Artificial Intelligence–HRM Interactions and Outcomes: A Systematic Review and Causal Configurational Explanation

IF 8.2 1区管理学 Q1 MANAGEMENT

Human Resource Management Review Pub Date : 2023-03-01 DOI:10.1016/j.hrmr.2022.100893

Shubhabrata Basu , Bishakha Majumdar , Kajari Mukherjee , Surender Munjal , Chandan Palaksha

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引用次数: 10

Abstract

Artificial intelligence (AI) systems and applications based on them are fast pervading the various functions of an organization. While AI systems enhance organizational performance, thereby catching the attention of the decision makers, they nonetheless pose threats of job losses for human resources. This in turn pose challenges to human resource managers, tasked with governing the AI adoption processes. However, these challenges afford opportunities to critically examine the various facets of AI systems as they interface with human resources. To that end, we systematically review the literature at the intersection of AI and human resource management (HRM). Using the configurational approach, we identify the evolution of different theme based causal configurations in conceptual and empirical research and the outcomes of AI-HRM interaction. We observe incremental mutations in thematic causal configurations as the literature evolves and also provide thematic configuration based explanations to beneficial and reactionary outcomes in the AI-HRM interaction process.

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人工智能与人力资源管理的互动与结果：系统回顾与因果配置解释

人工智能系统及其应用正在迅速渗透到组织的各种功能中。虽然人工智能系统可以提高组织绩效，从而吸引决策者的注意力，但它们仍然会对人力资源造成失业的威胁。这反过来又给负责管理人工智能采用过程的人力资源经理带来了挑战。然而，这些挑战为批判性地研究人工智能系统与人力资源接口的各个方面提供了机会。为此，我们系统地回顾了人工智能与人力资源管理（HRM）交叉的文献。使用配置方法，我们确定了概念和实证研究中不同主题因果配置的演变以及AI-HRM互动的结果。随着文献的发展，我们观察到主题因果配置的递增突变，并对AI-HRM相互作用过程中的有益和反应结果提供了基于主题配置的解释。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Human Resource Management Review MANAGEMENT-

CiteScore

20.20

自引率

7.00%

发文量

审稿时长

48 days

期刊介绍： The Human Resource Management Review (HRMR) is a quarterly academic journal dedicated to publishing scholarly conceptual and theoretical articles in the field of human resource management and related disciplines such as industrial/organizational psychology, human capital, labor relations, and organizational behavior. HRMR encourages manuscripts that address micro-, macro-, or multi-level phenomena concerning the function and processes of human resource management. The journal publishes articles that offer fresh insights to inspire future theory development and empirical research. Critical evaluations of existing concepts, theories, models, and frameworks are also encouraged, as well as quantitative meta-analytical reviews that contribute to conceptual and theoretical understanding. Subject areas appropriate for HRMR include (but are not limited to) Strategic Human Resource Management, International Human Resource Management, the nature and role of the human resource function in organizations, any specific Human Resource function or activity (e.g., Job Analysis, Job Design, Workforce Planning, Recruitment, Selection and Placement, Performance and Talent Management, Reward Systems, Training, Development, Careers, Safety and Health, Diversity, Fairness, Discrimination, Employment Law, Employee Relations, Labor Relations, Workforce Metrics, HR Analytics, HRM and Technology, Social issues and HRM, Separation and Retention), topics that influence or are influenced by human resource management activities (e.g., Climate, Culture, Change, Leadership and Power, Groups and Teams, Employee Attitudes and Behavior, Individual, team, and/or Organizational Performance), and HRM Research Methods.