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