Representation of unlearning in the innovation systems: A proposal from agent-based modeling

Santiago Quintero Ramírez; Walter Lugo Ruiz Castañeda; Jorge Robledo Velásquez

doi:10.1016/j.estger.2017.11.003

Representation of unlearning in the innovation systems: A proposal from agent-based modeling

Título traducido de la contribución: Representación del des-aprendizaje en los sistemas de innovación: Una propuesta desde la modelación basada en agentes

Santiago Quintero Ramírez, Walter Lugo Ruiz Castañeda, Jorge Robledo Velásquez

Producción científica: Contribución a una revista › Artículo en revista científica indexada › revisión exhaustiva

4 Citas (Scopus)

Resumen

In the present work it is understood the unlearning as the voluntary effort made by firms to abandon the capacities that are not necessary to compete in an innovation system. Modeling and simulating unlearning makes it possible to know emerging behaviors resulting not only from learning, but also from agents unlearning who try to adapt to other agents and the competitive environment. The objective of this work is to represent and analyze the unlearning from the agent-based methodology. As conclusion, a model representing unlearning as a negative variation in capacities accumulation was obtained, which according to its speed, has a different impact on the performance of the innovation system.

Título traducido de la contribución	Representación del des-aprendizaje en los sistemas de innovación: Una propuesta desde la modelación basada en agentes
Idioma original	Inglés
Páginas (desde-hasta)	366-376
Número de páginas	11
Publicación	Estudios Gerenciales
Volumen	33
N.º	145
DOI	https://doi.org/10.1016/j.estger.2017.11.003
Estado	Publicada - 2017

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Publisher Copyright:
© 2017 Universidad ICESI. Published by Elsevier España, S.L.U. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).

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title = "Representation of unlearning in the innovation systems: A proposal from agent-based modeling",

abstract = "In the present work it is understood the unlearning as the voluntary effort made by firms to abandon the capacities that are not necessary to compete in an innovation system. Modeling and simulating unlearning makes it possible to know emerging behaviors resulting not only from learning, but also from agents unlearning who try to adapt to other agents and the competitive environment. The objective of this work is to represent and analyze the unlearning from the agent-based methodology. As conclusion, a model representing unlearning as a negative variation in capacities accumulation was obtained, which according to its speed, has a different impact on the performance of the innovation system.",

keywords = "Agent-based model, Capabilities, Learning, Performance, Unlearning",

author = "Ram{\'i}rez, {Santiago Quintero} and Casta{\~n}eda, {Walter Lugo Ruiz} and Vel{\'a}squez, {Jorge Robledo}",

note = "Publisher Copyright: {\textcopyright} 2017 Universidad ICESI. Published by Elsevier Espa{\~n}a, S.L.U. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).",

year = "2017",

doi = "10.1016/j.estger.2017.11.003",

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T2 - A proposal from agent-based modeling

AU - Ramírez, Santiago Quintero

AU - Castañeda, Walter Lugo Ruiz

AU - Velásquez, Jorge Robledo

PY - 2017

Y1 - 2017

N2 - In the present work it is understood the unlearning as the voluntary effort made by firms to abandon the capacities that are not necessary to compete in an innovation system. Modeling and simulating unlearning makes it possible to know emerging behaviors resulting not only from learning, but also from agents unlearning who try to adapt to other agents and the competitive environment. The objective of this work is to represent and analyze the unlearning from the agent-based methodology. As conclusion, a model representing unlearning as a negative variation in capacities accumulation was obtained, which according to its speed, has a different impact on the performance of the innovation system.

AB - In the present work it is understood the unlearning as the voluntary effort made by firms to abandon the capacities that are not necessary to compete in an innovation system. Modeling and simulating unlearning makes it possible to know emerging behaviors resulting not only from learning, but also from agents unlearning who try to adapt to other agents and the competitive environment. The objective of this work is to represent and analyze the unlearning from the agent-based methodology. As conclusion, a model representing unlearning as a negative variation in capacities accumulation was obtained, which according to its speed, has a different impact on the performance of the innovation system.

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KW - Capabilities

KW - Learning

KW - Performance

KW - Unlearning

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SN - 0123-5923

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EP - 376

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ER -

Representation of unlearning in the innovation systems: A proposal from agent-based modeling

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