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A Natural Analogy to the Diffusion of Energy-Efficient Technologies

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  • José Antonio Moya

    (Joint Research Centre, Institute for Energy and Transport, P.O. Box 2, 1755 ZG Petten, The Netherlands)

Abstract

A new mathematical approach to the diffusion of energy-efficient technologies is presented using the diffusion of natural processes as an analogy. This approach is applied to the diffusion of the electric arc furnace in Japan. The main advantage offered by the new approach is the incorporation of an average effect of barriers to, and support measures for, innovation. This approach also incorporates some of the parameters influencing the cost-effectiveness of the investment in the new technology as the main driver for adopting the innovation. The straightforward equivalence between natural phenomena and the diffusion of innovation requires the conceptual abstraction of setting a dimension (and defining) the medium in which the diffusion takes place. This new approach opens new research paths to analysing under what circumstances innovations can take-off, the effect of barriers in the diffusion of energy efficient technologies, or how the diffusion process is incorporated in energy-system models.

Suggested Citation

  • José Antonio Moya, 2016. "A Natural Analogy to the Diffusion of Energy-Efficient Technologies," Energies, MDPI, vol. 9(6), pages 1-14, June.
  • Handle: RePEc:gam:jeners:v:9:y:2016:i:6:p:471-:d:72308
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    References listed on IDEAS

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    1. Romer, Paul M, 1986. "Increasing Returns and Long-run Growth," Journal of Political Economy, University of Chicago Press, vol. 94(5), pages 1002-1037, October.
    2. Crompton, Paul, 2001. "The diffusion of new steelmaking technology," Resources Policy, Elsevier, vol. 27(2), pages 87-95, June.
    3. Frank M. Bass, 1969. "A New Product Growth for Model Consumer Durables," Management Science, INFORMS, vol. 15(5), pages 215-227, January.
    4. Okazaki, Teruo & Yamaguchi, Mitsutsune, 2011. "Accelerating the transfer and diffusion of energy saving technologies steel sector experience--Lessons learned," Energy Policy, Elsevier, vol. 39(3), pages 1296-1304, March.
    5. Jordi Suriñach & Corinne Autant-Bernard & Fabio Manca & Nadine Massard & Rosina Moreno, 2009. "The diffusion/adoption of innovation in the internal market," European Economy - Economic Papers 2008 - 2015 384, Directorate General Economic and Financial Affairs (DG ECFIN), European Commission.
    6. Hall, Bronwyn H. & Khan, Beethika, 2003. "Adoption of New Technology," Department of Economics, Working Paper Series qt3wg4p528, Department of Economics, Institute for Business and Economic Research, UC Berkeley.
    7. Jayati Sarkar, 1998. "Technological Diffusion: Alternative Theories and Historical Evidence," Journal of Economic Surveys, Wiley Blackwell, vol. 12(2), pages 131-176, April.
    8. Meade, Nigel & Islam, Towhidul, 2006. "Modelling and forecasting the diffusion of innovation - A 25-year review," International Journal of Forecasting, Elsevier, vol. 22(3), pages 519-545.
    9. Moore, Michal C. & Arent, Douglas J. & Norland, Douglas, 2007. "R&D advancement, technology diffusion, and impact on evaluation of public R&D," Energy Policy, Elsevier, vol. 35(3), pages 1464-1473, March.
    10. Labson, B Stephen & Gooday, Peter, 1994. "Factors influencing the diffusion of electric arc furnace steelmaking technology," MPRA Paper 70666, University Library of Munich, Germany.
    11. Geroski, P. A., 2000. "Models of technology diffusion," Research Policy, Elsevier, vol. 29(4-5), pages 603-625, April.
    12. Hlavinka, Alexander N. & Mjelde, James W. & Dharmasena, Senarath & Holland, Christine, 2016. "Forecasting the adoption of residential ductless heat pumps," Energy Economics, Elsevier, vol. 54(C), pages 60-67.
    13. Reppelin-Hill, Valerie, 1999. "Trade and Environment: An Empirical Analysis of the Technology Effect in the Steel Industry," Journal of Environmental Economics and Management, Elsevier, vol. 38(3), pages 283-301, November.
    14. Jain, Dipak C & Rao, Ram C, 1990. "Effect of Price on the Demand for Durables: Modeling, Estimation, and Findings," Journal of Business & Economic Statistics, American Statistical Association, vol. 8(2), pages 163-170, April.
    15. Fleiter, Tobias & Worrell, Ernst & Eichhammer, Wolfgang, 2011. "Barriers to energy efficiency in industrial bottom-up energy demand models--A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 15(6), pages 3099-3111, August.
    16. Jaffe, Adam B. & Stavins, Robert N., 1994. "The energy-efficiency gap What does it mean?," Energy Policy, Elsevier, vol. 22(10), pages 804-810, October.
    17. repec:bla:jecsur:v:12:y:1998:i:2:p:131-76 is not listed on IDEAS
    18. Lucas, Robert Jr., 1988. "On the mechanics of economic development," Journal of Monetary Economics, Elsevier, vol. 22(1), pages 3-42, July.
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    Cited by:

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    2. Collins, Matthew & Curtis, John, 2017. "Advertising and investment spillovers in the diffusion of residential energy efficiency renovations," Papers WP569, Economic and Social Research Institute (ESRI).
    3. José Antonio Moya, 2017. "Where Diffusion of Clean Technologies and Barriers to Innovation Clash: Application to the Global Diffusion of the Electrical Arc Furnace," Energies, MDPI, vol. 10(1), pages 1-22, January.

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