Unravelling the Web of E-Learning Adoption

Since their advent, E-learning platforms have been deemed resourceful and impactful tools for disseminating knowledge. They have been responsible for making education more vocational, accessible and interactive. Especially during the COVID-19 pandemic when the entire world was compelled to move online, e-learning acted as a blessing in terms of keeping education institutions up and running, and the students engaged. However, the lack of adoption of e-learning platforms still remains to be a challenge for platform makers and marketers. Therefore, it is significant to find innovative ways to drive the adoption of e-learning platforms among students. This research explores the impact of network effects on the adoption of e-learning platforms among university students. It also evaluates the role of two antecedents of trust – the propensity to trust and initial trust, in moderating the relationship between network effects and adoption intention. A quantitative method of research was employed and an experimental survey was circulated amongst university students in India, The Netherlands and The United States of America. The respondents were randomly assigned one out of the four conditions in the experiment and a total of 120 valid responses were collected. The data were analysed using hierarchical multiple regression analysis and Hayes’ Moderation Analysis Model 2. The appropriate tests for reliability and validity were conducted. A manipulation check was conducted by forming the dummy correspondents for independent variables to check if the conditions were randomly assigned, along with a T-test. The results of the analysis were found to be insignificant for the impact of network effects on e-learning adoption. Moreover, for moderation analysis, the interactions of moderating variables with dependent and independent variables were also found to be insignificant. The interpretation of the analysis was reported in the discussion chapter and the theoretical and practical implications of the study were traced. The research serves a pivotal foundation in the e-learning adoption literature. The research model can be deployed to discern the factors affecting e-learning adoption. This research also challenges and substantiates previous research on technology adoption. It concludes that platform heterogeneity, geographical factors, diversity in sample characteristics and cultural contexts should also be considered while conducting research to understand the factors affecting e-learning adoption amongst students.