Abstract
The objective of this study is to show the dynamics of the evolution on research of the generations by means of analysis of journal publications from the category of management and business from Clarivate Analytics Web of Science. Bibliometric analysis is used to unveil the authors, journals, institutions, and the most influential countries on the subject from 2001 to date. The most pertinent studies are presented that show the main characteristics of the five generations that can currently be found in the workplace, namely the Silent Generation, Baby Boomers, Generation X, Generation Y and Generation Z. The results highlight that the studies focus on countries and regions with more developed economies. Studies are scarcer from countries and regions with emerging economies such as Latin America and the Caribbean, Africa, Eastern Europe and the Middle East. Likewise, there is evidence of the lack of qualitative studies on Generation Z, which will be of greater importance in the labour force or employment market and with higher purchasing power. The results add knowledge to academics to define their research strategies. For the practitioners it contributes information on the most pertinent academics on the study of generations, which facilitates potential candidates to contract or hire in case they need to study the characteristics of their workforce to define recruitment policies, career planning or motivation.
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The authors thank the two reviewers’ encouraging suggestions to a previous version of the manuscript.
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All authors contributed to the study conception and design. Maximiano Ortiz-Pimentel, and Guillermo Armando Ronda-Pupo performed material preparation, and analysis. Maximiano Ortiz-Pimentel, and Carlos Molina wrote the first draft of the manuscript, and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript.
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Ortiz-Pimentel, M., Molina, C. & Ronda-Pupo, G.A. Bibliometric assessment of papers on generations in management and business journals. Scientometrics 125, 445–469 (2020). https://doi.org/10.1007/s11192-020-03670-8
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DOI: https://doi.org/10.1007/s11192-020-03670-8