A Generative Network Model for Product Evolution

Abstract

Modeling the structure and evolution of products is important from the standpoint of improving quality and maintainability. With the increasing popularity of opensource processes for developing both software and physical systems, there is a need to develop computational models of product evolution in such dynamic product developments scenarios. Existing studies on the evolution of products involve modeling products as networks, taking snapshots of the structure at different time steps, and comparing the structural characteristics. Such approaches are limited because they do not capture the underlying dynamics through which products evolve. In this paper, we take a step toward addressing this gap by presenting a generative network model for product evolution. The generative model is based on different mechanisms though which networks evolve—addition and removal of nodes, addition and removal of links. The model links local network observations to global network structures. It is utilized for modeling and analyzing the evolution of a software product (Drupal) and a physical product (RepRap) developed by open source processes. For the software product, the generated networks are compared with the actual product structures using various network measures including average degree, density, clustering coefficients, average shortest path, propagation cost, clustered cost, and degree distributions. For the physical product, the product evolution is analyzed in terms of the proposed mechanisms. The proposed model has three general applications: longitudinal studies of a product's evolution, crosssectional studies of evolution of different products, and predictive analyzes.