New Generation, Great Expectations: A Field Study of the Millennial Generation
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This study investigated the career expectations and priorities of members of the “millennial” generation (born in or after 1980) and explored differences among this cohort related to demographic factors (i.e., gender, race, and year of study) and academic performance.
Data were obtained from a national survey of millennial undergraduate university students from across Canada (N = 23,413). Data were analyzed using various multivariate techniques to assess the impacts of demographic variables and academic achievement on career expectations and priorities.
Millennials placed the greatest importance on individualistic aspects of a job. They had realistic expectations of their first job and salary but were seeking rapid advancement and the development of new skills, while also ensuring a meaningful and satisfying life outside of work. Our results suggest that Millennials’ expectations and values vary by gender, visible minority status, GPA, and year of study, but these variables explain only a small proportion of variance.
Changing North American demographics have created a crisis in organizations as they strive to recruit and retain the millennial generation, who purportedly hold values, attitudes, and expectations that are significantly different from those of the generations of workers that preceded them. A better understanding of the Millennials’ career expectations and priorities helps employers to create job offerings and work environments that are more likely to engage and retain millennial workers.
This is a large-sample study that provides benchmark results for the millennial generation, which can be compared to results from other generational cohorts, and to millennial cohorts in the future as they progress through their life-cycle. This is one of the few studies that examines demographic heterogeneity within the millennial cohort.
KeywordsCanada Career expectations Millennial generation University students
Preparation of this manuscript is supported in part by a SSHRC grant to the research team. The authors would like to thank Brainstorm, DECODE, and Universum for making the data available to us. We also wish to thank Lisa Kuron for her invaluable contributions to the preparation and revision of this article.
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