Investigating the relationships between MOOC consumers' perceived quality, emotional experiences, and intention to recommend: an NLP-based approach

Abstract

PurposeThe paper aims to explore and examine the factors that influence the post-consumption behavioral intentions of education consumers with the help of online reviews from a Massive Open Online Course (MOOC) platform in the knowledge payment context.Design/methodology/approachThe paper adopted a novel mixed-method approach based on natural language processing (NLP) techniques. Variables were identified using topic modeling drawing upon 14,585 online reviews from a global commercial MOOC platform (Udemy.com). The relationships among identified factors, such as perceived quality dimensions, consumption emotions, and intention to recommend, were then tested from a cognition-affect-behavior (CAB) perspective using partial least squares structural equation modeling (PLS-SEM).FindingsResults indicate that course content quality, instructor quality, and platform quality are strong predictors of consumers' emotions and intention to recommend. Interestingly, course content quality displays a positive effect on invoking negative emotions in the MOOC context. Additionally, positive emotions mediate the relationships between three perceived qualities and the intention to recommend.Originality/valueLimited research has been conducted regarding MOOC consumers' post-consumption intentions in the knowledge payment context. Findings of this study address the limited literature on MOOC qualities and consumer post-consumption behaviors, which contribute to a comprehensive understanding of MOOC learners' experiences at a meso-level for future paid-MOOC creators.Peer reviewThe peer review history for this article is available at: https://publons.com/publon/10.1108/OIR-09-2021-0482/

Understanding the acceptance of multisided teleconsultation platforms: a critical analysis and proposal of a theorical model

“…When individuals perceive that a teleconsultation platform is well-controlled, reliable, and efficient, they are more likely to have a positive attitude towards the platform. This positive attitude, in turn, influences their intention to recommend the platform to others (Ma et al, 2022).…”