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Discovering knowledge map and evolutionary path of HRM and ER: using the STM combined with Word2vec

Dejian Yu (School of Business, Nanjing Audit University, Nanjing, China)
Bo Xiang (School of Business, Nanjing Audit University, Nanjing, China)

International Journal of Manpower

ISSN: 0143-7720

Article publication date: 5 May 2023

Issue publication date: 4 July 2023

221

Abstract

Purpose

The purpose of this study is to comprehensively review the human resource management (HRM) and employment relations (ERs) field and explore the knowledge map, knowledge evolution trends and paths and paradigm shifts within this field.

Design/methodology/approach

The Structural Topic Model in combination with Word2vec is proposed and applied in this work. First, this paper detects and interprets the research topics by reviewing 23,786 papers from 29 important journals in this field from 1990 to 2021. Then, this research explores popularity trends by aggregating topic proportions from a temporal perspective. Finally, this work explores the research topic evolution from the semantic perspective.

Findings

This paper obtains the following findings: (1) Sixteen research topics are identified, which provide the basic research overview of the whole field. (2) The changes in topic popularity over time map the tendency for employee benefits to be valued. (3) The evolutionary trajectories of temporal local topics are provided, which reflect the mechanisms of the paradigm and ideological migration and fusion.

Originality/value

This work adopts state-of-the-art textual as well as semantic mining techniques to establish a comprehensive knowledge map for HRM and ER research. Furthermore, these results uniquely demonstrate the pluralistic ideological orientation at the social level is gradually integrated into more micro levels, such as enterprises and individuals. These are the contents that were mentioned from previous studies by scholars, but not meticulously verified and interpreted.

Keywords

Acknowledgements

This manuscript was supported by the Postgraduate Research and Practice Innovation Program of Jiangsu Province (No. KYCX22_2187).

Citation

Yu, D. and Xiang, B. (2023), "Discovering knowledge map and evolutionary path of HRM and ER: using the STM combined with Word2vec", International Journal of Manpower, Vol. 44 No. 5, pp. 967-988. https://doi.org/10.1108/IJM-08-2022-0353

Publisher

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Emerald Publishing Limited

Copyright © 2023, Emerald Publishing Limited

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