人工智能与人力资源管理:人力资源管理者对决策和挑战的看法

IF 7.5 2区 管理学 Q1 BUSINESS
Aleksandar Radonjić , Henrique Duarte , Nádia Pereira
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引用次数: 0

摘要

聚焦当今大数据(BD)的变革力量让许多公司,即决策者,以前所未有的速度发展。在决策方面,人工智能(AI)将任务授权提升到了一个新的水平,通过采用人工智能辅助工具,企业可以为其人力资源部门提供管理现有数据和人力资源的手段。目标确定人力资源管理者如何评估人工智能是否有助于业务发展管理,以及他们如何构建必要的变革以应对人工智能及其实施的相关趋势,即他们是否愿意掌握人工智能的实施并应对可能的挑战。方法对来自不同领域的 16 名人力资源从业者的访谈样本进行内容分析,并使用大数据成熟度模型(BDMM)框架对结果进行分析。通过该模型所涵盖的领域,可以从应对颠覆性技术的准备程度和意愿方面研究决策趋势,从而改进决策并获得竞争优势。研究结果人工智能的核心潜力在于更快的数据存储和处理能力,从而带来更具洞察力和更有效的决策。本文深入探讨了在决策过程中实施人工智能所面临的挑战,特别是在战略调整、治理和实施方面。研究结果反映了有关人工智能本质的概念--在协助人力资源方面--并阐述了通过提供优势智能提取 BD 以增强人力资源决策的路径。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Artificial intelligence and HRM: HR managers’ perspective on decisiveness and challenges

Focus

The transformative power of today's big data (BD) has allowed many companies, i.e., decision-makers, to evolve at an unprecedented pace. With regard to decision-making, artificial intelligence (AI) takes task delegation to a new level, and by employing AI-assisted tools, companies can provide their HR departments with the means to manage the existing data and HR altogether.

Objectives

To determine how HR managers assess whether BD management is facilitated by AI, and how they frame the changes necessary to meet the trends related to AI and its implementation, namely their willingness to master its implementation and to meet the possible challenges.

Methodology

Content analysis was conducted on interviews held with a sample of 16 HR practitioners from a spectrum of areas, and the findings were analysed using the big data maturity model (BDMM) framework. Domains covered by this model allow the study of decision-making trends, in terms of preparedness and willingness to tackle disruptive technology with the aim of improving and gaining the competitive edge in decision-making.

Findings

The central potential of AI lies in faster data storage and processing power, thereby leading to more insightful and effective decision-making. This article contains closer insights into the challenges underlying the implementation of AI in decision-making processes, specifically in terms of strategic alignment, governance, and implementation. The results reflect the notions regarding the nature of AI – in assisting HR – and lay out the path that precedes the extraction of BD, through the delivery of advantageous intelligence, to augment decision-making in HR.

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来源期刊
CiteScore
12.90
自引率
5.30%
发文量
113
审稿时长
74 days
期刊介绍: The European Management Journal (EMJ) stands as a premier scholarly publication, disseminating cutting-edge research spanning all realms of management. EMJ articles challenge conventional wisdom through rigorously informed empirical and theoretical inquiries, offering fresh insights and innovative perspectives on key management themes while remaining accessible and engaging for a wide readership. EMJ articles embody intellectual curiosity and embrace diverse methodological approaches, yielding contributions that significantly influence both management theory and practice. We actively seek interdisciplinary research that integrates distinct research traditions to illuminate contemporary challenges within the expansive domain of European business and management. We strongly encourage cross-cultural investigations addressing the unique challenges faced by European management scholarship and practice in navigating global issues and contexts.
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