E-commerce Platform Personalized Recommendation Users To Adopt The Influencing Factors

In recent years,the development of the internet has been more and more vigorous,at the same time,China's e-commerce platform also arises at the historic moment,the e-commerce market scale and the number of users also increase.The scale development of online goods brings more choices to the vast number of e-commerce platform users,but also causes the information overload,which leads to the e-commerce platform users have to spend more time to search and screen information,that have to spend more and more choice cost in searching and screening information.In order to ease the user's information overload,personalized recommendation service is born,and has been gradually implemented in the major e-commerce platforms at home and abroad,and achieved some results.Although the e-commerce platform personalized recommendation algorithm has been improved and optimized,greatly enhancing the accuracy and diversity of the recommendation system,but in the actual application of the recommendation service effect is not as satisfactory as expected.Personalized recommendation service is essentially from the user's own network purchase behavior,whether to adopt recommendation information,so as to provide help for the purchase decision-making process.Information include product attributes is pus through personalized recommendation of e-commerce,which factors affect that adoption of information by users,and which factor lead to the adoption of recommendation information by users still need to be further studied.Firstly,this paper defines the connotation of information adoption of personalized recommendation,and expounds the influencing factors of user acceptance of personalized recommendation service in e-commerce,including: recommendation system factor,user subject factor and social factor;Then on the basis of information adoption theory and research,this paper defines the recommendation information adoption,analyzes the mechanism of information adoption process,discusses the technology acceptance model,constructs the model of personalized recommendation service user information adoption,and constructs the personalized recommendation user information adoption model by combining the integrated technology acceptanceand use model(utaut)from the user level,recommendation system level and adoption level.Then design and put the questionnaire,the questionnaire based on personalized recommended user information adoption model to write,to summarize the background and network use,the questionnaire involves 35 questions,the questionnaire first pre-test,found that Cronbach' s alpha is worth to improve when deleting question 26,question 35,to modify the scale,and then through the sample data of empirical descriptive analysis,reliability analysis,validity analysis and factor analysis.Finally,based on the analysis of the research results,some suggestions are put forward for the improvement of personalized recommendation service of e-commerce websites,and the research limitations and prospects are briefly summarized.