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

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

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.

Suggested Citation

  • Laciana, Carlos E. & Rovere, Santiago L. & Podestá, Guillermo P., 2013. "Exploring associations between micro-level models of innovation diffusion and emerging macro-level adoption patterns," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(8), pages 1873-1884.
    • Handle: RePEc:eee:phsmap:v:392:y:2013:i:8:p:1873-1884
    DOI: 10.1016/j.physa.2012.12.023
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    7. Hang Xiong & Puqing Wang & Georgiy Bobashev, 2018. "Multiple peer effects in the diffusion of innovations on social networks: a simulation study," Journal of Innovation and Entrepreneurship, Springer, vol. 7(1), pages 1-18, December.

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