Explained variance table.

With the rapid development of AI intelligent technology, AIGC can bring an innovative revolution to art creation, providing designers with unlimited possibilities but also challenges. These challenges affect the willingness to adopt and constrain the sustainable development of AIGC. The purpose of this study is to analyse the factors of designers’ adoption intention behaviours. This study reconstructed the research model by combining the factors of AIGC technology characteristics and interactivity, technology acceptance model, technology readiness model, etc. The empirical study was conducted from the dual perspectives of AIGC application characteristics and designers’ psychology, in order to predict the factors that predict designers’ behavioural intentions to use AIGC. In this study, a questionnaire survey was conducted among designers in China and 462 valuable responses were received. Through structural equation modelling (SEM) analysis, the study found that: (1) AIGC’s technical features and interactivity positively affect perceived ease of use, and perceived usefulness, but the interactive features do not directly affect perceived usefulness; perceived ease of use and perceived usefulness positively affect designers’ intention to adopt AIGC applications; (2) optimism and innovation positively affect technical features and designers’ intention to adopt; Insecurity negatively affects designers’ willingness to adopt, and insecurity does not affect technical features; discomfort does not affect designers’ technical features and willingness to adopt. This study further extends the theoretical models of TAM(Technology Acceptance Model) and TRI(Technology Readiness Model), provides a theoretical basis for studying designers’ adoption behaviour of AIGC, and enriches the application groups and domains of the theoretical models of TAM and TRI. The results of this study provide inspiration for the development, design, and marketing of AIGC applications, contributing to the realisation and further adoption of AIGC applications, as well as to the professional development of designers.

伴随人工智能技术的迅猛发展，人工智能生成内容（Artificial Intelligence Generated Content，AIGC）为艺术创作领域带来了颠覆性的创新变革，在为设计师提供广阔创作可能的同时，也衍生出诸多挑战。这些挑战不仅会削弱设计师对AIGC的采纳意愿，更会制约AIGC的可持续发展。本研究旨在剖析影响设计师采纳AIGC意愿的行为驱动因素。本研究结合AIGC技术特性与交互性维度、技术接受模型（Technology Acceptance Model，TAM）、技术准备度模型（Technology Readiness Model，TRI）等理论框架，重构了相关研究模型。本研究从AIGC应用特性与设计师心理双重视角开展实证研究，以期识别能够有效预测设计师使用AIGC行为意向的影响因素。本研究面向中国境内设计师群体发起问卷调查，最终回收有效问卷462份。通过结构方程模型（Structural Equation Modelling，SEM）分析，本研究得出以下核心结论：（1）AIGC的技术特性与交互性均对感知易用性、感知有用性产生显著正向影响，但交互特性并未直接作用于感知有用性；感知易用性与感知有用性均正向影响设计师对AIGC应用的采纳意向；（2）乐观性与创新性分别对技术特性及设计师采纳意向产生正向影响；不安全感负向影响设计师的采纳意愿，但未对技术特性产生显著作用；不适感未对技术特性与设计师采纳意愿产生显著影响。本研究进一步拓展了技术接受模型与技术准备度模型的理论应用边界，为探究设计师对AIGC的采纳行为提供了坚实的理论依据，同时丰富了TAM与TRI理论模型的应用群体与研究场景。本研究结论可为AIGC应用的开发、设计与营销提供实践启示，有助于推动AIGC应用的落地推广与进一步普及，同时助力设计师群体的专业能力提升与职业发展。