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

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  • Simona Cantono

    (Department of Economics, University of Turin)

  • Gerald Silverberg

    (UNU-MERIT)

Abstract

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.

Suggested Citation

  • Simona Cantono & Gerald Silverberg, 2008. "A percolation model of eco-innovation diffusion: the relationship between diffusion, learning economies and subsidies," MERIT Working Papers 2008-025, United Nations University - Maastricht Economic and Social Research Institute on Innovation and Technology (MERIT).
  • Handle: RePEc:unm:unumer:2008025
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    File URL: https://www.merit.unu.edu/publications/wppdf/2008/wp2008-025.pdf
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    References listed on IDEAS

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    1. 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.
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    4. Gerald Silverberg & Giovanni Dosi & Luigi Orsenigo, 2000. "Innovation, Diversity and Diffusion: A Self-Organisation Model," Chapters, in: Innovation, Organization and Economic Dynamics, chapter 14, pages 410-432, Edward Elgar Publishing.
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    6. Cowan, Robin, 2004. "Network models of innovation and knowledge diffusion," Research Memorandum 016, Maastricht University, Maastricht Economic Research Institute on Innovation and Technology (MERIT).
    7. Hohnisch, Martin & Pittnauer, Sabine & Stauffer, Dietrich, 2006. "A Percolation-Based Model Explaining Delayed Take-Off in New-Product Diffusion," Bonn Econ Discussion Papers 9/2006, University of Bonn, Bonn Graduate School of Economics (BGSE).
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    Cited by:

    1. Cantono, Simona, 2012. "Unveiling diffusion dynamics: an autocatalytic percolation model of environmental innovation diffusion and the optimal dynamic path of adoption subsidies," Department of Economics and Statistics Cognetti de Martiis LEI & BRICK - Laboratory of Economics of Innovation "Franco Momigliano", Bureau of Research in Innovation, Complexity and Knowledge, Collegio 201222, University of Turin.
    2. Floris J. Huétink & Alexander van der Vooren & Floortje Alkemade, 2009. "Initial infrastructure development strategies for the transition to sustainable mobility," Innovation Studies Utrecht (ISU) working paper series 09-05, Utrecht University, Department of Innovation Studies, revised Mar 2009.
    3. Frenken, Koen & Silverberg, Gerald & Valente, Marco, 2008. "A percolation model of the product lifecycle," MERIT Working Papers 2008-073, United Nations University - Maastricht Economic and Social Research Institute on Innovation and Technology (MERIT).
    4. Giulio Cainelli & Massimiliano Mazzanti & Sandro Montresor, 2012. "Environmental Innovations, Local Networks and Internationalization," Industry and Innovation, Taylor & Francis Journals, vol. 19(8), pages 697-734, November.
    5. Kindler, A. & Solomon, S. & Stauffer, D., 2013. "Peer-to-peer and mass communication effect on opinion shifts," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(4), pages 785-796.
    6. Alessandro Caiani, 2012. "An Agent-Based Model of Schumpeterian Competition," Quaderni di Dipartimento 176, University of Pavia, Department of Economics and Quantitative Methods.
    7. Albert Faber & Koen Frenken, 2008. "Models in evolutionary economics and environmental policy: Towards an evolutionary environmental economics," Innovation Studies Utrecht (ISU) working paper series 08-15, Utrecht University, Department of Innovation Studies, revised Apr 2008.
    8. Vona, Francesco & Patriarca, Fabrizio, 2011. "Income inequality and the development of environmental technologies," Ecological Economics, Elsevier, vol. 70(11), pages 2201-2213, September.
    9. Alessandro Caiani, 2017. "Innovation Dynamics and Industry Structure Under Different Technological Spaces," Italian Economic Journal: A Continuation of Rivista Italiana degli Economisti and Giornale degli Economisti, Springer;Società Italiana degli Economisti (Italian Economic Association), vol. 3(3), pages 307-341, November.
    10. Martin Zsifkovits & Markus Günther, 2015. "Simulating resistances in innovation diffusion over multiple generations: an agent-based approach for fuel-cell vehicles," 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. 23(2), pages 501-522, June.
    11. Rui Leite & Aurora Teixeira, 2012. "Innovation diffusion with heterogeneous networked agents: a computational model," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 7(2), pages 125-144, October.
    12. Dimitri Gagliardi & Francesco Niglia & Cinzia Battistella, 2012. "Use of multi-level self-regulating agents to evaluate the impact of innovation policy for the agro-food sector in the Region of Puglia, Italy," Openloc Working Papers 1205, Public policies and local development.
    13. Cantono Simona, 2012. "A percolation model of multi-technology diffusion: information feedbacks, learning economies and subsidy policy," Department of Economics and Statistics Cognetti de Martiis. Working Papers 201205, University of Turin.
    14. Dilaver, Özge, 2014. "Involuntary technology adoptions: How consumer interdependencies lead to societal change," Structural Change and Economic Dynamics, Elsevier, vol. 31(C), pages 138-148.
    15. Manman Wang & Shuai Lian & Shi Yin & Hengmin Dong, 2020. "A Three-Player Game Model for Promoting the Diffusion of Green Technology in Manufacturing Enterprises from the Perspective of Supply and Demand," Mathematics, MDPI, vol. 8(9), pages 1-26, September.

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    More about this item

    Keywords

    Innovation diffusion; learning economies; percolation; networks; heterogeneous agents; technology subsidies; environmental technologies;
    All these keywords.

    JEL classification:

    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • H23 - Public Economics - - Taxation, Subsidies, and Revenue - - - Externalities; Redistributive Effects; Environmental Taxes and Subsidies
    • O32 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Management of Technological Innovation and R&D
    • 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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