Predicting Employability of Congolese Information Technology Graduates Using Contextual Factors: Towards Sustainable Employability

Héritier Nsenge Mpia (), Simon Nyaga Mwendia and Lucy Waruguru Mburu
Additional contact information
Héritier Nsenge Mpia: Faculté de Sciences Economiques et de Gestion, Université de l’Assomption au Congo, Butembo P.O. Box 104, Democratic Republic of the Congo
Simon Nyaga Mwendia: School of Technology, KCA University, Nairobi P.O. Box 56808, Kenya
Lucy Waruguru Mburu: Department of Networks and Applied Computing, KCA University, Nairobi P.O. Box 56808, Kenya

Sustainability, 2022, vol. 14, issue 20, 1-17

Abstract: Predicting employability in an unstable developing country requires the use of contextual factors as predictors and a suitable machine learning model capable of generalization. This study has discovered that parental financial stability, sociopolitical, relationship, academic, and strategic factors are the factors that can contextually predict the employability of information technology (IT) graduates in the democratic republic of Congo (DRC). A deep stacking predictive model was constructed using five different multilayer perceptron (MLP) sub models. The deep stacking model measured good performance (80% accuracy, 0.81 precision, 0.80 recall, 0.77 f1-score). All the individual models could not reach these performances with all the evaluation metrics used. Therefore, deep stacking was revealed to be the most suitable method for building a generalizable model to predict employability of IT graduates in the DRC. The authors estimate that the discovery of these contextual factors that predict IT graduates’ employability will help the DRC and other similar governments to develop strategies that mitigate unemployment, an important milestone to achievement of target 8.6 of the sustainable development goals.

Keywords: deep stacking model; Democratic Republic of Congo; exploratory factor analysis; sustainable development goals; unemployment (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
https://www.mdpi.com/2071-1050/14/20/13001/pdf (application/pdf)
https://www.mdpi.com/2071-1050/14/20/13001/ (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:gam:jsusta:v:14:y:2022:i:20:p:13001-:d:939186

Access Statistics for this article

Sustainability is currently edited by Ms. Alexandra Wu

More articles in Sustainability from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().