Journal of Open Innovation: Technology, Market and Complexity (Sep 2024)

Foresight study using scenarios and the Delphi method in the leather agroindustrial chain to 2035 - Alignment of results with open innovation

  • Jhon Wilder Zartha Sossa,
  • Nolberto Gutiérrez Posada,
  • Luis Horacio Botero Montoya,
  • Adriana Maria Zuluaga Monsalve,
  • Juan Carlos Palacio Piedrahíta,
  • Gina Lia Orozco Mendoza,
  • Liliana Valencia Grisales,
  • Luis Fernando Gutiérrez Cano

Journal volume & issue
Vol. 10, no. 3
p. 100374

Abstract

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Objective: The objective of this article is to prioritize technologies, innovations, and new businesses related to the leather agroindustrial chain in the department of Quindío (Colombia) for the year 2035. Method: The prospective scenario and Delphi methods were used to prioritize key variables, technologies, actors, innovations, objectives, and scenarios in the leather agroindustry. As a previous phase, the Scopus database was used with the critical factors of leather, tanning, tanneries, tannery, leather transformation, cowhide, and suede, and the results were used as input for structured, anonymous and reiterative consultations with national and international experts on topics related to the chain and with a time horizon of 2035. The questionnaire was posed by groupings, including product and by-product innovation, sustainability, technology, and genetics, and, for the first round of the Delphi method, was sent to more than 70 national and industry experts/stakeholders, representatives of universities, the public and private sectors, and organizations related to the chain. Findings: After conducting a bibliometric analysis, key terms related to the leather sector were visualized and a validation was made for MICMAC methods, with 44 variables found; with topics ranging from raw materials to current regulations. For the MACTOR method, future objectives were determined for clean technologies, the creation of new product development, and an R&D&I Center for productive transformation. Meanwhile, for the Delphi method, 44 technologies and innovations were prioritized through rounds with complementary analysis using Python and natural language processing. Conclusions: Topics such as vegan leather made, from mushrooms; bio-leather or leather made, from mango peel; nanofibers, nanocomposites, biogas production, nanofiltration, 4D Printing, Artificial Intelligence to improve leather quality; augmented reality to improve customer experience; genetic improvement of animals to improve leather quality, among others, in which innovation challenges and open innovation strategies can be generated, as well as in R&D&I projects, were identified.

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