摘要
[目的/意义]探究研究生对生成式人工智能(GAI)的采纳行为,以促进其在学术科研领域的应用与发展。[方法/过程]整合基于技术接受模型框架下的TAME-ChatGPT理论与任务技术匹配理论,从用户内部感性与外部理性双重视角出发,构建了研究生用户采纳行为影响因素模型,运用问卷调查收集数据,并采用结构方程模型理论进行验证分析。[结果/结论]研究生对GAI的实际使用行为主要受其使用意愿驱动,其中感知有用性是最关键的驱动因素,其次是社会影响和感知易用性;TTF模型通过任务技术匹配度对实际使用行为产生积极影响,并能抑制感知风险的产生;此外,研究还发现个体焦虑对感知风险呈正相关。研究结果可为GAI的理论研究和实践发展提供启示。
[Purpose/significance]This paper explores the adoption behavior of graduate students towards Generative Artificial In-telligence(GAI),in order to promote its application and development in the field of academic research.[Method/process]Integrating the TAME-ChatGPT theory based on the framework of technology acceptance model and task-technology matching theory,this paper constructs a model of influencing factors of graduate student users’adoption behavior from the dual perspectives of users’internal per-ceptual and external rationality,collects the data by questionnaire survey,and uses the theory of Structural Equation Model for validation and analysis.[Result/conclusion]Graduate students’actual use behavior of GAI is mainly driven by their willingness to use it,in which perceived usefulness is the most critical driving factor,followed by social influence and perceived ease of use;The TTF model positively influences the actual use behavior through the task-technology matching degree and inhibits the generation of perceived risk;Moreover,the study finds that individual anxiety is positively correlated with perceived risk.The results of the study can provide insights for the theoretical research and practical development of GAI.
作者
马凤
黎阳
Ma Feng;Li Yang(School of Economics and Management,Anhui Agricultural University,Hefei Anhui 230036)
出处
《情报探索》
2025年第4期1-9,共9页
Information Research
基金
国家自然科学基金项目“基于引用模式分析的学术影响力研究”(项目编号:61702009)成果之一。
关键词
生成式人工智能
用户信息行为
研究生
结构方程模型
generative artificial intelligence
users’information behavior
graduate student
Structural Equation Model
作者简介
马凤(1984-),女,博士,副教授,主要研究方向为信息计量与科学评价、技术创新管理,已发表论文30余篇;黎阳(2001-),男,2023级硕士研究生,主要研究方向为用户信息行为。
