Diversification versus specialization -- lessons from a noise driven linear dynamical system

TL;DR

This paper analyzes how systems should choose between diversification and specialization strategies under resource constraints, using a noise-driven linear dynamical system to determine optimal approaches based on resource levels.

Contribution

It introduces an analytical model of a high-dimensional noisy dynamical system to compare the effectiveness of diversification versus specialization strategies.

Findings

Diversification benefits increase with moderate resource levels.

Specialization may outperform diversification when resources are very limited or abundant.

The model provides insights applicable to economic and biological systems.

Abstract

Specialization and diversification are two major strategies that complex systems might exploit. Given a fixed amount of resources, the question is whether to invest this in elements that respond in a correlated manner to external perturbations, or to build a diversified system with groups of elements that respond in a not necessarily correlated manner. This general dilemma is investigated here using a high dimensional discrete dynamical system subject to an external noise, analyzing the statistical properties of an order parameter that quantifies growth. Our analytical solution suggests that diversification is a good strategy once the system has a fair amount of resources. For systems with small or extremely large supplies, we argue that specialization might be a more successful strategy. We discuss the results also from the perspective of economic and biologic systems.