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Balancing exploration and exploitation in complex environments

Balancing exploration and exploitation in complex environments Purpose – The objective of this study is to model and analyze the exploration‐exploitation dynamics of March's model of mutual learning in a complex environment. By enhancing the above mentioned model, the paper seeks to propose a new agent‐based model of mutual learning within an organization. Design/methodology/approach – The paper replicates March's model of simulating learning within an organization using an agent‐based simulation approach, and extends it by modelling the problem space as a fitness landscape using Kauffman's NK model technique. Findings – It was found that it is impossible to find a right balance between exploration and exploitation using the communication structure of March's model. Practical implications – The proposed model could help create a virtual laboratory for experimenting organizations' behavior in a complex co‐evolving environment. This virtual laboratory may be used in the future to support the decision‐making process of managers and policy makers. Originality/value – Designing the external environment as a fitness landscape helps in discovering what effect the environmental complexity has on the emerging balance between exploration and exploitation. It is the first study to design the environment of a model which analyzes the mutual learning between an organization and its members as a complex non‐linear space. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png VINE Emerald Publishing

Balancing exploration and exploitation in complex environments

VINE , Volume 42 (1): 21 – Feb 10, 2012

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References (96)

Publisher
Emerald Publishing
Copyright
Copyright © 2012 Emerald Group Publishing Limited. All rights reserved.
ISSN
0305-5728
DOI
10.1108/03055721211207743
Publisher site
See Article on Publisher Site

Abstract

Purpose – The objective of this study is to model and analyze the exploration‐exploitation dynamics of March's model of mutual learning in a complex environment. By enhancing the above mentioned model, the paper seeks to propose a new agent‐based model of mutual learning within an organization. Design/methodology/approach – The paper replicates March's model of simulating learning within an organization using an agent‐based simulation approach, and extends it by modelling the problem space as a fitness landscape using Kauffman's NK model technique. Findings – It was found that it is impossible to find a right balance between exploration and exploitation using the communication structure of March's model. Practical implications – The proposed model could help create a virtual laboratory for experimenting organizations' behavior in a complex co‐evolving environment. This virtual laboratory may be used in the future to support the decision‐making process of managers and policy makers. Originality/value – Designing the external environment as a fitness landscape helps in discovering what effect the environmental complexity has on the emerging balance between exploration and exploitation. It is the first study to design the environment of a model which analyzes the mutual learning between an organization and its members as a complex non‐linear space.

Journal

VINEEmerald Publishing

Published: Feb 10, 2012

Keywords: Exploration‐exploitation trade‐off; Learning rates; Complexity theory; Learning; Organizations

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