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. Keywords Exploration-exploitation trade-off, Learning rates, Complexity theory, Learning, Organizations Paper type Research pape