Vijay Pereira , Elias Hadjielias , Michael Christofi , Demetris Vrontis
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Through an exhaustive systematic review and analysis of existing literature, we ultimately examine and cross-relate 60 papers, published in 30 leading international (AJG 3 and 4) journals over a period of 25 years (1995–2020). Our review researches the AI-workplace outcomes nexus by drawing on the major functions of human resource management and the process framework of ‘antecedents, phenomenon, outcomes’ at multiple levels of analysis. We review the sampled articles based on years of publication, theories, methods, and key themes across the ‘antecedents, phenomenon, outcomes’ framework. We provide useful directions for future research by embedding our discussion within HR literature, while we recommend topics drawing on alternative units of analysis and theories that draw on the individual, team, and institutional levels.</p></div>","PeriodicalId":48145,"journal":{"name":"Human Resource Management Review","volume":"33 1","pages":"Article 100857"},"PeriodicalIF":8.2000,"publicationDate":"2023-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/j.hrmr.2021.100857","citationCount":"72","resultStr":"{\"title\":\"A systematic literature review on the impact of artificial intelligence on workplace outcomes: A multi-process perspective\",\"authors\":\"Vijay Pereira , Elias Hadjielias , Michael Christofi , Demetris Vrontis\",\"doi\":\"10.1016/j.hrmr.2021.100857\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>Artificial intelligence (AI) can bring both opportunities and challenges to human resource management (HRM). While scholars have been examining the impact of AI on workplace outcomes more closely over the past two decades, the literature falls short in providing a holistic scholarly review of this body of research. Such a review is needed in order to: (a) guide future research on the effects of AI on the workplace; and (b) help managers make proper use of AI technology to improve workplace and organizational outcomes.</p><p>This is the first systematic review to explore the relationship between artificial intelligence and workplace outcomes. Through an exhaustive systematic review and analysis of existing literature, we ultimately examine and cross-relate 60 papers, published in 30 leading international (AJG 3 and 4) journals over a period of 25 years (1995–2020). Our review researches the AI-workplace outcomes nexus by drawing on the major functions of human resource management and the process framework of ‘antecedents, phenomenon, outcomes’ at multiple levels of analysis. We review the sampled articles based on years of publication, theories, methods, and key themes across the ‘antecedents, phenomenon, outcomes’ framework. We provide useful directions for future research by embedding our discussion within HR literature, while we recommend topics drawing on alternative units of analysis and theories that draw on the individual, team, and institutional levels.</p></div>\",\"PeriodicalId\":48145,\"journal\":{\"name\":\"Human Resource Management Review\",\"volume\":\"33 1\",\"pages\":\"Article 100857\"},\"PeriodicalIF\":8.2000,\"publicationDate\":\"2023-03-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://sci-hub-pdf.com/10.1016/j.hrmr.2021.100857\",\"citationCount\":\"72\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Human Resource Management Review\",\"FirstCategoryId\":\"91\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S105348222100036X\",\"RegionNum\":1,\"RegionCategory\":\"管理学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"MANAGEMENT\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Human Resource Management Review","FirstCategoryId":"91","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S105348222100036X","RegionNum":1,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"MANAGEMENT","Score":null,"Total":0}
A systematic literature review on the impact of artificial intelligence on workplace outcomes: A multi-process perspective
Artificial intelligence (AI) can bring both opportunities and challenges to human resource management (HRM). While scholars have been examining the impact of AI on workplace outcomes more closely over the past two decades, the literature falls short in providing a holistic scholarly review of this body of research. Such a review is needed in order to: (a) guide future research on the effects of AI on the workplace; and (b) help managers make proper use of AI technology to improve workplace and organizational outcomes.
This is the first systematic review to explore the relationship between artificial intelligence and workplace outcomes. Through an exhaustive systematic review and analysis of existing literature, we ultimately examine and cross-relate 60 papers, published in 30 leading international (AJG 3 and 4) journals over a period of 25 years (1995–2020). Our review researches the AI-workplace outcomes nexus by drawing on the major functions of human resource management and the process framework of ‘antecedents, phenomenon, outcomes’ at multiple levels of analysis. We review the sampled articles based on years of publication, theories, methods, and key themes across the ‘antecedents, phenomenon, outcomes’ framework. We provide useful directions for future research by embedding our discussion within HR literature, while we recommend topics drawing on alternative units of analysis and theories that draw on the individual, team, and institutional levels.
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.
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