Management of scientific and ancestral knowledge: a decision-making model in mezcal industry in Mexico
Journal
Frontiers in Artificial Intelligence
ISSN
2624-8212
Publisher
Frontiers Media SA
Date Issued
2025
Author(s)
Leyva-Hernández, Sandra Nelly
Type
text::journal::journal article
Abstract
Introduction: Knowledge management is essential to ensure the sustainability of rural communities and small producers since it generates value for innovation, productivity, and competitiveness. The aim of this study is to identify relevant factors for adequate decision-making in managing knowledge in the Mexican mezcal industry and its impact on developing rural communities and small producers - mezcaleros. For this purpose, a decision-making model for managing scientific and ancestral knowledge is created to support links with universities, research centers, and rural communities to accelerate innovation and competitiveness in this sector. Methods: The analysis methods were carried out through decision-making, machine-learning techniques, and fuzzy logic. Results: The Bayesian Network model suggests that the preceding variables to optimize the Mezcaleros Knowledge Management are the Mezcaleros Indigenous community, the Denomination of Origin, Scientific and Ancestral Knowledge, Waste Management and Use, and Jima. Discussion: This knowledge management model aims to guide small producers to be more productive and competitive through the support of a facilitator. ©The authors ©Frontiers in Artificial Intelligence ©Frontiers Media SA.
License
Acceso Abierto
How to cite
Terán-Bustamante, A., Martínez-Velasco, A., & Leyva-Hernández, S. N. (2025). Management of scientific and ancestral knowledge: a decision-making model in mezcal industry in Mexico. Frontiers in Artificial Intelligence, 8. https://doi.org/10.3389/frai.2025.1570617