The impact of generative AI on management innovation

IF 10.4 1区 计算机科学 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS Journal of Industrial Information Integration Pub Date : 2024-12-26 DOI:10.1016/j.jii.2024.100767
Caiming Zhang, Hui Zhang
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引用次数: 0

Abstract

Generative Artificial Intelligence (GAI) demonstrates significant potential in the application of management and organizational innovation. This paper systematically investigates the multifaceted impacts of GAI on management decision-making, management algorithms, information integration, and various specific domains. GAI significantly enhances the accuracy of management decisions through its robust data analysis and predictive capabilities. By effectively integrating internal and external information, it reduces information asymmetry and improves both information transparency and the quality of decisions. In terms of specific application areas, GAI shows broad prospects in multiple fields, including business, education, healthcare, content creation, and game development. As GAI technology continues to advance, it will become more intelligent and adaptive. However, further research and the establishment of relevant ethical guidelines and legal frameworks are necessary to ensure its safety and reliability.
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来源期刊
Journal of Industrial Information Integration
Journal of Industrial Information Integration Decision Sciences-Information Systems and Management
CiteScore
22.30
自引率
13.40%
发文量
100
期刊介绍: The Journal of Industrial Information Integration focuses on the industry's transition towards industrial integration and informatization, covering not only hardware and software but also information integration. It serves as a platform for promoting advances in industrial information integration, addressing challenges, issues, and solutions in an interdisciplinary forum for researchers, practitioners, and policy makers. The Journal of Industrial Information Integration welcomes papers on foundational, technical, and practical aspects of industrial information integration, emphasizing the complex and cross-disciplinary topics that arise in industrial integration. Techniques from mathematical science, computer science, computer engineering, electrical and electronic engineering, manufacturing engineering, and engineering management are crucial in this context.
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