A review of technology diffusion models with special reference to renewable energy technologies

Diffusion of renewable energy technologies (RETs) are driven by policies and incentives due to their inherent characteristics such as high upfront costs, lack of level playing field but distinct advantages from energy security, environmental and social considerations. Even after three decades of their promotion, only 20-25% of their potential has been realized. The theory of diffusion modeling allows analysis of diffusion processes and study of growth rates of different technologies and underlying diffusion factors. Their applications have focused on commercial and consumer products such as television, automobiles and IT products and their applications to RETs have been limited. Diffusion analysis of RETs have been based on barriers' to RET adoption and techno-economic, learning and experience curve approaches. It is observed that these diffusion models when applied to commercial products do not deal with the issues of policy influences which are critical to RET diffusion. Since policies drive RET diffusion, the models for analyzing RET diffusion should allow establishing explicit relationships between the diffusion parameters and policies and their impact on diffusion rates. Given the potential of renewable energy technologies for sustainable development, the aim of this paper is to review different diffusion theory based models and their applicability to RET diffusion analysis.

[1]  T. S. Robertson,et al.  Modeling Multinational Diffusion Patterns: An Efficient Methodology , 1989 .

[2]  Staffan Jacobsson,et al.  The diffusion of renewable energy technology: an analytical framework and key issues for research , 2000 .

[3]  Gustavo O Collantes,et al.  Incorporating stakeholders' perspectives into models of new technology diffusion: The case of fuel-cell vehicles , 2007 .

[4]  Lena Neij,et al.  Use of experience curves to analyse the prospects for diffusion and adoption of renewable energy technology , 1997 .

[5]  Rui Baptista,et al.  Do innovations diffuse faster within geographical clusters , 2000 .

[6]  Arnulf Grubler,et al.  Time for a change: On the patterns of diffusion of innovation , 1996 .

[7]  J. C. Fisher,et al.  A simple substitution model of technological change , 1971 .

[8]  Ramesh Bhatia,et al.  Diffusion of renewable energy technologies in developing countries: A case study of biogas engines in India , 1990 .

[9]  A. Masini,et al.  Forecasting the diffusion of photovoltaic systems in southern Europe: A learning curve approach $ , 2003 .

[10]  Henrik Lund,et al.  The Kyoto mechanisms and technological innovation , 2006 .

[11]  Robert A. Peterson,et al.  Models for innovation diffusion , 1985 .

[12]  Robert Fildes,et al.  The role of prices in models of innovation diffusion , 1998 .

[13]  Valerio Lo Brano,et al.  Energy performances and life cycle assessment of an Italian wind farm , 2008 .

[14]  William E. Griffiths,et al.  The penetration of CDs in the sound recording market: issues in specification, model selection and forecasting , 2003 .

[15]  Timothy R. Anderson,et al.  Technology Forecasting for Wireless Communication , 2008 .

[16]  Harikesh S. Nair,et al.  Diffusion of New Pharmaceutical Drugs in Developing and Developed Nations , 2004 .

[17]  V. Narayanan Managing Technology and Innovation for Competitive Advantage , 2000 .

[18]  Pablo del Río,et al.  Overcoming the lock-out of renewable energy technologies in Spain: The cases of wind and solar electricity , 2007 .

[19]  Peter Lund,et al.  Upfront resource requirements for large-scale exploitation schemes of new renewable technologies , 2007 .

[20]  Axel Michaelowa,et al.  CDM potential of SPV pumps in India , 2005 .

[21]  N. Meade,et al.  Modelling and forecasting the diffusion of innovation – A 25-year review , 2006 .

[22]  Peter Lund,et al.  Market penetration rates of new energy technologies , 2006 .

[23]  Nigel Meade,et al.  Technological Forecasting-Model Selection, Model Stability, and Combining Models , 1998 .

[24]  Theocharis Tsoutsos,et al.  The sustainable diffusion of renewable energy technologies as an example of an innovation-focused policy , 2005 .

[25]  Maarten J. Arentsen,et al.  Green certificate trading in the Netherlands in the prospect of the European electricity market , 2003 .

[26]  Denzil G. Fiebig,et al.  A flexible logistic growth model with applications in telecommunications , 1988 .

[27]  Chemmangot Nayar,et al.  Conceptual model for marketing solar based technology to developing countries , 2002 .

[28]  F. Bass,et al.  A diffusion theory model of adoption and substitution for successive generations of high-technology products , 1987 .

[29]  J. Scott Armstrong,et al.  Principles of forecasting , 2001 .

[30]  V.V.N. Kishore,et al.  Wind power technology diffusion analysis in selected states of India , 2009 .

[31]  N. Meade The use of growth curves in forecasting market development—a review and appraisal , 1984 .

[32]  Vijay Mahajan,et al.  Chapter 8 New-product diffusion models , 1993, Marketing.

[33]  Frank M. Bass,et al.  Comments on "A New Product Growth for Model Consumer Durables The Bass Model" , 2004, Manag. Sci..

[34]  Antonio Soria,et al.  Technical change dynamics: evidence from the emerging renewable energy technologies , 2001 .

[35]  V. Dinica Support systems for the diffusion of renewable energy technologies—an investor perspective , 2006 .

[36]  Karin Ibenholt Explaining learning curves for wind power , 2002 .

[37]  Tara C. Kandpal,et al.  Renewable energy technologies for irrigation water pumping in India: projected levels of dissemination, energy delivery and investment requirements using available diffusion models , 2005 .

[38]  Frank M. Bass,et al.  A New Product Growth for Model Consumer Durables , 2004, Manag. Sci..

[39]  E. Rogers Diffusion of Innovations , 1962 .

[40]  J. Painuly,et al.  Diffusion of renewable energy technologies—barriers and stakeholders’ perspectives , 2004 .

[41]  F. Bass A new product growth model for consumer durables , 1976 .