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What is NK Model

Handbook of Research on Nature-Inspired Computing for Economics and Management
A binary particle model developed by Kauffman and Weinberger to understand how organisms evolve by undertaking adaptive walks similar to hill climbing to achieve maximize fitness.
Published in Chapter:
Competitive Advantage of Geographical Clusters
V. Albino (Politecnico di Bari, Italy)
DOI: 10.4018/978-1-59140-984-7.ch022
Abstract
This chapter deals with complexity science issues from two sides: from one side, it uses complexity science concepts to give new contributions to the theoretical understanding of geographical clusters (GCs); from the other side, it presents an application of complexity science tools such as emergent (bottom-up) simulation, using agent-based modeling to study the sources of GC competitive advantage. Referring to the first direction, complexity science is used as a conceptual framework to identify the key structural conditions of GCs that give them the adaptive capacity, so assuring their competitive advantage. Regarding the methodological approach, the agent-based simulation is used to analyze the dynamics of GCs. To this aim, we model the main characteristics of GCs and carry out a simulation analysis to observe that the behaviors of GCs are coherent with the propositions built up on the basis of complexity science literature.
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Toward a Fitness Landscape Model of Firms' IT-Enabled Dynamic Capabilities
Provides a comprehensive framework to evaluate the effects of relationships between ( N ) components of systems and their respective epistatic linkages or relationships ( K ).
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