The Impact of Generative Artificial Intelligence on Organizational Innovation Performance: Roles of AI Generated Content Quality, AI Experience, and AI Usage Environment

Haonan Xu, Ruoxuan Xu, Hongyu Lin, Xiaojuan He
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Abstract

With the progress of artificial intelligence (AI), generative AI has emerged as a novel catalyst for driving innovation within enterprises. This study, rooted in behavior activation theory, endeavors to examine the impact of generative AI on enterprise innovation. A conceptual model is formulated to elucidate the relationship between generative AI and enterprise innovation. Utilizing structural equation modeling to scrutinize this model, the findings reveal substantial positive effects: AI generated content quality significantly influences the activation of enterprise innovation behavior (ß = 0.37, t-value = 7.64, p < 0.01), AI experience has a notable positive impact on innovation behavior activation (ß = 0.19, t-value = 3.47, p < 0.01), and a supportive AI usage environment significantly influences the activation of enterprise innovation behavior (ß= 0.46, t-value = 10.48, p <0.01). Furthermore, innovation behavior activation makes a significant contribution to enterprise innovation performance (ß = 0.65, t-value = 18.23, p < 0.01).
生成式人工智能对组织创新绩效的影响:人工智能生成内容质量、人工智能体验和人工智能使用环境的作用
随着人工智能(AI)的发展,生成式人工智能已成为推动企业创新的新型催化剂。本研究以行为激活理论为基础,试图探讨生成式人工智能对企业创新的影响。本研究建立了一个概念模型,以阐明生成性人工智能与企业创新之间的关系。利用结构方程模型对该模型进行仔细研究,研究结果显示了实质性的积极影响:人工智能生成内容的质量明显影响企业创新行为的激活(ß=0.37,t值=7.64,p<0.01),人工智能经验对创新行为激活有明显的积极影响(ß=0.19,t值=3.47,p<0.01),支持性人工智能使用环境明显影响企业创新行为的激活(ß=0.46,t值=10.48,p<0.01)。此外,创新行为激活对企业创新绩效也有重要贡献(ß= 0.65,t 值= 18.23,p <0.01)。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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