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Diffusion dynamics in small-world networks with heterogeneous consumers

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Cited by:

  1. Halleck-Vega, Solmaria & Mandel, Antoine & Millock, Katrin, 2018. "Accelerating diffusion of climate-friendly technologies: A network perspective," Ecological Economics, Elsevier, vol. 152(C), pages 235-245.
  2. Côme Billard, 2020. "Technology Contagion in Networks," Working Papers 2020.01, FAERE - French Association of Environmental and Resource Economists.
  3. Fan Yang & Wen Dong, 2020. "Integrating simulation and signal processing in tracking complex social systems," Computational and Mathematical Organization Theory, Springer, vol. 26(1), pages 1-22, March.
  4. Ning Nan & Robert Zmud & Emre Yetgin, 2014. "A complex adaptive systems perspective of innovation diffusion: an integrated theory and validated virtual laboratory," Computational and Mathematical Organization Theory, Springer, vol. 20(1), pages 52-88, March.
  5. Meihan He & Jongsu Lee, 2020. "Social culture and innovation diffusion: a theoretically founded agent-based model," Journal of Evolutionary Economics, Springer, vol. 30(4), pages 1109-1149, September.
  6. Hossein Sabzian & Mohammad Ali Shafia & Mehdi Ghazanfari & Ali Bonyadi Naeini, 2020. "Modeling the Adoption and Diffusion of Mobile Telecommunications Technologies in Iran: A Computational Approach Based on Agent-Based Modeling and Social Network Theory," Sustainability, MDPI, vol. 12(7), pages 1-36, April.
  7. Paolo Zeppini & Koen Frenken, 2015. "Networks, Percolation, and Demand," Department of Economics Working Papers 38/15, University of Bath, Department of Economics.
  8. Elmar Kiesling & Markus Günther & Christian Stummer & Lea Wakolbinger, 2012. "Agent-based simulation of innovation diffusion: a review," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 20(2), pages 183-230, June.
  9. Torsten Heinrich, 2018. "Network Externalities and Compatibility Among Standards: A Replicator Dynamics and Simulation Analysis," Computational Economics, Springer;Society for Computational Economics, vol. 52(3), pages 809-837, October.
  10. Hu, Sen & Hu, Bin & Cao, Ya, 2018. "The wider, the better? The interaction between the IoT diffusion and online retailers’ decisions," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 509(C), pages 196-209.
  11. Mike Danilovic & Marleen Hensbergen & Maya Hoveskog & Liudmila Zadayannaya, 2015. "Exploring Diffusion and Dynamics of Corporate Social Responsibility," Corporate Social Responsibility and Environmental Management, John Wiley & Sons, vol. 22(3), pages 129-141, May.
  12. Tatsuhiro Shichijo & Emiko Fukuda, 2019. "A dynamic game analysis of Internet services with network externalities," Theory and Decision, Springer, vol. 86(3), pages 361-388, May.
  13. Muller, Eitan & Peres, Renana, 2019. "The effect of social networks structure on innovation performance: A review and directions for research," International Journal of Research in Marketing, Elsevier, vol. 36(1), pages 3-19.
  14. Held, Fabian P. & Wilkinson, Ian F. & Marks, Robert E. & Young, Louise, 2014. "Agent-based Modelling, a new kind of research," Australasian marketing journal, Elsevier, vol. 22(1), pages 4-14.
  15. Giovanni Pegoretti & Francesco Rentocchini & Giuseppe Vittucci Marzetti, 2012. "An agent-based model of innovation diffusion: network structure and coexistence under different information regimes," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 7(2), pages 145-165, October.
  16. Karolina Safarzyńska & Jeroen Bergh, 2010. "Evolutionary models in economics: a survey of methods and building blocks," Journal of Evolutionary Economics, Springer, vol. 20(3), pages 329-373, June.
  17. Ray M. Chang & Wonseok Oh & Alain Pinsonneault & Dowan Kwon, 2010. "A Network Perspective of Digital Competition in Online Advertising Industries: A Simulation-Based Approach," Information Systems Research, INFORMS, vol. 21(3), pages 571-593, September.
  18. Song-min Yu & Lei Zhu, 2017. "Impact of Firms’ Observation Network on the Carbon Market," Energies, MDPI, vol. 10(8), pages 1-14, August.
  19. Heinrich, Torsten, 2015. "A Replicator Dynamic and Simulation Analysis of Network Externalities and Compatibility Among Standards," MPRA Paper 67198, University Library of Munich, Germany.
  20. Heinrich, Torsten, 2016. "The Narrow and the Broad Approach to Evolutionary Modeling in Economics," MPRA Paper 75797, University Library of Munich, Germany.
  21. Houxing Tang & Zhenzhong Ma & Jiuling Xiao & Lei Xiao, 2020. "Toward a more Efficient Knowledge Network in Innovation Ecosystems: A Simulated Study on Knowledge Management," Sustainability, MDPI, vol. 12(16), pages 1-18, August.
  22. Hong, Jungsik & Koo, Hoonyoung & Kim, Taegu, 2016. "Easy, reliable method for mid-term demand forecasting based on the Bass model: A hybrid approach of NLS and OLS," European Journal of Operational Research, Elsevier, vol. 248(2), pages 681-690.
  23. Jesús Rosales-Carreón & César García-Díaz, 2015. "Exploring Transitions Towards Sustainable Construction: The Case of Near-Zero Energy Buildings in the Netherlands," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 18(1), pages 1-10.
  24. Desmarchelier, Benoît & Fang, Eddy S., 2016. "National culture and innovation diffusion. Exploratory insights from agent-based modeling," Technological Forecasting and Social Change, Elsevier, vol. 105(C), pages 121-128.
  25. Viktor Vojtko, 2014. "Rethinking the Concept of Just Noticeable Difference in Online Marketing," Acta Informatica Pragensia, Prague University of Economics and Business, vol. 2014(2), pages 204-218.
  26. 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.
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