Structural model hypothesis testing outcomes.

This research explores the determinants affecting academic researchers’ acceptance of AI writing tools using the Theory of Reasoned Action (TRA). The impact of attitudes, subjective norms, and perceived barriers on researchers’ intentions to adopt these technologies is examined through a cross-sectional survey of 150 researchers. Structural Equation Modeling (SEM) is employed to evaluate the measurement and structural models. Findings confirm the positive influence of favorable attitudes and subjective norms on intentions to use AI writing tools. Interestingly, perceived barriers did not significantly impact attitudes or intentions, suggesting that in the academic context, potential benefits may outweigh perceived obstacles to AI writing tool adoption. Contrarily, perceived barriers do not significantly affect attitudes and intentions directly. The TRA model demonstrates considerable explanatory and predictive capabilities, indicating its effectiveness in understanding AI writing tool adoption among researchers. The study’s diverse sample across various disciplines and career stages provides insights that may be generalizable to similar academic contexts, though further research with larger samples is needed to confirm broader applicability. Results offer practical guidance for tool developers, academic institutions, and publishers aiming to foster responsible and efficient AI writing tool use in academia. Findings suggest strategies such as demonstrating clear productivity gains, establishing AI Writing Tool programs, and developing comprehensive training initiatives could promote responsible adoption. Strategies focusing on cultivating positive attitudes, leveraging social influence, and addressing perceived barriers could be particularly effective in promoting adoption. This pioneering study investigates researchers’ acceptance of AI writing tools using a technology acceptance model, contributing to the understanding of technology adoption in professional contexts and highlighting the importance of field-specific factors in examining adoption intentions and behaviors.本研究基于理性行为理论（Theory of Reasoned Action，TRA），探究影响学术研究者接受人工智能写作工具（AI writing tools）的决定因素。本研究通过对150名研究者开展横断面调查，检验态度、主观规范及感知障碍对研究者采纳此类技术的意向的影响，并采用结构方程模型（Structural Equation Modeling，SEM）评估测量模型与结构模型。研究结果证实，积极态度与主观规范对人工智能写作工具的使用意向具有正向影响。值得注意的是，感知障碍并未对态度或使用意向产生显著影响，这表明在学术场景中，潜在收益或超过人工智能写作工具采纳所面临的感知阻碍；与之相反，感知障碍并未直接显著影响态度与使用意向。理性行为理论模型展现出较强的解释与预测能力，说明其在解析研究者群体对人工智能写作工具的采纳行为方面具备有效性。本研究的样本覆盖多学科领域与不同职业阶段，所得结论可推广至类似学术场景，但仍需开展更大样本量的后续研究以验证其更广泛的适用性。研究结果可为致力于在学术界推广负责任且高效使用人工智能写作工具的工具开发者、学术机构及出版商提供实践指导。研究结果显示，诸如明确展示生产力提升效益、设立人工智能写作工具项目、制定系统化培训计划等策略，可推动负责任的工具采纳；其中，聚焦培育积极态度、利用社会影响力以及应对感知障碍的策略，在促进工具采纳方面或尤为有效。本研究作为一项开创性探索，采用技术接受模型（Technology Acceptance Model）探究研究者对人工智能写作工具的接受度，有助于深化对专业场景下技术采纳行为的认知，并凸显了领域特定因素在检验采纳意向与行为中的重要性。