From interaction to impact: Examining the role of chatbots in enhancing social sustainability using SEM-ANN approach

Despite the growing integration of Artificial Intelligence (AI) in educational settings, there is a notable gap in the literature regarding the role of chatbots in promoting social sustainability in higher education. This study aims to fill this void by developing a model that combines constructs from Task-Technology Fit (TTF), Source Credibility Theory (SCT), Fogg's Model of Web Credibility, and Social Presence Theory (SPT). This research utilizes a hybrid approach of Structural Equation Modeling (SEM) and Artificial Neural Networks (ANN) to evaluate the proposed model based on data collected from 341 students. The results confirmed 13 out of 16 hypotheses, underscoring the pivotal roles of credibility, social presence, and TTF in enhancing chatbot utilization, which, in turn, supports social sustainability. The ANN findings showed that TTF is the most important factor influencing chatbot use, with a normalized importance of 99.1 %. The significance of this research lies in its potential to guide the development of chatbot applications that effectively support universities' educational and social objectives, making a vital contribution to the discourse on technology's role in sustainable educational practices.