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BIBLIOMETRIC ANALYSIS OF HR ANALYTICS LITERATURE

Yıl 2022, Cilt: 21 Sayı: 83, 1147 - 1169, 01.07.2022
https://doi.org/10.17755/esosder.950426

Öz

Human resource analytics (HR analytics) research has been popular in recent years and is a newly emerging research area. Seeing in which frame the work done in this field is progressing will shed light on new future studies in the field. This study examines how HR analytics work is built on the basis of the intellectual framework. This research aims to contribute to the literature by examining the references, authors, topics, citations and journals of the studies. For this purpose, bibliometric techniques were used to examine 178 articles published between 2010 and 2021. A wide variety of disciplines have been used in the journals that publish these articles to address the issues of HR analytics. Main themes gathered in the articles are around the concepts of big data, talent management and workforce analytics. The study results show that research interest in HR analytics has increased in recent years. While the competencies of HR professionals, data quality, technological developments, cooperation with the IT department are the main topics, the literature seems to neglect the issue of ethics.

Kaynakça

  • Andersen, M. K. (2017). Human capital analytics: the winding road. Journal of Organizational Effectiveness: People and Performance.
  • Angrave, D., Charlwood, A., Kirkpatrick, I., Lawrence, M., & Stuart, M. (2016). HR and analytics: why HR is set to fail the big data challenge. Human Resource Management Journal, 26(1), 1-11.
  • Aral, S., Brynjolfsson, E., & Wu, L. (2012). Three-way complementarities: Performance pay, human resource analytics, and information technology. Management Science, 58(5), 913-931.
  • Bag, S., & Pretorius, J. H. C. (2020). Relationships between industry 4.0, sustainable manufacturing and circular economy: proposal of a research framework. International Journal of Organizational Analysis.
  • Barney, J. (1991). Firm resources and sustained competitive advantage. Journal of management, 17(1), 99-120.
  • Bassi, L., & McMurrer, D. (2016). Four lessons learned in how to use human resource analytics to improve the effectiveness of leadership development. Journal of leadership studies, 10(2), 39-43.
  • Ben-Gal, H. C. (2019). An ROI-based review of HR analytics: practical implementation tools. Personnel Review.
  • Berk, L., Bertsimas, D., Weinstein, A. M., & Yan, J. (2019). Prescriptive analytics for human resource planning in the professional services industry. European Journal of Operational Research, 272(2), 636-641.
  • Bohlouli, M., Mittas, N., Kakarontzas, G., Theodosiou, T., Angelis, L., & Fathi, M. (2017). Competence assessment as an expert system for human resource management: A mathematical approach. Expert Systems with Applications, 70, 83-102.
  • Boudreau, J. W., & Ramstad, P. M. (2007). Beyond HR: The new science of human capital. Harvard Business Press.
  • Bowen, D. E. (1996). Market-focused HRM in service organizations: Satisfying internal and external customers. Journal of Market-Focused Management, 1(1), 31-47.
  • Božič, K., & Dimovski, V. (2019). Business intelligence and analytics for value creation: The role of absorptive capacity. International journal of information management, 46, 93-103.
  • Calvard, T. S., & Jeske, D. (2018). Developing human resource data risk management in the age of big data. International Journal of Information Management, 43, 159-164.
  • Carmeli, A., & Tishler, A. (2004). The relationships between intangible organizational elements and organizational performance. Strategic management journal, 25(13), 1257-1278.
  • Cheng, M. M., & Hackett, R. D. (2021). A critical review of algorithms in HRM: definition, theory, and practice. Human Resource Management Review, 31(1), 100698.
  • Chenthamarakshan, V., Dixit, K., Gattani, M., Goyal, M., Gupta, P., Kambhatla, N., ... & Visweswariah, K. (2010). Effective decision support systems for workforce deployment. IBM Journal of Research and Development, 54(6), 5-1.
  • Chittiprolu, V., Singh, S., Bellamkonda, R. S., & Vanka, S. (2020). A text mining analysis of online reviews of Indian hotel employees. Anatolia, 1-14.
  • Choi, Y., & Choi, J. W. (2020). A study of job involvement prediction using machine learning technique. International Journal of Organizational Analysis.
  • Culnan, M. J. (1987). Mapping the intellectual structure of MIS, 1980-1985: A co-citation analysis. Mis Quarterly, 341-353.
  • Danvila-del-Valle, I., Estévez-Mendoza, C., & Lara, F. J. (2019). Human resources training: A bibliometric analysis. Journal of Business Research, 101, 627-636.
  • Davenport, T. H., Harris, J., & Shapiro, J. (2010). Competing on talent analytics. Harvard business review, 88(10), 52-58.
  • De Laat, M., & Schreurs, B. (2013). Visualizing informal professional development networks: Building a case for learning analytics in the workplace. American Behavioral Scientist, 57(10), 1421-1438.
  • De Mauro, A., Greco, M., Grimaldi, M., & Ritala, P. (2018). Human resources for Big Data professions: A systematic classification of job roles and required skill sets. Information Processing & Management, 54(5), 807-817.
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İK ANALİTİĞİ LİTERATÜRÜNÜN BİBLİYOMETRİK ANALİZİ

Yıl 2022, Cilt: 21 Sayı: 83, 1147 - 1169, 01.07.2022
https://doi.org/10.17755/esosder.950426

Öz

İnsan kaynakları analitiği (İK analitiği) araştırması son yıllarda popüler hale gelmiş ve yeni ortaya çıkan bir araştırma alandır. Bu alanda yapılan çalışmaların hangi çerçevede ilerlediğini görmek, ileride bu alanda yapılacak yeni çalışmalara ışık tutacaktır. Bu çalışma, İK analitiğinin entelektüel çerçeve temelinde nasıl ilerlediğini incelemektedir. Bu araştırma, çalışmaların referansları, yazarları, konuları, atıfları ve dergileri incelenerek literatüre katkı sağlamayı amaçlamaktadır. Bu amaçla, 2010 ile 2021 yılları arasında yayınlanan 178 makaleyi incelerek bibliyometrik analiz tekniği kullanılmıştır. İK analitiği konularını ele alan ve bu makaleleri yayınlayan dergilerde çok çeşitli disiplinler kullanıldı görülmüştür. Makalelerde toplanan ana temalar, büyük veri, yetenek yönetimi ve işgücü analitiği kavramları etrafındadır. Çalışma sonuçları, İK analitiğine yönelik araştırma ilgisinin son yıllarda arttığını göstermektedir. İK profesyonellerinin yetkinlikleri, veri kalitesi, teknolojik gelişmeler, BT departmanı ile işbirliği ana başlıklar iken, literatürün etik konusunu ihmal ettiği görülmüştür.

Kaynakça

  • Andersen, M. K. (2017). Human capital analytics: the winding road. Journal of Organizational Effectiveness: People and Performance.
  • Angrave, D., Charlwood, A., Kirkpatrick, I., Lawrence, M., & Stuart, M. (2016). HR and analytics: why HR is set to fail the big data challenge. Human Resource Management Journal, 26(1), 1-11.
  • Aral, S., Brynjolfsson, E., & Wu, L. (2012). Three-way complementarities: Performance pay, human resource analytics, and information technology. Management Science, 58(5), 913-931.
  • Bag, S., & Pretorius, J. H. C. (2020). Relationships between industry 4.0, sustainable manufacturing and circular economy: proposal of a research framework. International Journal of Organizational Analysis.
  • Barney, J. (1991). Firm resources and sustained competitive advantage. Journal of management, 17(1), 99-120.
  • Bassi, L., & McMurrer, D. (2016). Four lessons learned in how to use human resource analytics to improve the effectiveness of leadership development. Journal of leadership studies, 10(2), 39-43.
  • Ben-Gal, H. C. (2019). An ROI-based review of HR analytics: practical implementation tools. Personnel Review.
  • Berk, L., Bertsimas, D., Weinstein, A. M., & Yan, J. (2019). Prescriptive analytics for human resource planning in the professional services industry. European Journal of Operational Research, 272(2), 636-641.
  • Bohlouli, M., Mittas, N., Kakarontzas, G., Theodosiou, T., Angelis, L., & Fathi, M. (2017). Competence assessment as an expert system for human resource management: A mathematical approach. Expert Systems with Applications, 70, 83-102.
  • Boudreau, J. W., & Ramstad, P. M. (2007). Beyond HR: The new science of human capital. Harvard Business Press.
  • Bowen, D. E. (1996). Market-focused HRM in service organizations: Satisfying internal and external customers. Journal of Market-Focused Management, 1(1), 31-47.
  • Božič, K., & Dimovski, V. (2019). Business intelligence and analytics for value creation: The role of absorptive capacity. International journal of information management, 46, 93-103.
  • Calvard, T. S., & Jeske, D. (2018). Developing human resource data risk management in the age of big data. International Journal of Information Management, 43, 159-164.
  • Carmeli, A., & Tishler, A. (2004). The relationships between intangible organizational elements and organizational performance. Strategic management journal, 25(13), 1257-1278.
  • Cheng, M. M., & Hackett, R. D. (2021). A critical review of algorithms in HRM: definition, theory, and practice. Human Resource Management Review, 31(1), 100698.
  • Chenthamarakshan, V., Dixit, K., Gattani, M., Goyal, M., Gupta, P., Kambhatla, N., ... & Visweswariah, K. (2010). Effective decision support systems for workforce deployment. IBM Journal of Research and Development, 54(6), 5-1.
  • Chittiprolu, V., Singh, S., Bellamkonda, R. S., & Vanka, S. (2020). A text mining analysis of online reviews of Indian hotel employees. Anatolia, 1-14.
  • Choi, Y., & Choi, J. W. (2020). A study of job involvement prediction using machine learning technique. International Journal of Organizational Analysis.
  • Culnan, M. J. (1987). Mapping the intellectual structure of MIS, 1980-1985: A co-citation analysis. Mis Quarterly, 341-353.
  • Danvila-del-Valle, I., Estévez-Mendoza, C., & Lara, F. J. (2019). Human resources training: A bibliometric analysis. Journal of Business Research, 101, 627-636.
  • Davenport, T. H., Harris, J., & Shapiro, J. (2010). Competing on talent analytics. Harvard business review, 88(10), 52-58.
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  • Minbaeva, D. B. (2018). Building credible human capital analytics for organizational competitive advantage. Human Resource Management, 57(3), 701-713.
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  • Yasmin, M., Tatoglu, E., Kilic, H. S., Zaim, S., & Delen, D. (2020). Big data analytics capabilities and firm performance: An integrated MCDM approach. Journal of Business Research, 114, 1-15.
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  • Ziebell, R. C., Albors-Garrigos, J., Schoeneberg, K. P., & Marin, M. R. P. (2019). Adoption and success of e-HRM in a cloud computing environment: a field study. International Journal of Cloud Applications and Computing (IJCAC), 9(2), 1-27.
Toplam 118 adet kaynakça vardır.

Ayrıntılar

Birincil Dil İngilizce
Konular İşletme
Bölüm Araştırma Makalesi
Yazarlar

Merve Vural Allaham 0000-0002-3735-3008

Yayımlanma Tarihi 1 Temmuz 2022
Gönderilme Tarihi 10 Haziran 2021
Yayımlandığı Sayı Yıl 2022 Cilt: 21 Sayı: 83

Kaynak Göster

APA Vural Allaham, M. (2022). BIBLIOMETRIC ANALYSIS OF HR ANALYTICS LITERATURE. Elektronik Sosyal Bilimler Dergisi, 21(83), 1147-1169. https://doi.org/10.17755/esosder.950426

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Elektronik Sosyal Bilimler Dergisi (Electronic Journal of Social Sciences), Creative Commons Atıf-GayriTicari 4.0 Uluslararası Lisansı ile lisanslanmıştır.

ESBD Elektronik Sosyal Bilimler Dergisi (Electronic Journal of Social Sciences), Türk Patent ve Marka Kurumu tarafından tescil edilmiştir. Marka No:2011/119849.