Management of scientific and ancestral knowledge: a decision-making model in mezcal industry in Mexico - Terán-Bustamante, Antonia; Martínez-Velasco, Antonieta; Leyva-Hernández, Sandra Nelly (Frontiers in Artificial Intelligence, 2025)
IntroductionKnowledge 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.MethodsThe analysis methods were carried out through decision-making, machine-learning techniques, and fuzzy logic.ResultsThe 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.DiscussionThis knowledge management model aims to guide small producers to be more productive and competitive through the support of a facilitator.