揭示企业数字平台中生成式人工智能的采用:制度压力的影响以及内外环境的调节作用

IF 4.6 3区 管理学 Q1 BUSINESS IEEE Transactions on Engineering Management Pub Date : 2024-12-09 DOI:10.1109/TEM.2024.3513773
Lin Zhang;Zhen Shao;Bin Chen;Jose Benitez
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引用次数: 0

摘要

尽管生成式人工智能(AI)系统在企业数字平台中具有变革潜力,但在理解与采用这些系统相关的挑战和战略方面仍存在差距。为解决这一紧迫问题,本文借鉴制度理论,深入研究影响企业在其企业数字平台中采用生成式人工智能的驱动因素。利用从 328 家已实施数字平台以支持其业务运营的公司收集到的调查数据,我们发现制度压力对企业数字平台中的生成性人工智能的采用产生了积极影响。此外,我们还发现了政策不确定性和创新文化在形成这种关系方面的显著调节作用。我们的研究结果阐明了采用人工智能的潜在挑战和策略,并重新评估了制度理论在数字领域的应用,为人工智能文献做出了重大贡献。
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Unraveling Generative AI Adoption in Enterprise Digital Platforms: The Effect of Institutional Pressures and the Moderating Role of Internal and External Environments
Despite the transformative potential of generative artificial intelligence (AI) systems within enterprise digital platforms, there still exist gaps in understanding the challenges and strategies associated with their adoption. Addressing this pressing issue, this article draws upon institutional theory to delve into the drivers influencing firms’ adoption of generative AI within their enterprise digital platforms. Leveraging survey data collected from 328 firms that have implemented digital platforms to support their business operations, we find that institutional pressures positively influence generative AI adoption within their enterprise digital platforms. Furthermore, we identify salient moderating effects of policy uncertainty and innovative culture in shaping the relationships. Our research findings make a substantial contribution to AI literature by illuminating the potential challenges and strategies toward generative AI adoption as well as reassessing the application of institutional theory within the digital landscape.
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来源期刊
IEEE Transactions on Engineering Management
IEEE Transactions on Engineering Management 管理科学-工程:工业
CiteScore
10.30
自引率
19.00%
发文量
604
审稿时长
5.3 months
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.
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