Exploring associations between micro-level models of innovation diffusion and emerging macro-level adoption patterns

TL;DR

This paper develops a micro-level agent-based model of innovation diffusion that links individual perceptions and social influence to macro-level adoption patterns, matching traditional models and providing insights for marketing strategies.

Contribution

It introduces a micro-level simulation framework that reproduces macro-level diffusion patterns and explores how micro-parameters influence aggregate adoption.

Findings

Micro-simulation closely matches Bass macro-level model predictions.

Adoption increases with number of innovators and their introduction rate.

Social network structure and perceived utility significantly affect diffusion patterns.

Abstract

A micro-level agent-based model of innovation diffusion was developed that explicitly combines (a) an individual's perception of the advantages or relative utility derived from adoption, and (b) social influence from members of the individual's social network. The micro-model was used to simulate macro-level diffusion patterns emerging from different configurations of micro-model parameters. Micro-level simulation results matched very closely the adoption patterns predicted by the widely-used Bass macro-level model (Bass, 1969). For a portion of the domain, results from micro-simulations were consistent with aggregate-level adoption patterns reported in the literature. Induced Bass macro-level parameters and responded to changes in micro-parameters: (1) increased with the number of innovators and with the rate at which innovators are introduced; (2) increased with the probability of rewiring in small-world networks, as the characteristic path length decreases; and (3) an increase in the overall perceived utility of an innovation caused a corresponding increase in induced and values. Understanding micro to macro linkages can inform the design and assessment of marketing interventions on micro-variables - or processes related to them - to enhance adoption of future products or technologies.