Innovation diffusion in networks: the microeconomics of percolation
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References listed on IDEAS
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CitationsCitations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
- Katarzyna Maciejowska & Arkadiusz Jedrzejewski & Anna Kowalska-Pyzalska & Katarzyna Sznajd-Weron & Rafal Weron, 2015. "Two faces of word-of-mouth: Understanding the impact of social interactions on demand curves for innovative products," HSC Research Reports HSC/15/09, Hugo Steinhaus Center, Wroclaw University of Technology.
- Bogner, Kristina, 2015. "The effect of project funding on innovative performance: An agent-based simulation model," Hohenheim Discussion Papers in Business, Economics and Social Sciences 10-2015, University of Hohenheim, Faculty of Business, Economics and Social Sciences.
- Paolo Zeppini & Koen Frenken & Roland Kupers, 2013. "Threshold models of technological transitions," Working Papers 13-06, Eindhoven Center for Innovation Studies, revised Aug 2013.
- Solomon Sorin & Golo Natasa, 2013.
"Minsky Financial Instability, Interscale Feedback, Percolation and Marshall–Walras Disequilibrium,"
Accounting, Economics, and Law: A Convivium,
De Gruyter, vol. 3(3), pages 167-260, October.
- Sorin Solomon & Natasa Golo, 2014. "Minsky Financial Instability, Interscale Feedback, Percolation and Marshall-Walras Disequilibrium," Papers 1402.0176, arXiv.org.
More about this item
Keywordscritical transition; demand; learning curves; market efficiency; social networks;
- C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
- D42 - Microeconomics - - Market Structure, Pricing, and Design - - - Monopoly
- O33 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Technological Change: Choices and Consequences; Diffusion Processes
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