Published in | Physica A: Statistical Mechanics and its Applications |
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Authors | Laciana, C., Rovere, S.L. and Podestá, G.P.   |
Publication year | 2013 |
DOI | https://doi.org/10.1016/j.physa.2012.12.023 |
Affiliations |
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IAI Program | CRN3 |
IAI Project | CRN3035 |
Keywords | |
A micro-level agent-based model of innovation diffusion was developed that explicitly combines (a) an individual&rsquos perception of the advantages or relative utility derived from adoption, and (b) social influence from members of the individual&rsquos 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  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&ndashor processes related to them&ndashto enhance adoption of future products or technologies.