Predicting the core determinants of cloud-edge computing adoption (CECA) for sustainable development in the higher education institutions of Africa: A high order SEM-ANN analytical approach

Aims: In the recent past, many studies have been conducted to elucidate the determinants affecting cloud computing adoption at different institutional levels. The study aims to identify how technological, organizational, environmental, and socio-culture factors influence the adoption of cloud edge technologies. Methods: The proposed theoretical framework is based on the main determinants of the TOE theory and extends it by incorporating a socio-cultural predictor. Eighteen core manifests were extracted from previous literature and the standard theories. The researcher used a proper validation process to create a valid questionnaire. Two-stage analytical methods, i.e., SEM and ANN, test the proposed model. SEM is applied to test all core hypotheses, and identified significant predictors are considered input items to the neural network model to ascertain the relative magnitude of each manifest in a subsequent stage. Findings: The outcomes of the quantitative investigation outline the relationship between chosen constructs and cloud-edge computing adoption (CECA). The study supports all core hypotheses using SEM. Novelty: The study is one of the novel attempts to empirically confirm and estimate the synergy of multimodal structure to elucidate the relative importance of manifests to be considered by top management of HEIs.