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.
Complete Chapter List
P. Collet, J. Rennard
I. Naveh, R. Sun
J. Barr, F. Saraceno
H. Kwasnicka, W. Kwasnicki
A. Berro, I. leroux
N. J. Saam, W. Kerber
A. Brabazon, A. Silva, T. F.S. Sousa, R. Matthews, M. O’Neill
G. D.M. Serugendo
K. Taveter, G. Wagner
L. Shan, R. Shen, J. Wang
M. Klein, P. Faratin, H. Sayama
A. Mochon, Y. Saez
R. Marks, D. Midgley, L. Cooper
T. Erez, S. Moldovan, Soloman
M. Ciprian, M. Kaucic
S. Lavigne, S. Sanchez