The study objective is to see how human resource management (HRM) could rely on small data evidence-based analytics to gauge employee commitment in a sub-Saharan African University. A 7-point Likert scale questionnaire on academic employee commitment in Kenya Public Universities was designed, validated and pilot tested. Out of around 60 questionnaires administered, only 31 responses were obtained before the Corona Virus (COVID-19) pandemic lockdowns in Kenya. The responses were subjected to the Modeler analyses using the statistical package for social sciences (SPSS version 21) to generate twelve optimal ARIMA (0,0,0) models for further statistical analyses. Results indicate 46.7% of employees want to spend the rest of their career in the organisation, over 61.2% of employees felt alienated and 34.9% were not emotionally attached. Around 59.3%, 64.0% and almost all employees tested on different metrics have difficulty leaving the organisation now. Although 28.9% of employees could leave abruptly, 64.6% of employees felt acculturated and 29.7% would remain at all costs. Overall, add-on effects of willingness to stay and bear with the organisation, emotional attachment, alienation, moral obligation, beneficial to remain, discouragement levels, organisational culture and being sold out to organisation could influence employee commitment levels. Thus, contributing to the HRM field, especially because the twelve-layered cascade of a series-parallel network made up of ladder and lattice structures of shared human and material resources management was used to deduce the Jackson’s theorem. Future research shall consider larger sample sizes to enable us to confirm or refute the conclusions derived in this study.
A two-stage parallel network DEA model for analyzing the operational capability of container terminals