Author
Listed:
- Daniel Moise
(The Faculty of Marketing, The Bucharest University of Economic Studies, 010404 Bucharest, Romania)
- Elena Goga
(The Faculty of Marketing, The Bucharest University of Economic Studies, 010404 Bucharest, Romania)
- Georgiana Rusu
(The Faculty of Marketing, The Bucharest University of Economic Studies, 010404 Bucharest, Romania)
- Raluca-Giorgiana Chivu (Popa)
(The Faculty of Marketing, The Bucharest University of Economic Studies, 010404 Bucharest, Romania)
- Mihai-Cristian Orzan
(The Faculty of Marketing, The Bucharest University of Economic Studies, 010404 Bucharest, Romania)
Abstract
This study investigates consumer satisfaction in e-learning services by addressing a specific gap in the literature: the limited integration of sustainability principles and behavioral modeling in understanding satisfaction drivers in online education. While existing studies have explored engagement and usability, few have considered how sustainability-related factors influence satisfaction in digital learning environments. Based on a conceptual model involving system quality, service quality, motivation, and cognitive engagement, we applied structural equation modeling (WarpPLS) to a sample of 312 university students from Romania, using mainstream learning management systems (LMS). Data were collected from students at the Bucharest University of Economic Studies using a convenience sampling method. The results show that service quality and cognitive engagement are the strongest predictors of satisfaction. This study offers practical recommendations for improving sustainable digital marketing strategies in e-learning, such as enhancing support services and aligning platform features with eco-conscious consumer expectations.
Suggested Citation
Daniel Moise & Elena Goga & Georgiana Rusu & Raluca-Giorgiana Chivu (Popa) & Mihai-Cristian Orzan, 2025.
"Data-Driven Insights into Consumer Satisfaction in E-Learning: Implications for Sustainable Digital Marketing,"
Sustainability, MDPI, vol. 17(14), pages 1-15, July.
Handle:
RePEc:gam:jsusta:v:17:y:2025:i:14:p:6445-:d:1701506
Download full text from publisher
Corrections
All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jsusta:v:17:y:2025:i:14:p:6445-:d:1701506. See general information about how to correct material in RePEc.
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
We have no bibliographic references for this item. You can help adding them by using this form .
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .
Please note that corrections may take a couple of weeks to filter through
the various RePEc services.