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Additionality, common practice and incentive schemes for the uptake of innovations

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  • Barnes, Belinda
  • Southwell, Darren
  • Bruce, Sarah
  • Woodhams, Felicity

Abstract

Crucial components of carbon offset trading schemes are the determination of whether a technology or practice is innovative (i.e. not common practice), and whether the practice is adopted as a result of incentives (termed additional). Under schemes such as the Clean Development Mechanism (CDM), early adopters of carbon reducing technologies receive tradable carbon credits that can be sold to businesses to offset their emissions. However, frameworks for distinguishing early adopters are inconsistent, and the effect of incentive schemes on uptake is poorly understood. In this study we: 1) review measures of common practice taken from the literature with the purpose of informing a standardised approach; and 2) using the Bass model we explore the effects of incentive schemes on adoption with the purpose of establishing the proportion of uptake attributable to the scheme. We found that a fixed common practice threshold of approximately 20% adoption is well supported by a wide range of approaches, and that 85–95% (approximately) of early adoption can be attributed to incentives, such as offset schemes. Although we focussed on carbon reducing technologies, our results have broad implications for general practice and product diffusion, and the effect of promotions on adoption.

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  • Barnes, Belinda & Southwell, Darren & Bruce, Sarah & Woodhams, Felicity, 2014. "Additionality, common practice and incentive schemes for the uptake of innovations," Technological Forecasting and Social Change, Elsevier, vol. 89(C), pages 43-61.
    • Handle: RePEc:eee:tefoso:v:89:y:2014:i:c:p:43-61
    DOI: 10.1016/j.techfore.2014.08.015
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    as
    1. Engelbert Dockner & Steffen Jørgensen, 1988. "Optimal Advertising Policies for Diffusion Models of New Product Innovation in Monopolistic Situations," Management Science, INFORMS, vol. 34(1), pages 119-130, January.
    2. John A. Norton & Frank M. Bass, 1987. "A Diffusion Theory Model of Adoption and Substitution for Successive Generations of High-Technology Products," Management Science, INFORMS, vol. 33(9), pages 1069-1086, September.
    3. Tal Garber & Jacob Goldenberg & Barak Libai & Eitan Muller, 2004. "From Density to Destiny: Using Spatial Dimension of Sales Data for Early Prediction of New Product Success," Marketing Science, INFORMS, vol. 23(3), pages 419-428, August.
    4. Peres, Renana & Muller, Eitan & Mahajan, Vijay, 2010. "Innovation diffusion and new product growth models: A critical review and research directions," International Journal of Research in Marketing, Elsevier, vol. 27(2), pages 91-106.
    5. Dan Horsky & Leonard S. Simon, 1983. "Advertising and the Diffusion of New Products," Marketing Science, INFORMS, vol. 2(1), pages 1-17.
    6. Higgins, Andrew & Paevere, Phillip & Gardner, John & Quezada, George, 2012. "Combining choice modelling and multi-criteria analysis for technology diffusion: An application to the uptake of electric vehicles," Technological Forecasting and Social Change, Elsevier, vol. 79(8), pages 1399-1412.
    7. Sivan Kartha & Michael Lazarus & Maurice LeFranc, 2005. "Market penetration metrics: tools for additionality assessment?," Climate Policy, Taylor & Francis Journals, vol. 5(2), pages 147-165, March.
    8. Lambert Schneider, 2009. "Assessing the additionality of CDM projects: practical experiences and lessons learned," Climate Policy, Taylor & Francis Journals, vol. 9(3), pages 242-254, May.
    9. Frank M. Bass & Trichy V. Krishnan & Dipak C. Jain, 1994. "Why the Bass Model Fits without Decision Variables," Marketing Science, INFORMS, vol. 13(3), pages 203-223.
    10. Roger M. Heeler & Thomas P. Hustad, 1980. "Problems in Predicting New Product Growth for Consumer Durables," Management Science, INFORMS, vol. 26(10), pages 1007-1020, October.
    11. Islam, Towhidul, 2014. "Household level innovation diffusion model of photo-voltaic (PV) solar cells from stated preference data," Energy Policy, Elsevier, vol. 65(C), pages 340-350.
    12. Park, Sang Yong & Kim, Jong Wook & Lee, Duk Hee, 2011. "Development of a market penetration forecasting model for Hydrogen Fuel Cell Vehicles considering infrastructure and cost reduction effects," Energy Policy, Elsevier, vol. 39(6), pages 3307-3315, June.
    13. Hermann Simon & Karl-Heinz Sebastian, 1987. "Diffusion and Advertising: The German Telephone Campaign," Management Science, INFORMS, vol. 33(4), pages 451-466, April.
    14. Newell, Richard G. & Jaffe, Adam B. & Stavins, Robert N., 2006. "The effects of economic and policy incentives on carbon mitigation technologies," Energy Economics, Elsevier, vol. 28(5-6), pages 563-578, November.
    15. Tang, Amy & Taylor, John E. & Mahalingam, Ashwin, 2013. "Strategic structure matrix: A framework for explaining the impact of superstructure organizations on the diffusion of wind energy infrastructure," Energy Policy, Elsevier, vol. 63(C), pages 69-80.
    16. Rao, K. Usha & Kishore, V.V.N., 2010. "A review of technology diffusion models with special reference to renewable energy technologies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 14(3), pages 1070-1078, April.
    17. Frank M. Bass, 1969. "A New Product Growth for Model Consumer Durables," Management Science, INFORMS, vol. 15(5), pages 215-227, January.
    18. Greene, David L. & Patterson, Philip D. & Singh, Margaret & Li, Jia, 2005. "Feebates, rebates and gas-guzzler taxes: a study of incentives for increased fuel economy," Energy Policy, Elsevier, vol. 33(6), pages 757-775, April.
    19. Greene, David L. & Patterson, Philip D. & Singh, Margaret & Li, Jia, 2005. "Corrigendum to "Feebates, rebates and gas-guzzler taxes: a study of incentives for increased fuel economy" [Energy Policy 33 (2005) 757-775]," Energy Policy, Elsevier, vol. 33(14), pages 1901-1902, September.
    20. Shlomo Kalish & Gary L. Lilien, 1983. "Optimal Price Subsidy Policy for Accelerating the Diffusion Of Innovation," Marketing Science, INFORMS, vol. 2(4), pages 407-420.
    21. Dalla Valle, Alessandra & Furlan, Claudia, 2011. "Forecasting accuracy of wind power technology diffusion models across countries," International Journal of Forecasting, Elsevier, vol. 27(2), pages 592-601, April.
    22. Ajay Mathur & Ananth P. Chikkatur & Ambuj D. Sagar, 2007. "Past as prologue: an innovation-diffusion approach to additionality," Climate Policy, Taylor & Francis Journals, vol. 7(3), pages 230-239, May.
    23. Dan Horsky, 1990. "A Diffusion Model Incorporating Product Benefits, Price, Income and Information," Marketing Science, INFORMS, vol. 9(4), pages 342-365.
    24. Dalla Valle, Alessandra & Furlan, Claudia, 2011. "Forecasting accuracy of wind power technology diffusion models across countries," International Journal of Forecasting, Elsevier, vol. 27(2), pages 592-601.
    25. Emmanouilides, Christos J. & Davies, Richard B., 2007. "Modelling and estimation of social interaction effects in new product diffusion," European Journal of Operational Research, Elsevier, vol. 177(2), pages 1253-1274, March.
    26. Shlomo Kalish, 1985. "A New Product Adoption Model with Price, Advertising, and Uncertainty," Management Science, INFORMS, vol. 31(12), pages 1569-1585, December.
    27. Gerard J. Tellis & Stefan Stremersch & Eden Yin, 2003. "The International Takeoff of New Products: The Role of Economics, Culture, and Country Innovativeness," Marketing Science, INFORMS, vol. 22(2), pages 188-208, October.
    28. Bruce Robinson & Chet Lakhani, 1975. "Dynamic Price Models for New-Product Planning," Management Science, INFORMS, vol. 21(10), pages 1113-1122, June.
    29. Christophe Van den Bulte & Gary L. Lilien, 1997. "Bias and Systematic Change in the Parameter Estimates of Macro-Level Diffusion Models," Marketing Science, INFORMS, vol. 16(4), pages 338-353.
    30. Christophe Van den Bulte & Stefan Stremersch, 2004. "Social Contagion and Income Heterogeneity in New Product Diffusion: A Meta-Analytic Test," Marketing Science, INFORMS, vol. 23(4), pages 530-544, July.
    31. Dan Horsky & Karl Mate, 1988. "Dynamic Advertising Strategies of Competing Durable Good Producers," Marketing Science, INFORMS, vol. 7(4), pages 356-367.
    32. Higgins, Andrew & Syme, Mike & McGregor, James & Marquez, Leorey & Seo, Seongwon, 2014. "Forecasting uptake of retrofit packages in office building stock under government incentives," Energy Policy, Elsevier, vol. 65(C), pages 501-511.
    33. Vijay Mahajan & Eitan Muller & Frank M. Bass, 1995. "Diffusion of New Products: Empirical Generalizations and Managerial Uses," Marketing Science, INFORMS, vol. 14(3_supplem), pages 79-88.
    34. Heinz, B. & Graeber, M. & Praktiknjo, A.J., 2013. "The diffusion process of stationary fuel cells in a two-sided market economy," Energy Policy, Elsevier, vol. 61(C), pages 1556-1567.
    35. Lund, Peter, 2006. "Market penetration rates of new energy technologies," Energy Policy, Elsevier, vol. 34(17), pages 3317-3326, November.
    36. Rajshree Agarwal & Barry L. Bayus, 2002. "The Market Evolution and Sales Takeoff of Product Innovations," Management Science, INFORMS, vol. 48(8), pages 1024-1041, August.
    37. Shrestha, Ram M. & Timilsina, Govinda R., 2002. "The additionality criterion for identifying clean development mechanism projects under the Kyoto Protocol," Energy Policy, Elsevier, vol. 30(1), pages 73-79, January.
    38. 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.
    39. Gort, Michael & Klepper, Steven, 1982. "Time Paths in the Diffusion of Product Innovations," Economic Journal, Royal Economic Society, vol. 92(367), pages 630-653, September.
    40. Kuehne, Geoff & Llewellyn, Rick S. & Pannell, David J. & Wilkinson, Roger & Dolling, P. & Ewing, Michael A., 2011. "ADOPT: a tool for predicting adoption of agricultural innovations," 2011 Conference (55th), February 8-11, 2011, Melbourne, Australia 100570, Australian Agricultural and Resource Economics Society.
    41. V. Srinivasan & Charlotte H. Mason, 1986. "Technical Note—Nonlinear Least Squares Estimation of New Product Diffusion Models," Marketing Science, INFORMS, vol. 5(2), pages 169-178.
    42. Christophe Van den Bulte, 2000. "New Product Diffusion Acceleration: Measurement and Analysis," Marketing Science, INFORMS, vol. 19(4), pages 366-380, June.
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