When Users Meet AI: Customer Acceptance of Recommendation Systems in Online Shopping
(R2022-111795)

AUTHORS

Vaida Kaduškevičiūtė, Faculty of Economics and Business Administration, Vilnius University; Božena Mackevi?i?t?, Vilnius University

ABSTRACT

Study analyses how a set of factors influences intention to use recommendation. Based on theoretical analysis, Technology Acceptance Model and Theory of Planned Behaviour are employed while investigating this intention. Additionally, privacy risk and trust are chosen as important predictors. Survey revealed that perceived ease of use, perceived usefulness, trust and privacy risk has an impact on, while trust and privacy risks have an impact on perceived behavioural control. Finally, attitude was found out to have a strong impact on intention to use recommendation systems while perceived behavioural control did not have significant impact on intention to use recommendation systems.