人事管理中的人工智能:APM模型的发展

IF 8 Q1 INFORMATION SCIENCE & LIBRARY SCIENCE Bottom Line Pub Date : 2020-11-04 DOI:10.1108/bl-08-2020-0055
Ki-Hwan Chang
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引用次数: 9

摘要

管理者对人工智能(AI)如何影响人事管理(PM)有不同的看法。本文的目的是识别潜在的知识差距,并为人工智能-人事管理文献带来新的见解。设计/方法/途径采用适用性和理论观点来批判性地讨论人工智能在项目管理中的约束和机会。表格和叙事分析用于阐明人工智能在管理实践中的作用。研究结果帮助开发了一种名为人工智能人事管理(APM)的新模式。APM模型从三个层面展开,然后是潜在的结果。这三个层面包括“组织、管理和个人工作层面”,结果包括“组织绩效、员工幸福感和员工流动率”。研究局限/启示APM模型帮助管理者理解人工智能对其工作场所的影响。通过更好地理解人工智能的含义,管理者更有可能制定适当的人工智能驱动的管理政策,这反过来又有利于员工和他们的组织。APM模型作为一个参考指南,帮助管理者在管理实践中评估人工智能的约束和机会。APM模型对学术研究人员来说是有价值的和有用的,因为它首先回应了Malik等人(2019)的呼吁(关于人工智能和管理文献的缺失),更重要的是,它提高了对人工智能-管理关系的认识,支持学者们进一步理解人工智能在项目管理中的作用。
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Artificial intelligence in personnel management: the development of APM model
Purpose Managers have mixed views of how artificial intelligence (AI) affects personnel management (PM). The purpose of this paper is to identify potential knowledge gap and bring new insights to the AI-personnel-management literature. Design/methodology/approach Both applicability and theoretical perspectives are adopted to critically discuss the constraint and opportunity of AI in PM. Tables and narrative analysis are used to clarify the role of AI in managerial practices. Findings Research findings have helped to develop a new model titled AI in Personnel Management (APM). The APM model unfolds itself in three levels, followed by potential outcome. The three levels comprise “organizational, managerial and individual job levels,” and the outcome comprises “organizational performance, employees’ well-being and staff turnover rate”. Research limitations/implications The APM model helps managers to understand the implication of AI in their workplace. With better understanding of AI’s implication, managers are more likely to develop appropriate AI-driven managerial policies, which in turn benefit employees and their organizations. The APM model acts as a reference guide, helping managers to evaluate the AI’s constraint and opportunity in their managerial practices. Originality/value The APM model is valuable and informative to the academic researchers, as it has first responded to Malik et al. (2019)’s call (re: the absence of AI and management literature), and, more importantly, it has advanced the knowledge of AI–management relationship, supporting scholars to further understand the role of AI in PM.
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Bottom Line
Bottom Line INFORMATION SCIENCE & LIBRARY SCIENCE-
CiteScore
9.90
自引率
12.20%
发文量
7
期刊介绍: Because The Bottom Line: Managing Library Finances is written and edited by well respected figures from the librarian community - you can be assured the topics covered will be particularly relevant to you and your library.
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