AI-Driven Hybrid Learning for Sustainable Development : A Bibliometric Analysis and Systematic Literature Review - Makhija, Ritu; Aggarwal, Shalini; Singh, Yashvardhan (Prabandhan: Indian Journal of Management, 2025)
Purpose : This study investigated the role of artificial intelligence (AI) in hybrid learning (HL) and its contribution to sustainable development using bibliometric analysis and systematic literature review. It also analyzed the antecedents, decisions, and outcomes associated with AI in HL. Design Methodology : The study utilized data from 144 Scopus-indexed articles from 2010 to 2024. The R-studio software was used to generate tables and figures, providing insights into research trends. Findings : The findings indicated that the UAE emerged as a leader in research on AI in HL and sustainable development, followed by Germany and Malaysia. The Institute of Electrical and Electronics Engineers was the top publisher with 22 papers, while Springer ranked second with 20 publications. The most frequently used keywords across the literature are “e-learning” (60 occurrences) and “sustainable development” (56 occurrences). Practical/Social Implications : These findings highlighted the increasing significance of AI-driven HL and its potential to encourage sustainable educational practices on a global scale. Originality/Value : This study provided an in-depth analysis of AI applications in HL, emphasizing their role in advancing sustainable development. It identified key trends, leading authors, publication patterns, and research gaps to support future research endeavors.