Learning in the Regional Innovation Systems: An Agent Based Model

  • Santiago Quintero Ramirez Universidad Pontificia Bolivariana - Sede Medellín.
  • Walter Lugo Ruiz Castañeda Universidad Pontificia Bolivariana - Sede Medellín.
  • Jorge Robledo Velásquez Universidad Nacional de Colombia - Sede Medellín.

Abstract

Learning in regional innovation systems is a complex phenomenon. Therefore, its analysis is being increasingly approached through computer-simulated strategies. The agent-based model in particular has demonstrated to be a useful approximation to overcome the limitations of other methodological strategies since it allows a more trustworthy representation of the agent’s capabilities, their reasoning limitations, of the mechanisms used for decision making, their interaction, and their success formulas to take advantage of market opportunities. Nevertheless, the development of these models represents serious conceptual and methodological challenges. This article proposes a model that represents the agents of a regional innovation system as vectors of capabilities and the learning process as the accumulation of their innovation capabilities. The proximity among agents and the influence of public policies favors the result of the interaction induced by the market. Methodologically, the development of the model starts with a conceptual proposal validated through contrast against. specialized literature. After that, a model verified by computer was elaborated and its behavior was validated. Finally, a simulation of scenarios was performed to prove its potential application. The resulting model contributes to the understanding the learning dynamics and the emerging patterns of the agent’s specialization and their influence on the system’s performance. Finally, the simulation exercises demonstrate the model’s potential to guide policy decisions that seek to improve the performance regional innovation systems.

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Author Biographies

Santiago Quintero Ramirez, Universidad Pontificia Bolivariana - Sede Medellín.

Profesor Asociado, Facultad de Ingenierías, Ing. Industrial, Universidad Pontificia Bolivariana - Sede Medellín, Colombia. Ingeniero de Alimentos, Corporación Universitaria Lasallista Caldas - Antioquia; Magister en Gestión Tecnológica, Universidad Pontificia Bolivariana, Medellín, Colombia. Grupo de Investigación en Gestión de la Tecnología y la Innovación, Categoría A - Universidad Pontificia Bolivariana - Sede Medellín, Colombia

Walter Lugo Ruiz Castañeda, Universidad Pontificia Bolivariana - Sede Medellín.
Profesor Asociado, Escuela de Economía, Administración y Negocios - Centro de Desarrollo Empresarial - Universidad Pontificia Bolivariana - Sede Medellín, Colombia. Ingeniero Industrial - Universidad Nacional de Colombia Sede Medellín; Magíster en Administración - Universidad EAFIT, Medellín, Colombia. Grupo de Investigación Estudios Empresariales - GEE, Categoría C - Universidad Pontificia Bolivariana - Medellín, Colombia y Grupo de Investigación en Innovación y Gestión Tecnológica, Categoría A - Universidad Nacional de Colombia - Sede Medellín
Jorge Robledo Velásquez, Universidad Nacional de Colombia - Sede Medellín.
Profesor Titular, Facultad de Minas, Dpto. de Ing. de la Organización, Universidad Nacional de Colombia - Sede Medellín, Colombia. Ingeniero Mecánico, Universidad Nacional de Colombia - Sede Medellín; Magíster en Sistemas de Generación de Energía Eléctrica, Universidad del Valle, Cali, Colombia; Ph.D. en Política y Gestión de Ciencia y Tecnología, Universidad de Sussex, Brighton, Inglaterra. Grupo de Investigación en Innovación y Gestión Tecnológica, Categoría A - Universidad Nacional de Colombia - Sede Medellín
 
Published
2017-10-05
How to Cite
QUINTERO RAMIREZ, Santiago; RUIZ CASTAÑEDA, Walter Lugo; ROBLEDO VELÁSQUEZ, Jorge. Learning in the Regional Innovation Systems: An Agent Based Model. Cuadernos de Administración, [S.l.], v. 33, n. 57, oct. 2017. ISSN 2256-5078. Available at: <http://revistas.univalle.edu.co/index.php/cuadernos_de_administracion/article/view/4535>. Date accessed: 18 dec. 2017. doi: https://doi.org/10.25100/cdea.v33i57.4535.
Section
Research

Keywords

Aprendizaje; interacciones; capacidades; modelos basado en agentes; sistemas regionales de innovación