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Author: search.filters.author.Leyva-Hernández, Sandra NellySubject: search.filters.subject.Mexico

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    Item type:Publication,
    Management of scientific and ancestral knowledge: a decision-making model in mezcal industry in Mexico
    (Frontiers Media SA, 2025)
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    Leyva-Hernández, Sandra Nelly
    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.
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    Item type:Publication,
    Knowledge and innovation management model in the mezcal industry in Mexico
    (Elsevier, 2025)
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    Leyva-Hernández, Sandra Nelly
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    This research aims to study and analyze knowledge management in the mezcal sector in Mexico and its impact on the development of rural communities through Bayesian-networks with machine learning techniques. A model is made in which the critical factors that impact is identified and quantified to optimally manage the knowledge that generates value and translates into innovation and competitive advantages. The results show that the most relevant factors to adequate knowledge and innovation management are commercialization and marketing capacity, value system model, ancient knowledge, strategic business model, process management, competencies, Business structure model, Facilitators governments, universities, mezcaleros, and indigenous communities. ©The authors ©Elsevier Ltd.
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