Innovation and Technological Management Model in the Tequila Sector in Mexico

Antonia Terán-Bustamante, Antonieta Martínez-Velasco, Víctor Manuel Castillo-Girón and Suhey Ayala-Ramírez
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Antonia Terán-Bustamante: Facultad de Ciencias Económicas y Empresariales, Universidad Panamericana, Ciudad de México 03920, Mexico
Antonieta Martínez-Velasco: Facultad de Ingeniería, Universidad Panamericana, Ciudad de México 03920, Mexico
Víctor Manuel Castillo-Girón: Departamento de Ciencias Económico Administrativas, Centro Universitario de los Valles, University of Guadalajara, Ameca 46600, Mexico
Suhey Ayala-Ramírez: Departamento de Ciencias Sociales y Humanidades, Centro Universitario de los Valles, University of Guadalajara, Ameca 46600, Mexico

Sustainability, 2022, vol. 14, issue 12, 1-23

Abstract: Creativity, ideas, and an entrepreneurial attitude are needed to innovate. However, it is also necessary to have practical instruments that allow innovations to be reflected in the company. One of those tools is technology. This research aims to analyze innovation and technology in the tequila industry through Bayesian networks with machine learning techniques. Likewise, an innovation and technology management model will be developed to make better decisions, which will allow the company to innovate to generate competitive advantages in a mature low-tech industry. A model is made in which the critical factors that influence management innovation and technology optimally to generate value translate into competitive advantages. The evidence shows that the optimal or non-optimal management of knowledge management and its various factors, through the causality of the variables, allow the interrelation to be more adequately captured to manage it. The results show that the most relevant factors for adequate management of innovation and technology are knowledge management, sales and marketing, organizational and technological architecture, national and international markets, cultivation of raw materials, agave, and management, use of waste, and not research and development.

Keywords: innovation; Bayesian networks; machine learning; Mexico; technology model; technological innovation; tequila industry (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2022
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