# Management of scientific and ancestral knowledge: a decision-making model in mezcal industry in Mexico

## TL;DR

This paper presents a decision-making model to manage scientific and ancestral knowledge in the Mexican mezcal industry to support rural communities and small producers.

## Contribution

A novel decision-making model integrating scientific and ancestral knowledge for the mezcal industry is proposed.

## Key findings

- The model identifies key factors like indigenous community and denomination of origin for effective knowledge management.
- Bayesian Network analysis highlights variables crucial for optimizing mezcaleros' knowledge management.
- The model aims to enhance productivity and competitiveness through collaboration with universities and research centers.

## Abstract

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.

The analysis methods were carried out through decision-making, machine-learning techniques, and fuzzy logic.

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.

This knowledge management model aims to guide small producers to be more productive and competitive through the support of a facilitator.