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
{"title":"The Impact of Generative Artificial Intelligence on Organizational Innovation Performance: Roles of AI Generated Content Quality, AI Experience, and AI Usage Environment","authors":"Haonan Xu, Ruoxuan Xu, Hongyu Lin, Xiaojuan He","doi":"10.1109/ICETSIS61505.2024.10459661","DOIUrl":null,"url":null,"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).","PeriodicalId":518932,"journal":{"name":"2024 ASU International Conference in Emerging Technologies for Sustainability and Intelligent Systems (ICETSIS)","volume":"412 8","pages":"1802-1807"},"PeriodicalIF":0.0000,"publicationDate":"2024-01-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2024 ASU International Conference in Emerging Technologies for Sustainability and Intelligent Systems (ICETSIS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICETSIS61505.2024.10459661","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

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).
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
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。
求助全文
约1分钟内获得全文 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Other reviewers Bean Leaf Lesions Image Classification: A Robust Ensemble Deep Learning Approach MTU Analyzing for Data Centers Interconnected Using VxLAN AFAR-YOLO: An Adaptive YOLO Object Detection Framework A Decision Support Framework for Sustainable Waste Disposal Technology Selection
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1