Understanding the Continuance Intention for Artificial Intelligence News Anchor: Based on the Expectation Confirmation Theory

Abstract

The Metaverse accelerates the development of the meta-human industry and human-AI interactions in both traditional media outlets and online platforms. As a typical application of meta-human, artificial intelligence (AI) news anchors have been gradually utilized for program reports instead of newscasters in China. In this paper, through the lens of expectation confirmation theory, we establish a conceptual model consisting of perceived anthropomorphism (ANT), perceived intelligence (PI), perceived attractiveness (PA), perceived novelty (PN), information quality (IQ), confirmation of expectation (CE), trust (TRU), and satisfaction (SAT) to explore continuous intention (CI) of watching news reported by AI anchors among online users. By leveraging on a sample of 598 eligible questionnaires, the partial least square structural equation model is employed and the results show that the holistic continuing intention for AI news anchor is positive but not robust. Further analysis indicates that SAT, PI, and TRU can predict CI directly, meanwhile CE, ANT, and PA associate with CI through the mediation of satisfaction. In addition, trust and satisfaction serve as serial mediators between IQ and CI. There is no direct relationship between CE & CI, ANT & CI, and PN & SAT. Nevertheless, user gender and previous experience can moderate the relationships of ANT & CI and PN & SAT, respectively. It can be seen that the proposed model can explain 80.1% of the variance in CI. The implications are intended to provide references for further commercialization of AI news anchors.

Keywords

• meta-human
• AI news anchor
• continuance intention
• expectation confirmation model