Quantifying human resource management: a literature review

Author:

Coron ClotildeORCID

Abstract

PurposeWith a focus on the evolution of human resource management (HRM) quantification over 2000–2020, this study addresses the following questions: (1) What are the data sources used to quantify HRM? (2) What are the methods used to quantify HRM? (3) What are the objectives of HRM quantification? (4) What are the representations of quantification in HRM?Design/methodology/approachThis study is based on an integrative synthesis of 94 published peer-reviewed empirical and non-empirical articles on the use of quantification in HRM. It uses the theoretical framework of the sociology of quantification.FindingsThe analysis shows that there have been several changes in HRM quantification over 2000–2020 in terms of data sources, methods and objectives. Meanwhile, representations of quantification have evolved relatively little; it is still considered as a tool, and this ignores the possible conflicts and subjectivity associated with the use of quantification.Originality/valueThis literature review addresses the use of quantification in HRM in general and is thus larger in scope than previous reviews. Notably, it brings forth new insights on possible differences between the main uses of quantification in HRM, as well as on artificial intelligence and algorithms in HRM.

Publisher

Emerald

Subject

Organizational Behavior and Human Resource Management,Applied Psychology

Reference119 articles.

1. HR and analytics: why HR is set to fail the big data challenge;Human Resource Management Journal,2016

2. Three-way complementarities: performance pay, human resource analytics, and information technology;Management Science,2012

3. Raging debates in HR analytics;People and Strategy,2011

4. New HR metrics: scoring on the business scorecard;Organizational Dynamics,2003

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