{"title":"人工智能应用强度与企业创新绩效的关系:人工智能能力的作用","authors":"Xiaoyue Lin;Tiandong Wang;Fan Sheng","doi":"10.1109/TEM.2025.3572042","DOIUrl":null,"url":null,"abstract":"Although the transformative potential of artificial intelligence (AI) in driving innovation is widely acknowledged, the relationship between AI-adoption intensity and firm innovation performance remains underexplored. To address this gap, this study investigates the impact of AI-adoption intensity on firm innovation performance through the lens of technology affordance theory (TAT), emphasizing the role of AI affordances. Additionally, it examines the moderating role of data quality in shaping the relationship between AI-adoption intensity and AI affordances. A conceptual model was developed and tested through structural equation modeling using data collected from 396 Chinese firms. The findings demonstrate that AI-adoption intensity significantly enhances firm innovation performance. AI affordances—conceptualized along three dimensions: mobility affordance, interactivity affordance, and autonomy affordance—mediate the effect of AI-adoption intensity on firm innovation performance. These affordances collectively support AI’s dual roles as a supportive tool and an innovation agent. Furthermore, data quality positively moderates the relationship between AI-adoption intensity and AI affordances, underscoring the importance of data quality in realizing AI’s potential benefits. This article advances our understanding of leveraging AI to bolster innovation outcomes and extends the theoretical foundations of the TAT within the context of AI innovation. These insights provide valuable guidance for firms seeking to enhance their innovation outcomes through AI adoption.","PeriodicalId":55009,"journal":{"name":"IEEE Transactions on Engineering Management","volume":"72 ","pages":"2267-2278"},"PeriodicalIF":4.6000,"publicationDate":"2025-06-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"The Relationship Between AI-Adoption Intensity and Firm Innovation Performance: The Role of AI Affordances\",\"authors\":\"Xiaoyue Lin;Tiandong Wang;Fan Sheng\",\"doi\":\"10.1109/TEM.2025.3572042\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Although the transformative potential of artificial intelligence (AI) in driving innovation is widely acknowledged, the relationship between AI-adoption intensity and firm innovation performance remains underexplored. To address this gap, this study investigates the impact of AI-adoption intensity on firm innovation performance through the lens of technology affordance theory (TAT), emphasizing the role of AI affordances. Additionally, it examines the moderating role of data quality in shaping the relationship between AI-adoption intensity and AI affordances. A conceptual model was developed and tested through structural equation modeling using data collected from 396 Chinese firms. The findings demonstrate that AI-adoption intensity significantly enhances firm innovation performance. AI affordances—conceptualized along three dimensions: mobility affordance, interactivity affordance, and autonomy affordance—mediate the effect of AI-adoption intensity on firm innovation performance. These affordances collectively support AI’s dual roles as a supportive tool and an innovation agent. Furthermore, data quality positively moderates the relationship between AI-adoption intensity and AI affordances, underscoring the importance of data quality in realizing AI’s potential benefits. This article advances our understanding of leveraging AI to bolster innovation outcomes and extends the theoretical foundations of the TAT within the context of AI innovation. These insights provide valuable guidance for firms seeking to enhance their innovation outcomes through AI adoption.\",\"PeriodicalId\":55009,\"journal\":{\"name\":\"IEEE Transactions on Engineering Management\",\"volume\":\"72 \",\"pages\":\"2267-2278\"},\"PeriodicalIF\":4.6000,\"publicationDate\":\"2025-06-05\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IEEE Transactions on Engineering Management\",\"FirstCategoryId\":\"91\",\"ListUrlMain\":\"https://ieeexplore.ieee.org/document/11026822/\",\"RegionNum\":3,\"RegionCategory\":\"管理学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"BUSINESS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Transactions on Engineering Management","FirstCategoryId":"91","ListUrlMain":"https://ieeexplore.ieee.org/document/11026822/","RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"BUSINESS","Score":null,"Total":0}
The Relationship Between AI-Adoption Intensity and Firm Innovation Performance: The Role of AI Affordances
Although the transformative potential of artificial intelligence (AI) in driving innovation is widely acknowledged, the relationship between AI-adoption intensity and firm innovation performance remains underexplored. To address this gap, this study investigates the impact of AI-adoption intensity on firm innovation performance through the lens of technology affordance theory (TAT), emphasizing the role of AI affordances. Additionally, it examines the moderating role of data quality in shaping the relationship between AI-adoption intensity and AI affordances. A conceptual model was developed and tested through structural equation modeling using data collected from 396 Chinese firms. The findings demonstrate that AI-adoption intensity significantly enhances firm innovation performance. AI affordances—conceptualized along three dimensions: mobility affordance, interactivity affordance, and autonomy affordance—mediate the effect of AI-adoption intensity on firm innovation performance. These affordances collectively support AI’s dual roles as a supportive tool and an innovation agent. Furthermore, data quality positively moderates the relationship between AI-adoption intensity and AI affordances, underscoring the importance of data quality in realizing AI’s potential benefits. This article advances our understanding of leveraging AI to bolster innovation outcomes and extends the theoretical foundations of the TAT within the context of AI innovation. These insights provide valuable guidance for firms seeking to enhance their innovation outcomes through AI adoption.
期刊介绍:
Management of technical functions such as research, development, and engineering in industry, government, university, and other settings. Emphasis is on studies carried on within an organization to help in decision making or policy formation for RD&E.