技术接受模型
创造力
可用性
计算机科学
结构方程建模
考试(生物学)
心理学
知识管理
人机交互
社会心理学
机器学习
生物
古生物学
作者
Junping Xu,Xiaolin Zhang,Hui Li,Chaemoon Yoo,Pan Younghwan
摘要
Artificial Intelligence (AI) applications in different fields are developing rapidly, among which AI painting technology, as an emerging technology, has received wide attention from users for its creativity and efficiency. This study aimed to investigate the factors that influence user acceptance of the use of AIBPS by proposing an extended model that combines the Extended Technology Acceptance Model (ETAM) with an AI-based Painting System (AIBPS). A questionnaire was administered to 528 Chinese participants, and validated factor analysis data and Structural Equation Modeling (SEM) were used to test our hypotheses. The findings showed that Hedonic Motivation (HM) and Perceived Trust (PE) had a positive effect (+) on users’ Perceived Usefulness (PU) and Perceived Ease of Use (PEOU), while Previous Experience (PE) and Technical Features (TF) had no effect (−) on users’ Perceived Usefulness (PU). This study provides an important contribution to the literature on AIBPS and the evaluation of systems of the same type, which helps to promote the sustainable development of AI in different domains and provides a possible space for the further extension of TAM, thus helping to improve the user experience of AIBPS. The results of this study provide insights for system developers and enterprises to better motivate users to use AIBPS.
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