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Folly Beach Library
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Edgar Allan Poe/Sullivan's Island Library
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Wando Mount Pleasant Library
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Village Library
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Hurd/St. Andrews Library
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An interdisciplinary review of AI and HRM: Challenges and future directions.
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![loading](/sites/all/modules/hf_eds/images/loading.gif)
- Author(s): Pan, Yuan (AUTHOR); Froese, Fabian J. (AUTHOR)
- Source:
Human Resource Management Review. Mar2023, Vol. 33 Issue 1, pN.PAG-N.PAG. 1p. - Source:
- Additional Information
- Subject Terms:
- Abstract: Artificial intelligence (AI) has the potential to change the future of human resource management (HRM). Scholars from different disciplines have contributed to the field of AI in HRM but with rather insufficient cross-fertilization, thus leading to a fragmented body of knowledge. In response, we conducted a systematic, interdisciplinary review of 184 articles to provide a comprehensive overview. We grouped prior research into four categories based on discipline: management and economics, computer science, engineering and operations, and others. The findings reveal that studies in different disciplines had different research foci and utilized different methods. While studies in the technical disciplines tended to focus on the development of AI for specific HRM functions, studies from the other disciplines tended to focus on the consequences of AI on HRM, jobs, and labor markets. Most studies in all categories were relatively weak in theoretical development. We therefore offer recommendations for interdisciplinary collaborations, propose a unified definition of AI, and provide implications for research and practice. • This paper provides a systematic, interdisciplinary literature review. • Artificial intelligence has great potential to change the future of HRM. • Prior research from different disciplines has been fragmented. • We identify methodological and theoretical weaknesses. • We propose recommendations for research and practice. [ABSTRACT FROM AUTHOR]
- Abstract: Copyright of Human Resource Management Review is the property of Elsevier B.V. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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