IDEAS home Printed from https://ideas.repec.org/a/dbk/datame/v4y2025ip1010id1056294dm20251010.html
   My bibliography  Save this article

A Fuzzy Logic-Based Decision Support System for Predicting Entrepreneurial Intention Among Textile Students

Author

Listed:
  • Nora Abia
  • Hanane Sadeq
  • Ibtissam Medarhri
  • Aziz Soulhi

Abstract

This article presents a fuzzy logic-based decision support system, which functions as a predictive model for assessing and guiding entrepreneurial intention among Moroccan university students in the textile sector. The model used four key variables, namely Desirability, Self-Concept, University Context, and Feasibility. These latter and their influence were identified through a previous ANN model. Fuzzy memberships functions were designed, and 81 expert validated rules were constructed for the fuzzy model. The model provided entrepreneurial scores based on the students’ inputs and was tested on a new 40 student survey responses. Key findings highlighted that desirability and self- concept are critical drivers of entrepreneurial intention, and the results showed an alignment with expert judgments and theoretical models. Furthermore, the model provided personalised recommendations for both students and university and makes clear contributions to both theoretical and practical advancements in the entrepreneurship studies.

Suggested Citation

Handle: RePEc:dbk:datame:v:4:y:2025:i::p:1010:id:1056294dm20251010
DOI: 10.56294/dm20251010
as

Download full text from publisher

To our knowledge, this item is not available for download. To find whether it is available, there are three options:
1. Check below whether another version of this item is available online.
2. Check on the provider's web page whether it is in fact available.
3. Perform a
for a similarly titled item that would be available.

More about this item

Statistics

Access and download statistics

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:dbk:datame:v:4:y:2025:i::p:1010:id:1056294dm20251010. 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: Javier Gonzalez-Argote (email available below). General contact details of provider: https://dm.ageditor.ar/ .

Please note that corrections may take a couple of weeks to filter through the various RePEc services.

IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.