Analysing post adoption factors for determining MOOC continuance intentions: interpretive structural modelling and fuzzy MICMAC approach

Neeraj Chopra, Rajiv Sindwani and Manisha Goel

International Journal of Innovation and Learning, 2025, vol. 38, issue 3, 263-281

Abstract: This study investigates the post-adoption behaviour of MOOC participants and aims to enhance our understanding of the cognitive-affective-conative framework in this context. Despite the recognised benefits of MOOCs, their adoption is still at an early stage, which is crucial for MOOC platforms due to high dropout rates. Fifteen post-adoption factors were identified through a comprehensive literature review and expert opinions, and a hierarchical model was developed using ISM and, fuzzy MICMAC techniques to capture the mutual interactions among these factors. Intentions to recommend and cultural intelligence occupied the highest and lowest positions in the hierarchical model, respectively. The fuzzy MICMAC analysis examined the driving and dependence power of the factors for clustering purposes, revealing the absence of autonomous factors and ten factors in the linkage region. This pioneering work provides practitioners and decision-makers with valuable resources to improve retention rates based on the relationships and power dynamics among these factors.

Keywords: MOOC; cognitive-affective-conative framework; adoption; ISM; fuzzy MICMAC. (search for similar items in EconPapers)
Date: 2025
References: Add references at CitEc
Citations:

Downloads: (external link)
http://www.inderscience.com/link.php?id=148421 (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:ids:ijilea:v:38:y:2025:i:3:p:263-281

Access Statistics for this article

More articles in International Journal of Innovation and Learning from Inderscience Enterprises Ltd
Bibliographic data for series maintained by Sarah Parker ().