The impact of network characteristics on the diffusion of innovations

Authored by Renana Peres

Date Published: 2014-05-15

DOI: 10.1016/j.physa.2014.02.003

Sponsors: Israeli National Science Foundation Israeli Association for Internet Study

Platforms: No platforms listed

Model Documentation: Other Narrative Mathematical description

Model Code URLs: Model code not found

Abstract

This paper studies the influence of network topology on the speed and reach of new product diffusion. While previous research has focused on comparing network types, this paper explores explicitly the relationship between topology and measurements of diffusion effectiveness. We study simultaneously the effect of three network metrics: the average degree, the relative degree of social hubs (i.e., the ratio of the average degree of highly-connected individuals to the average degree of the entire population), and the clustering coefficient. A novel network-generation procedure based on random graphs with a planted partition is used to generate 160 networks with a wide range of values for these topological metrics. Using an agent-based model, we simulate diffusion on these networks and check the dependence of the net present value (NPV) of the number of adopters over time on the network metrics. We find that the average degree and the relative degree of social hubs have a positive influence on diffusion. This result emphasizes the importance of high network connectivity and strong hubs. The clustering coefficient has a negative impact on diffusion, a finding that contributes to the ongoing controversy on the benefits and disadvantages of transitivity. These results hold for both monopolistic and duopolistic markets, and were also tested on a sample of 12 real networks. (C) 2014 Elsevier B.V. All rights reserved.

Tags

Agent-based models Clustering Average degree Diffusion of innovations Social hubs Word of mouth