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Review

Understanding Users’ Acceptance of Artificial Intelligence Applications: A Literature Review

1
School of Information Science and Engineering, NingboTech University, Ningbo 315100, China
2
Nottingham University Business School China, University of Nottingham Ningbo China, Ningbo 315100, China
3
Business School, Ningbo University, Ningbo 315211, China
4
School of Management, Zhejiang University, Hangzhou 310058, China
*
Author to whom correspondence should be addressed.
Behav. Sci. 2024, 14(8), 671; https://doi.org/10.3390/bs14080671
Submission received: 24 June 2024 / Revised: 30 July 2024 / Accepted: 1 August 2024 / Published: 2 August 2024
(This article belongs to the Topic Online User Behavior in the Context of Big Data)

Abstract

In recent years, with the continuous expansion of artificial intelligence (AI) application forms and fields, users’ acceptance of AI applications has attracted increasing attention from scholars and business practitioners. Although extant studies have extensively explored user acceptance of different AI applications, there is still a lack of understanding of the roles played by different AI applications in human–AI interaction, which may limit the understanding of inconsistent findings about user acceptance of AI. This study addresses this issue by conducting a systematic literature review on AI acceptance research in leading journals of Information Systems and Marketing disciplines from 2020 to 2023. Based on a review of 80 papers, this study made contributions by (i) providing an overview of methodologies and theoretical frameworks utilized in AI acceptance research; (ii) summarizing the key factors, potential mechanisms, and theorization of users’ acceptance response to AI service providers and AI task substitutes, respectively; and (iii) proposing opinions on the limitations of extant research and providing guidance for future research.
Keywords: AI; user acceptance; AI service provider; AI task substitute; systematic literature review AI; user acceptance; AI service provider; AI task substitute; systematic literature review

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MDPI and ACS Style

Jiang, P.; Niu, W.; Wang, Q.; Yuan, R.; Chen, K. Understanding Users’ Acceptance of Artificial Intelligence Applications: A Literature Review. Behav. Sci. 2024, 14, 671. https://doi.org/10.3390/bs14080671

AMA Style

Jiang P, Niu W, Wang Q, Yuan R, Chen K. Understanding Users’ Acceptance of Artificial Intelligence Applications: A Literature Review. Behavioral Sciences. 2024; 14(8):671. https://doi.org/10.3390/bs14080671

Chicago/Turabian Style

Jiang, Pengtao, Wanshu Niu, Qiaoli Wang, Ruizhi Yuan, and Keyu Chen. 2024. "Understanding Users’ Acceptance of Artificial Intelligence Applications: A Literature Review" Behavioral Sciences 14, no. 8: 671. https://doi.org/10.3390/bs14080671

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