Understanding the adoption and institutionalization of workforce analytics: A systematic literature review and research agenda

IF 8.2 1区 管理学 Q1 MANAGEMENT
Patrick Coolen , Sjoerd van den Heuvel , Karina Van De Voorde , Jaap Paauwe
{"title":"Understanding the adoption and institutionalization of workforce analytics: A systematic literature review and research agenda","authors":"Patrick Coolen ,&nbsp;Sjoerd van den Heuvel ,&nbsp;Karina Van De Voorde ,&nbsp;Jaap Paauwe","doi":"10.1016/j.hrmr.2023.100985","DOIUrl":null,"url":null,"abstract":"<div><p>Data analytics plays a crucial role in enhancing organizational decision-making. Various organizational disciplines have already embraced data analytics. However, human resources management is lagging in data-driven decision-making and, specifically, workforce analytics. Although an increasing number of studies explore the diffusion of workforce analytics, our understanding of why organizations decide to adopt workforce analytics and how organizations further institutionalize workforce analytics remains limited. Taking an HRM innovation and contextualized perspective, this systematic literature review aims to provide in-depth knowledge on factors driving workforce analytics adoption and institutionalization. The results, including relevant learnings from business analytics research, show the importance of competitive, institutional, heritage mechanisms, key decision-makers and actors, and HRM fit-related factors in the diffusion process. Based on the results of this review, various avenues for future research are presented. Additionally, insights from this literature review can help decision-makers allocate their scarce resources effectively and efficiently to cultivate workforce analytics as an organizational practice.</p></div>","PeriodicalId":48145,"journal":{"name":"Human Resource Management Review","volume":"33 4","pages":"Article 100985"},"PeriodicalIF":8.2000,"publicationDate":"2023-08-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Human Resource Management Review","FirstCategoryId":"91","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1053482223000384","RegionNum":1,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"MANAGEMENT","Score":null,"Total":0}
引用次数: 0

Abstract

Data analytics plays a crucial role in enhancing organizational decision-making. Various organizational disciplines have already embraced data analytics. However, human resources management is lagging in data-driven decision-making and, specifically, workforce analytics. Although an increasing number of studies explore the diffusion of workforce analytics, our understanding of why organizations decide to adopt workforce analytics and how organizations further institutionalize workforce analytics remains limited. Taking an HRM innovation and contextualized perspective, this systematic literature review aims to provide in-depth knowledge on factors driving workforce analytics adoption and institutionalization. The results, including relevant learnings from business analytics research, show the importance of competitive, institutional, heritage mechanisms, key decision-makers and actors, and HRM fit-related factors in the diffusion process. Based on the results of this review, various avenues for future research are presented. Additionally, insights from this literature review can help decision-makers allocate their scarce resources effectively and efficiently to cultivate workforce analytics as an organizational practice.

了解劳动力分析的采用和制度化:系统的文献综述和研究议程
数据分析在提高组织决策方面起着至关重要的作用。各种组织学科已经接受了数据分析。然而,人力资源管理在数据驱动的决策,特别是劳动力分析方面落后。尽管越来越多的研究探索劳动力分析的扩散,但我们对组织为什么决定采用劳动力分析以及组织如何进一步将劳动力分析制度化的理解仍然有限。从人力资源管理创新和情境化的角度来看,这一系统的文献综述旨在深入了解推动劳动力分析采用和制度化的因素。结果,包括商业分析研究的相关知识,显示了竞争、制度、传统机制、关键决策者和行动者以及人力资源管理适合相关因素在扩散过程中的重要性。在此综述的基础上,提出了未来研究的各种途径。此外,本文献综述的见解可以帮助决策者有效地分配稀缺资源,以培养劳动力分析作为组织实践。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
CiteScore
20.20
自引率
7.00%
发文量
0
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.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信