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

Roberto Pico-Saltos, David Sabando-Vera (), Marcela Yonfa-Medranda, Javier Garzás and Andrés Redchuk
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Roberto Pico-Saltos: Department of Statistics and Operations Research, Rey Juan Carlos University, 28933 Madrid, Spain
David Sabando-Vera: Faculty of Social and Humanistic Sciences, ESPOL Polytechnic University, Campus Gustavo Galindo Km, 30.5 Vía Perimetral, Guayaquil 9015863, Ecuador
Marcela Yonfa-Medranda: Faculty of Social and Humanistic Sciences, ESPOL Polytechnic University, Campus Gustavo Galindo Km, 30.5 Vía Perimetral, Guayaquil 9015863, Ecuador
Javier Garzás: Department of Statistics and Operations Research, Rey Juan Carlos University, 28933 Madrid, Spain
Andrés Redchuk: Department of Statistics and Operations Research, Rey Juan Carlos University, 28933 Madrid, Spain

Sustainability, 2022, vol. 15, issue 1, 1-25

Abstract: 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.

Keywords: Hierarchical Component Model (HCM); career success; PLS-SEM; multigroup analysis (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2022
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Persistent link: https://EconPapers.repec.org/RePEc:gam:jsusta:v:15:y:2022:i:1:p:540-:d:1018153

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