Ising-like agent-based technology diffusion model: Adoption patterns vs. seeding strategies
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References listed on IDEAS
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- Lin, Ying-Ting & Han, Xiao-Pu & Wang, Bing-Hong, 2014. "Dynamics of human innovative behaviors," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 394(C), pages 74-81.
- Markus Brede, 2019. "How Does Active Participation Affect Consensus: Adaptive Network Model of Opinion Dynamics and Influence Maximizing Rewiring," Complexity, Hindawi, vol. 2019, pages 1-16, June.
- 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.
- Laciana, Carlos E. & Oteiza-Aguirre, Nicolás, 2014. "An agent based multi-optional model for the diffusion of innovations," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 394(C), pages 254-265.
- Bodo, Peter, 2016. "MADness in the method: On the volatility and irregularity of technology diffusion," Technological Forecasting and Social Change, Elsevier, vol. 111(C), pages 2-11.
- Robinson, Scott A. & Rai, Varun, 2015. "Determinants of spatio-temporal patterns of energy technology adoption: An agent-based modeling approach," Applied Energy, Elsevier, vol. 151(C), pages 273-284.
- Laciana, C.E. & Gual, G. & Kalmus, D. & Oteiza-Aguirre, N. & Rovere, S.L., 2014. "Diffusion of two brands in competition: Cross-brand effect," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 413(C), pages 104-115.
- Peres, Renana, 2014. "The impact of network characteristics on the diffusion of innovations," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 402(C), pages 330-343.
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KeywordsCollective decision; Technology adoption; Ising model; Early adopters; Networks;
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