Large Deviations Theory of Increasing Returns

TL;DR

This paper analyzes a generalized increasing returns model using large deviations theory, revealing the most probable market share trajectories and entropy behaviors, with implications for understanding lock-in phenomena.

Contribution

It introduces a large deviation framework for a generalized increasing returns model, connecting it to urn models and deriving equations for market share dynamics.

Findings

Most likely market share trajectories identified

Region of sub-linear entropy cost in lock-in phase

Non-linear differential equation for cumulant generating function

Abstract

An influential theory of increasing returns has been proposed by the economist W. B. Arthur in the '80s to explain the lock-in phenomenon between two competing commercial products. In the most simplified situation there are two competing products that gain customers according to a majority mechanism: each new customer arrives and asks which product they bought to a certain odd number of previous customers, and then buy the most shared product within this sample. It is known that one of these two companies reaches monopoly almost surely in the limit of infinite customers. Here we consider a generalization [G. Dosi, Y. Ermoliev, Y. Kaniovsky, J. Math. Econom. 23, 1-19 (1994)] where the new customer follows the indication of the sample with some probability, and buy the other product otherwise. Other than economy, this model can be reduced to the urn of Hill, Lane and Sudderth, and includes several models of physical interest as special cases, like the Elephant Random Walk, the Friedman's urn and other generalized urn models. We provide a large deviation analysis of this model at the sample-path level, and give a formula that allows to find the most likely trajectories followed by the market share variable. Interestingly, in the parameter range where the lock-in phase is expected, we observe a whole region of convergence where the entropy cost is sub-linear. We also find a non-linear differential equation for the cumulant generating function of the market share variable, that can be studied with a suitable perturbations theory.