The Influence Of Electronic Commerce Personalized Recommendation System On Consumer Purchase Intention

Personalization Recommendation System is developed by the growth of Internet and E-commerce industry.It is a kind of high-level E-commerce platform based on massive data mining to provide personalized information service and decision making support.In recent years,there is lots of successful cases in industry of large recommendation system.At the meantime,personalized recommendation system is gradually becoming hot spot in academia.However,from the previous studies,the academic community for the personalized recommendation system is still mainly focused on the algorithm level.At the user level,academic research on personalized recommendation system is still inadequate.Therefore,from the perspective of users,this research builds a research model of user behavior using personalized recommendation system based on technology acceptance model and trust theory.Under the online shopping scenario,the questionnaire investigated 266 online shoppers in Tianjin,Zhejiang and other places about personalize system usage behavior and analyze sample data via AMOS.The empirical results show that for the e-commerce platform to provide personalized recommendation system,the user's perceived usefulness and consumer trust will positively affect the user's attitude towards the personalized recommendation system.Perceived usefulness,consumer trust and the attitude of using the consumer will have a positive impact on purchase intention.The main contributions of this research are as follows: a)Explain the impact of personalized recommendation system on purchase intention during the process of online shopping,and expand the scope of application of the technology acceptance model;b)Develop the "personality recommended system of research scale ",and through empirical methods,given the conclusions and management recommendations to help company to better carry out e-commerce business in China.