Boolean Network Simulation for Exploring the Dynamics of Industrial Network

Kristina Boyanova Georgieva, 2001

This thesis applies a computer simulation methodology for the study of industrial network dynamics based on the Boolean network model developed by Stuart Kauffman for the study of complex non-linear dynamical systems. 'Industrial networks' is a term used to describe organisational markets where there are strong links and interdependencies between customers and suppliers, and exchanges take place in the context of long-term relationships. Boolean networks are binary parallel-processing systems comprising many interacting elements. The behaviour of each element changes over time depending on the behaviour of other elements according to a Boolean logic rule.

The unit of simulation is redefined as the exchange between two economic agents. Boolean functions specify the local conditions for exchanges that in turn reflect specific relations and dependencies between actors, resources and activities. Small networks ranging from 3 to 9 exchanges are simulated modelling specific industrial network situations. The simulation experiments trace the emergence of the overall exchange patterns for the network in a bottom-up manner as exchange processes organised and enacted locally unfold over time. A number of alternative long-term recurrent patterns – attractors – are possible for the network depending on the initial conditions. The exchange patterns defined by attractors are explained through the industrial micro-logic reflected in the Boolean functions. Attractor stability and the network response to change are explored for random perturbations and for changes in the local exchange conditions.

The research offers a novel way of explaining the patterns of stability and change observed in real life industrial networks through the ability of networks to evolve endogenously a limited set of global dynamical structures, attractors. They emerge out of local processes of interaction between network elements and stabilise the system by defining the boundaries for the dynamics at the local level.