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The purpose of this study is to analyze the combined effect of eight factors – performance expectancy (PE), effort expectancy (EE), hedonic motivation (HM), system quality (SQ), information quality (IQ), service quality (SEQ), digital literacy (DL) and computer anxiety (CA) on learners’ behavioral intention (BI) toward the adoption of e-learning in higher education institutions (HEIs) in India.

The study used factors from two theoretical models, the extended Unified Theory of Acceptance and Use of Technology and the DeLone and McLean Information Systems Success model. The study also considered DL and CA as additional factors because they could affect a learner’s intention in a developing country like India. Data were collected from three HEIs in Southern India and analyzed using fuzzy qualitative and comparative analysis (fsQCA).

The results of the study emphasize the importance of considering both individual and technological factors in e-learning adoption and provide evidence for the significance of integrating multiple theories in understanding the complex relationship between factors and learners’ BI. Four different configurations of the eight factors: EE*HM*SQ*IQ*SEQ*DL*∼CA; PE*EE*HM*SQ*IQ*DL*CA; PE*EE*HM*IQ*SEQ*DL*CA; and PE*EE*SQ*IQ*SEQ*DL*CA found to be sufficient to cause learners’ BI to use e-learning.

This study explores the complex relationship between different factors and learners’ intention to adopt e-learning using the fsQCA method. These findings may need further validation in HEIs across different geographical locations.

This study provides practical insights for HEIs in India and other developing countries on how different factors combine and interact to determine e-learning adoption in multiple contexts.

Using fsQCA as a novel and rigorous method, this study uncovers the complex and nonlinear causal relationships among various factors that affect e-learning adoption. This study provides a holistic and contextualized understanding of e-learning adoption in a developing country’s scenario. This study can inform educators and policymakers on how to design and implement effective e-learning strategies that suit different learner profiles and contexts.