommendation System On Consumer Purchasing Behavior

With the advent of the Internet age of intelligence,e-commerce also ushers in the explosive development.competition between various e-commerce platform has continued to intensify.With the help of universal use of personalized user data-based recommendation system,the e-commerce platform could attract customer groups better and enhance customer stickiness and save consumers search shopping time,and stimulate consumers' potential consumption.The personalized recommendation system of e-commerce platform recommends the products or services that consumers frequently browse to consumers through the comprehensive analysis of information such as consumers' search traces and consumer goods and specific needs on the e-commerce platform.This can help consumers quickly find services or products they might be interested in on the e-commerce platform and increase the number of effective clicks and promote the e-commerce platform views and sales,thus enhance the consumer's shopping experience and improve consumers' loyalty and satisfaction to e-commerce platform.The existing research on e-commerce platforms focuses on the impact of online reviews on consumers' purchasing behavior and explores the impact of online reviews on consumers' purchasing behavior through e-commerce platforms,combined with consumers' perception of product quality to make the final purchase.The research on the personalized recommendation system of e-commerce platform focuses more on the field of computer and information science,which is mainly from the technical point of view to study how to improve the accuracy of algorithms in the recommendation system,less from the point of view of consumers such as consumers' sensory experience factors in analysis and research.By reviewing the relevant literature and theoretical knowledge,this study chooses the rational behavior theory as the theoretical basis of the study,and takes the behavioral attitude and subjective norm as the main variables.This paper analyzes the influence of e-commerce platform's personalized recommendation system on purchasing decision-making,that is,when the information characteristics of the recommended products are concerned by consumers coincide with the individual needs of consumers,we analyze the impact of online reviews and sales volume and other third-party information on consumer purchasing behavior.Therefore,the research focuses on the mechanism of the impact of technology-based recommendation system on consumers' purchasing behavior.In this study,the main information that consumers pay attention to in the process of e-commerce shopping,such as online reviews,individual demand,sales volume and so on,are taken as the main influencing factors through the questionnaire survey,the basic data of the personalized recommendation system of the consumer purchase experience are obtained and the effect of the personalized recommendation system and the feedback of the consumer purchase behavior to the personalized recommendation system are verified from the consumer's perspective.This study uses structural equation modeling(SEM)to empirically analyze the first part of the research model,that is,the purchase stage hypothesis and uses regression analysis to verify the second part of the feedback stage hypothesis.The conclusions are as follows:Firstly,the personalized recommendation system of e-commerce platform has significant positive influence on individual behavior and subjective norm;secondly,consumer's individual behavior attitude and the subjective norm have the remarkable positive influence on consumer's purchase behavior;thirdly,the effectiveness of consumer's purchase behavior has significant positive influence on the personalized recommendation system of e-commerce platform through consumer individual behavior attitude;finally,the satisfaction with consumer 's purchase behavior has significant positive influence on personalized recommendation system of e-commerce platform through consumer subjective regulation.Finally,according to the research conclusion,the paper puts forward the optimization suggestion to e-commerce platform personalized recommendation system,which has the guidance function to e-commerce platform to enhance its competitive advantage and attract customers.