Metaverse is an immersive three-dimensional (3D) virtual world inhabited by avatars beyond the physical realm. The COVID-19 pandemic has disrupted the education system and the need to accelerate the digitalization of education has received a lot of attention. Metaverse can be an alternative solution for sociocultural interaction and to continue education. Accordingly, this study aimed to identify key factors in predicting the educational sustainability of Metaverse. The study empirically tested the role of psychological needs (i.e. hedonic motivation, affiliation, dominance, achievement, and autonomy) in predicting educational sustainability. The study employed a hybrid method integrating covariance-based structural-equation-modeling (CB-SEM) and deep artificial neural network (ANN) model. The CB-SEM results indicated that the need for autonomy and hedonic motivation significantly predicted the educational sustainability of Metaverse. Further, deep ANN models indicated that hedonic motivation was the most important input factor, followed by autonomy, affiliation, dominance, and achievement. Findings have practical implications for developers of the Metaverse environments and theoretical contributions for educators who manage and implement such environments.

The Internet of Things (IoT) holds immense potential for the social and economic development of developing countries, as recognized by academia and professionals. However, there is a notable lack of theoretical research on IoT adoption within agricultural settings. To address this gap, this study introduces a model focusing on nine critical “Technology-Organization-Environment” (TOE) factors. Empirical validation was conducted using data from 179 managers in diverse agricultural organizations. The research model was evaluated by using “Partial Least Squares Structural Equation Modeling” (PLS-SEM). The results underscored the significance of governmental support and technological compatibility in driving IoT adoption. Moreover, financial considerations within organizations and the evolving digital landscape were identified as key influencers of smart farm adoption. This study offers valuable insights with significant implications for sustainable IoT adoption in research and practical applications.