Factors Research On Users’ Adoption Of Online Personalized Recommendation Systems

With the rapid development of the Internet and E-commerce, more and more users begin to favor online shopping. However, the information explosion has also brought about information overload. It is difficult for the users to locate the target goods quickly in the vast amounts of goods and information. E-commerce recommendation system has come into being at the historic moment, and has now become a powerful tool for e-commerce enterprises to solve this difficult problem. Although the personalized recommendation systems have created enormous economic benefits for some businesses, there are still many potential users who have declined to adopt and use them. At present, the systemic research outcomes concerning about the users’ adoption intention of the electronic commerce recommendation system in our country and abroad are few. Nevertheless, it is still necessary to engage in further research on this subject.Based on the previous research outcomes, combined with the characteristics of e-commerce recommendation system, from the perspective of users, this paper aims to improve the Unified Theory of Acceptance and Use of Technology, and to construct the theoretical framework of the users’ adoption intention. For this, it designed measurement scale and investigation questionnaires, put forward 12 basic assumptions, performed questionnaire survey and collected data through the network, and then carried out the empirical analysis. At first, this paper analyzed the questionnaires by using the SPSS20.0 software, including descriptive statistics analysis, the reliability and validity analysis, confirmatory factor analysis, etc. We established the user adoption factors of structural equation model by using AMOS20.0 software. Through the model validation, it evaluated initial SEM model, performed the fitting model correction and path analysis, and tested the significance of each path. Finally, by the analysis of hypothesis test, it made clear about the relationship between each variable factors and the influencing content of users’ adoption intention.After the theoretical research and empirical analysis, the study gets the following conclusions:(1) Performance expectancy, Flow experience, and Social influence have significantly affected on the Users’ adoption intention, and Perceived risk impact the Users’ adoption intention significantly and negatively.(2) Effort expectancy and Self cognition didn’t significantly affect the Users’ adoption intention, Self-cognition had significantly and directly affected the Effort expectancy, and Effort expectancy significantly influences the Users’ adoption intention through the Performance expectancy.(3) Perceived recommending quality impacted the Users’ adoption intention significantly and indirectly, Perceived effective had the positive and significant influence on these three factors: Perceived recommending quality, Performance expectancy and Effort expectancy, it also affected the Users’ adoption intention significantly and indirectly through the Performance expectancy.(4) Users’ adoption intention directly affected the adoption behavior significantly and positively.According to the outcomes of the above empirical research, combined with the status quo of development of China’s e-commerce recommendation system and the respondents’ feedback situation, this paper puts forward targeted measures and suggestions, so as to provide theoretical guidance for increasing the degree of users’ adoption intention and improving the recommendation system function.