Ahmad A. Khanfar, Reza Kiani Mavi, Mohammad Iranmanesh, Denise Gengatharen
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引用次数: 0
摘要
由于人工智能（AI）系统的诸多益处，其采用率正在不断上升。本研究进行了文献计量分析，以确定：(1) 有关采用人工智能的文献在过去几年中是如何演变的；(2) 文献中与采用人工智能相关的关键主题；(3) 文献中的空白。为了实现这些目标，我们利用 R 软件包的文献计量分析工具 Biblioshiny 对人工智能应用文献进行了分析。本研究共审阅和分析了 91 篇文章。确定了四大主题：人工智能、机器学习、技术接受和使用统一理论（UTAUT）模型和技术接受模型（TAM）。通过对确定的主题进行内容分析，本研究获得了对人工智能应用研究的更多见解。以往的研究仅限于特定行业和系统，UTAUT 和 TAM 等采用理论的使用也很有限。本研究为今后的研究提供了方向。
Determinants of artificial intelligence adoption: research themes and future directions
The adoption of artificial intelligence (AI) systems is on the rise owing to their many benefits. This study conducted a bibliometric analysis to identify (1) how the literature on AI adoption has evolved over the past few years, (2) key themes associated with AI adoption in the literature, and (3) the gaps in the literature. To achieve these objectives, we utilised the Biblioshiny of R-package bibliometric analysis tool to analyse the AI adoption literature. A total of 91 articles were reviewed and analysed in this study. Four major themes were identified: AI, machine learning, the unified theory of acceptance and use of technology (UTAUT) model and the technology acceptance model (TAM). Using a content analysis of the identified themes, the study gained additional insight into the studies on AI adoption. Previous studies have been limited to specific industries and systems, and adoption theories like the UTAUT and TAM have also been utilised to a limited extent. Directions for future studies were provided.
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