Unravelling Lifelong Learning in Multi-Generational Workforce Using Text Mining

Jaya Gupta and Pooja Misra

Business Perspectives and Research, 2025, vol. 13, issue 1, 51-69

Abstract: Accelerated structural transformations characterize the workplace post-pandemic. A lifelong learning ecosystem must be built to ensure a smooth and inclusive transition since generational diversity is ubiquitous in contemporary organizations. The present phenomenological qualitative study attempts to explore generational diversity from the lens of lifelong learning construct across the three prominent generations, X, Y, and Z, present in the workforce. The data collected from 24 semi-structured telephonic interviews were analyzed using text mining and topic modeling. The results suggest differences and similarities among the members of different generations. The topics derived waxed and waned across generations. While the drive to engage in continuous learning varied across generational cohorts, the preferred mode for engaging in it was similar. The study provides insights that could help enhance the effectiveness of human resource management practices and firms’ competitiveness during tough times. Further, the findings contribute to the existing literature by adopting machine learning as a tool to extract and decode the latent topics across the three generational cohorts.

Keywords: Lifelong learning; multigenerational workforce; theory of planned behavior; Covid 19; text mining; qualitative (search for similar items in EconPapers)
Date: 2025
References: Add references at CitEc
Citations:

Downloads: (external link)
https://journals.sagepub.com/doi/10.1177/22785337221148575 (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:sae:busper:v:13:y:2025:i:1:p:51-69

DOI: 10.1177/22785337221148575

Access Statistics for this article

More articles in Business Perspectives and Research
Bibliographic data for series maintained by SAGE Publications ().