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ISSN 1995-459X print
E-ISSN 2312-9972 online
ISSN 2500-2597 online English

Leonid Gokhberg


Gaofeng Yi1
  • 1 Higher Education Research Institute,Yancheng Teachers University, Xiwang Avenue, Yancheng City 224051, Jiangsu Province, P. R. China

Why are Some Recommendation Systems Preferred?

2020. Vol. 14. No. 2. P. 76–86 [issue contents]
There has been wide interest in exploring ways to provide more efficient personalized recommendation systems (RSs) in order to attract customers and increase product sales. The majority of the existing researches are concerned with improving the accuracy and effectiveness of the recommendation algorithms, or focusing on how to limit perceived risks, with the aim of increasing consumer satisfaction. Unlike these mentioned studies, this research begins from the perspective of customer-RS interaction, and ends in revealing the mechanisms involved in consumers’ acceptance of recommendations by using the technology acceptance model. The empirical study results show that perceived interpersonal interaction is an important factor that directly affects university students’ intentions to use RS, while perceived ease- of- use influences them in an indirect way through mediation of perceived usefulness. On this basis, the study thus provides suggestions on how to supply an improved interaction with easy and useful personalized RS.
Citation: Yi G. (2020) Why are Some Recommendation Systems Preferred? Foresight and STI Governance, vol. 14, no 2, pp. 76–86. DOI: 10.17323/2500-2597.2020.2.76.86
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