Hot Topics and Directions of Human Resource Analytics Based on a Hybrid Method (Bibliometric Analysis, Fuzzy Delphi Method and SWARA)

Due to the emergence of big data during the recent decades, data analytics played an important role in organizations, especially in human resource management (HRM). Despite increasing attention to data analytics in HRM, there is still a gap in this research scope. According to the dispersion of exis...

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Main Authors: Mona Kardani Malekinezhad, Fariborz Rahimnia, GHasem Eslami, Mohammad Mahdi Farahi
Format: Article
Language:English
Published: Regional Information Center for Science and Technology (RICeST) 2025-01-01
Series:International Journal of Information Science and Management
Subjects:
Online Access:https://ijism.isc.ac/article_718773_23364de30e2634198413d4070a24a4b9.pdf
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author Mona Kardani Malekinezhad
Fariborz Rahimnia
GHasem Eslami
Mohammad Mahdi Farahi
author_facet Mona Kardani Malekinezhad
Fariborz Rahimnia
GHasem Eslami
Mohammad Mahdi Farahi
author_sort Mona Kardani Malekinezhad
collection DOAJ
description Due to the emergence of big data during the recent decades, data analytics played an important role in organizations, especially in human resource management (HRM). Despite increasing attention to data analytics in HRM, there is still a gap in this research scope. According to the dispersion of existing relevant studies, this study aimed to reveal the hot topics, as well as the future directions of this field. Therefore, the present study utilized a hybrid method based on bibliometric analysis (co-word analysis), Fuzzy Delphi, and SWARA (Step-Wise Weight Assessment Ratio Analysis) and evaluated 87 articles from the Scopus database. The co-word results extracted a total of 40 keywords, and then the indicators were measured according to experts' opinions and the fuzzy Delphi method (FDM) and were prioritized using the SWARA method. Based on the analysis results, HR analytics and human resource data analytics are the most important cases, and then people analytics, human capital analytics, workforce analytics, data analytics, big data, analytical competencies, predictive HR analytics capability, and HR analyst are ranked third to tenth. The top 6 keywords for future directions are strategy, HR processes, big data, competencies, technology, and evidence.
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language English
publishDate 2025-01-01
publisher Regional Information Center for Science and Technology (RICeST)
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spelling doaj-art-5da7f6d5402d47779a8cbb47a870c5552025-01-18T06:18:23ZengRegional Information Center for Science and Technology (RICeST)International Journal of Information Science and Management2008-83022008-83102025-01-0123114716910.22034/ijism.2024.2020158.1365718773Hot Topics and Directions of Human Resource Analytics Based on a Hybrid Method (Bibliometric Analysis, Fuzzy Delphi Method and SWARA)Mona Kardani Malekinezhad0Fariborz Rahimnia1GHasem Eslami2Mohammad Mahdi Farahi3Department of Management, Faculty of Economics & Administrative Sciences, Ferdowsi University of Mashhad, Mashhad, IranManagement Department, Faculty of Economics & Administrative Sciences, Ferdowsi University of Mashhad, Mashhad, Iran.Management Department, Faculty of Economics & Administrative Sciences, Ferdowsi University of Mashhad, Mashhad, IranManagement Department, Faculty of Economics & Administrative Sciences, Ferdowsi University of Mashhad, Mashhad, Iran.Due to the emergence of big data during the recent decades, data analytics played an important role in organizations, especially in human resource management (HRM). Despite increasing attention to data analytics in HRM, there is still a gap in this research scope. According to the dispersion of existing relevant studies, this study aimed to reveal the hot topics, as well as the future directions of this field. Therefore, the present study utilized a hybrid method based on bibliometric analysis (co-word analysis), Fuzzy Delphi, and SWARA (Step-Wise Weight Assessment Ratio Analysis) and evaluated 87 articles from the Scopus database. The co-word results extracted a total of 40 keywords, and then the indicators were measured according to experts' opinions and the fuzzy Delphi method (FDM) and were prioritized using the SWARA method. Based on the analysis results, HR analytics and human resource data analytics are the most important cases, and then people analytics, human capital analytics, workforce analytics, data analytics, big data, analytical competencies, predictive HR analytics capability, and HR analyst are ranked third to tenth. The top 6 keywords for future directions are strategy, HR processes, big data, competencies, technology, and evidence.https://ijism.isc.ac/article_718773_23364de30e2634198413d4070a24a4b9.pdfco-word analysisfuzzy delphi methodhot topicshuman resource analyticsswara
spellingShingle Mona Kardani Malekinezhad
Fariborz Rahimnia
GHasem Eslami
Mohammad Mahdi Farahi
Hot Topics and Directions of Human Resource Analytics Based on a Hybrid Method (Bibliometric Analysis, Fuzzy Delphi Method and SWARA)
International Journal of Information Science and Management
co-word analysis
fuzzy delphi method
hot topics
human resource analytics
swara
title Hot Topics and Directions of Human Resource Analytics Based on a Hybrid Method (Bibliometric Analysis, Fuzzy Delphi Method and SWARA)
title_full Hot Topics and Directions of Human Resource Analytics Based on a Hybrid Method (Bibliometric Analysis, Fuzzy Delphi Method and SWARA)
title_fullStr Hot Topics and Directions of Human Resource Analytics Based on a Hybrid Method (Bibliometric Analysis, Fuzzy Delphi Method and SWARA)
title_full_unstemmed Hot Topics and Directions of Human Resource Analytics Based on a Hybrid Method (Bibliometric Analysis, Fuzzy Delphi Method and SWARA)
title_short Hot Topics and Directions of Human Resource Analytics Based on a Hybrid Method (Bibliometric Analysis, Fuzzy Delphi Method and SWARA)
title_sort hot topics and directions of human resource analytics based on a hybrid method bibliometric analysis fuzzy delphi method and swara
topic co-word analysis
fuzzy delphi method
hot topics
human resource analytics
swara
url https://ijism.isc.ac/article_718773_23364de30e2634198413d4070a24a4b9.pdf
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