Hierarchical Component Model (HCM) of Career Success and the Moderating Effect of Gender, from the Perspective of University Alumni: Multigroup Analysis and Empirical Evidence from Quevedo, Ecuador

The professional success of graduates is closely linked to the value of university performance, perhaps much more so than other indicators. This study analyses the predictive and explanatory capacity of a model on the career success of university alumni in a developing country (Ecuador), which serve...

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Bibliographic Details
Published in:Sustainability 2023-01, Vol.15 (1), p.540
Main Authors: Pico-Saltos, Roberto, Sabando-Vera, David, Yonfa-Medranda, Marcela, Garzás, Javier, Redchuk, Andrés
Format: Article
Language:English
Subjects:
Career development
Careers
College graduates
Demographic aspects
Developing countries
Economic aspects
Gender
Higher education
Hypotheses
LDCs
Literature reviews
Perceptions
Permutations
Professionals
Regression analysis
Sex differences
Statistical analysis
Success
Sustainability
Variance
Women
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Summary:The professional success of graduates is closely linked to the value of university performance, perhaps much more so than other indicators. This study analyses the predictive and explanatory capacity of a model on the career success of university alumni in a developing country (Ecuador), which serves as empirical evidence on the subject; we examine the moderating effect of gender on the relationships between constructs in the model. We use a Hierarchical Component Model (HCM) of Partial Least Squares Structural Equations (PLS-SEM) and a permutation-based multigroup analysis for moderation. The used database comprises 444 records from a self-administered survey of graduates of the State Technical University of Quevedo (UTEQ)—Ecuador. On the findings, the model proposed has good explanatory and predictive power for career success. Objective success has a lower incidence of professional success (22% of the variance explained) than subjective success (78% of the variance explained). In none of the latent variable correlations in the model were gender differences between men and women found to be statistically significant. Finally, we also cover the study’s theoretical and practical implications.
ISSN:2071-1050
2071-1050
DOI:10.3390/su15010540