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A percolation model of eco-innovation diffusion: the relationship between diffusion, learning economies and subsidies

  • Simona Cantono


    (Department of Economics, University of Turin)

  • Gerald Silverberg



An obstacle to the widespread adoption of environmentally friendly energy technologies such as stationary and mobile fuel cells is their high upfront costs. While much lower prices seem to be attainable in the future due to learning curve cost reductions that increase rapidly with the scale of diffusion of the technology, there is a chicken and egg problem, even when some consumers may be willing to pay more for green technologies. Drawing on recent percolation models of diffusion by Solomon et al. [7], Frenken et al. [8] and Höhnisch et al. [9], we develop a network model of new technology diffusion that combines contagion among consumers with heterogeneity of agent characteristics. Agents adopt when the price falls below their random reservation price drawn from a lognormal distribution, but only when one of their neighbors has already adopted. Combining with a learning curve for the price as a function of the cumulative number of adopters, this may lead to delayed adoption for a certain range of initial conditions. Using agent-based simulations we explore when a limited subsidy policy can trigger diffusion that would otherwise not happen. The introduction of a subsidy policy seems to be highly effective for a given high initial price level only for learning economies in a certain range. Outside this range, the diffusion of a new technology either never takes off despite the subsidies, or the subsidies are unnecessary. Perhaps not coincidentally, this range seems to correspond to the values observed for many successful innovations.

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Paper provided by United Nations University - Maastricht Economic and Social Research Institute on Innovation and Technology (MERIT) in its series MERIT Working Papers with number 025.

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Date of creation: 2008
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Handle: RePEc:unm:unumer:2008025
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  1. Cowan Robin, 2004. "Network models of innovation and knowledge diffusion," Research Memorandum 016, Maastricht University, Maastricht Economic Research Institute on Innovation and Technology (MERIT).
  2. Cristiano Antonelli, 1996. "Localized knowledge percolation processes and information networks," Journal of Evolutionary Economics, Springer, vol. 6(3), pages 281-295.
  3. Silverberg, Gerald & Dosi, Giovanni & Orsenigo, Luigi, 1988. "Innovation, Diversity and Diffusion: A Self-organisation Model," Economic Journal, Royal Economic Society, vol. 98(393), pages 1032-54, December.
  4. Geroski, P. A., 2000. "Models of technology diffusion," Research Policy, Elsevier, vol. 29(4-5), pages 603-625, April.
  5. Solomon, Sorin & Weisbuch, Gerard & de Arcangelis, Lucilla & Jan, Naeem & Stauffer, Dietrich, 2000. "Social percolation models," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 277(1), pages 239-247.
  6. Martin Hohnisch & Sabine Pittnauer & Dietrich Stauffer, 2006. "A Percolation-Based Model Explaining Delayed Take-Off in New-Product Diffusion," Bonn Econ Discussion Papers bgse9_2006, University of Bonn, Germany.
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