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

Carlos E. Laciana, Santiago L. Rovere, Guillermo P. Podestá

Research output: Contribution to journalArticle

15 Scopus citations

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 [1]). For a portion of the p-q domain, results from micro-simulations were consistent with aggregate-level adoption patterns reported in the literature. Induced Bass macro-level parameters p and q responded to changes in micro-parameters: (1) p increased with the number of innovators and with the rate at which innovators are introduced; (2) q 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 p and q 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.

Original languageEnglish (US)
Pages (from-to)1873-1884
Number of pages12
JournalPhysica A: Statistical Mechanics and its Applications
Volume392
Issue number8
DOIs
StatePublished - Apr 15 2013

Keywords

  • Agent-based models
  • Bass model
  • Innovation diffusion
  • Technology adoption

ASJC Scopus subject areas

  • Statistics and Probability
  • Condensed Matter Physics

Fingerprint Dive into the research topics of 'Exploring associations between micro-level models of innovation diffusion and emerging macro-level adoption patterns'. Together they form a unique fingerprint.

  • Cite this