Abstract
With the popularity of the Internet and e-commerce, e-commerce system provides users with more choices. While at the same time users may easily lost in the information space of a large number of goods and can’t successfully find their own needed goods. In order to meet the needs of users in this area, the recommendation system arises at the historic moment. This paper extends Davis’s (1989) technology acceptance model (TAM) to find factors influencing users’ adoption intention of e-commerce recommendation system and improve the users’ intention to adopt recommendation system. On the basis of previous studies and related literatures, this paper presents users’ adoption intention model of e-commerce recommendation system and collects 271 valid data in the form of internet survey. Moreover, this paper evaluates the recommendation system adoption model using the path analysis principle, and explores the relationship between external and internal variables included by the model. Finally, according to the analysis results and specific factors, the paper analyses and discusses the research results from two aspects, and proposes the suggestion for improving the adoption of e-commerce recommendation system.
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Gan, X., Jiao, Y., Liu, L., Zhang, Y. (2018). Research on the Factors Influencing Users’ Adoption Intention of E-commerce Recommendation System. In: Tan, Y., Shi, Y., Tang, Q. (eds) Data Mining and Big Data. DMBD 2018. Lecture Notes in Computer Science(), vol 10943. Springer, Cham. https://doi.org/10.1007/978-3-319-93803-5_53
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