Evaluating the influence of characteristics on the acceptance of artificial intelligence application: An empirical study

Athapol Ruangkanjanases; Ornlatcha Sivarak; Chin-Tsu Chen; Asif Khan; Shih-Chih Chen

doi:10.1016/j.heliyon.2024.e39460

Evaluating the influence of characteristics on the acceptance of artificial intelligence application: An empirical study

Heliyon. 2024 Oct 17;10(21):e39460. doi: 10.1016/j.heliyon.2024.e39460. eCollection 2024 Nov 15.

Authors

Athapol Ruangkanjanases¹, Ornlatcha Sivarak², Chin-Tsu Chen³, Asif Khan⁴, Shih-Chih Chen⁵

Affiliations

¹ Chulalongkorn Business School, Chulalongkorn University, Bangkok, Thailand.
² Mahidol University International College, Mahidol University, Nakhon Pathom, Thailand.
³ Department of Commercial Design and Management, National Taipei University of Business, Taipei, Taiwan.
⁴ College of Business, Southern Taiwan University of Science and Technology, Tainan, Taiwan.
⁵ Department of Information Management, College of Management, National Kaohsiung University of Science and Technology, Kaohsiung, Taiwan.

Abstract

Artificial intelligence has accelerated the application scenarios and business value of map applications. However, the sustained intention of map applications utilizing artificial intelligence technology has not received sufficient attention and scholarly investigation. Therefore, this study constructs a theoretical model of the continuance intention of map applications, based on their characteristics and combined with user satisfaction and trust, aiming to explore the influence mechanism of this continuance intention. The results of structural equation modeling show that not only user trust and satisfaction have a positive effect on continuance intention towards map applications, but also interactivity characteristics, reliability characteristics, richness characteristics, and personalized characteristics have a positive effect on user satisfaction and trust towards map applications. This study reveals the influence mechanism of map application continuance intention, which can effectively guide map application operators to optimize their services and then provide practical insights for users to use map applications consistently.

Keywords: Artificial intelligence; Continuance intention; Interactivity characteristics; Map APP; Personalized characteristics; Reliability characteristics; Richness characteristics; User satisfaction; User trust.