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.
Key Terms in this Chapter
Computational Model: A simplification of a real system that can be analytically understood and/or run as a computer simulation.
NK Model: 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.
Agent-Based Simulation: A collection of autonomous, heterogeneous, intelligent, and interacting software agents, which operate and exist in an environment. These software agents interact with each other in a non-linear manner with little or no central direction. The large-scale effects determined by the locally interacting agents are called emergent properties of the system. The main goal of agent-based simulation is to enrich the understanding of fundamental processes regulating and determining dynamics of complex adaptive systems.
Geographical Cluster: A geographically defined production system, characterized by a large number of small and medium-sized firms involved at various phases in the production of a homogeneous product family. These firms are highly specialized in a few phases of the production process and integrated through a complex network of inter-organizational relationships.
Emergence: The behavior that surfaces out of interaction of a group of agents/people whose behavior cannot be predicted on the basis of individual and isolated actions and is not externally imposed.
Complex Adaptive System: A collection of agents, interconnections, and flows where aggregate system behavior is determined from the complex, local interactions of agents.
Agent: An object with various attributes that interprets and interacts with its environment through behavioral rules.