Exploring the Factors Affecting Chatbot Use in Higher Education and Its Impact on Social Sustainability Using a Hybrid SEM-ANN Approach
Loading...
Date
2023-06
Authors
Journal Title
Journal ISSN
Volume Title
Publisher
The British University in Dubai (BUiD)
Abstract
Previous studies have identified various drivers of chatbot adoption through different technology adoption theories. However, these studies have not been thoroughly reviewed and synthesized. Most studies have focused on examining the intention of using chatbots, with limited investigations on actual use and sustainable intention. This thesis explores the factors influencing the sustainable adoption of chatbots in higher education, specifically focusing on social sustainability. It aims to develop an integrated model that comprehensively examines the influencing factors, moderating effects, and organizational dynamics that shape chatbot adoption. The research begins with a comprehensive literature review to identify factors that generally influence chatbot adoption. These factors encompass technological, individual, organizational, and contextual dimensions. Building upon this literature review, the conceptual model is developed, addressing the research gaps in the existing literature and focusing on chatbot acceptance in the higher education sector. The systematic review includes an analysis of empirical studies published between 2016 and September 2022, resulting in 219 eligible studies out of 3,942 reviewed. The main findings reveal that the Technology Acceptance Model (TAM), Social Presence Theory (SPT), and Computers as Social Actors (CASA) are the prevailing theories explaining chatbot adoption. Anthropomorphism is the most examined external factor, followed by trust, enjoyment, and interactivity. The conceptual framework integrates established theories such as Task-Technology Fit (TTF), Source Credibility Theory, Social Presence Theory (SPT), and additional factors specific to chatbot adoption in higher education. A quantitative survey is administered to a sample of 341 individuals and students from the higher education sector in the UAE, capturing diverse perspectives on chatbot adoption. The model is then validated using advanced analytical techniques, including Partial Least Squares Structural Equation Modelling (PLS-SEM) and Artificial Neural Networks (ANN). The findings contribute to understanding chatbot adoption in higher education, providing insights into key drivers, challenges, and implications for social sustainability. The study's findings highlight factors such as task-technology fit, credibility, and social presence that significantly influence the intention to sustainably use chatbots in higher education. The sensitivity analysis reveals the importance of social presence, followed by credibility and task-technology fit, in influencing chatbot use. The chatbots’ technological characteristics have a greater impact than the task characteristics, and visual cues are perceived as more important than invisible and verbal cues for chatbot social presence. Trustworthiness is the most significant factor impacting credibility, followed by ease of use, tailoring, and commercial implications. However, Expertise, Real-World Feel, and Amateurism do not significantly impact credibility. These results contribute to developing acceptance models that can guide the design, implementation, and evaluation of chatbot initiatives in higher education institutions, fostering social sustainability. The theoretical contributions lie in developing an integrated model that extends existing theories to the context of chatbot adoption in higher education. The model provides a comprehensive understanding of the influencing factors and their interrelationships, offering a valuable framework for future research. From a practical perspective, the findings assist higher education institutions in strategically implementing and managing chatbots. The insights gained from this study can guide the development of effective strategies to promote chatbot acceptance, address privacy concerns, and leverage chatbots' potential for enhancing social sustainability in higher education settings.
Description
Keywords
chatbot adoption, higher education, social sustainability,