Generational Theory and Cohort Analysis
Alan Okros ()
Additional contact information
Alan Okros: Canadian Forces College
Chapter 2 in Harnessing the Potential of Digital Post-Millennials in the Future Workplace, 2020, pp 33-51 from Springer
Abstract:
Abstract This chapter introduces the broad frameworks of generational theory and cohort analyses which are presented in the literature as a means to examine groups and/or describe those of similar ages and, potentially, predict key characteristics of groups into the future. Our analyses indicate that the predictive aspects of generational theories are not supported and we recognize significant intra-generational variations will persist owing to age, socioeconomic status, parenting styles, and technological diffusion. Despite these shortcomings, we explore the ways in which broad social factors and shared experiences can influence how a group of people close in age and sharing important experiences can interact with society and develop values. Of greater importance, we conclude that each age group is likely to acquire labels, ascribed characteristics and broad stereotypes which, whether accurate or not, will influence how others see them and, in return, how members of the defined group will see themselves and others. Accordingly, we believe it is a useful exercise to present these brief portraits in order to identify perceived commonalities and shared experiences.
Date: 2020
References: Add references at CitEc
Citations: View citations in EconPapers (2)
There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.
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:spr:mgmchp:978-3-030-25726-2_2
Ordering information: This item can be ordered from
http://www.springer.com/9783030257262
DOI: 10.1007/978-3-030-25726-2_2
Access Statistics for this chapter
More chapters in Management for Professionals from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().