IDEAS home Printed from https://ideas.repec.org/a/eee/tefoso/v89y2014icp43-61.html
   My bibliography  Save this article

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

Author

Listed:
  • 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.

Suggested Citation

  • 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
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0040162514002546
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.techfore.2014.08.015?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. 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.
    2. 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.
    3. 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.
    4. 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.
    5. 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.
    6. Hermann Simon & Karl-Heinz Sebastian, 1987. "Diffusion and Advertising: The German Telephone Campaign," Management Science, INFORMS, vol. 33(4), pages 451-466, April.
    7. 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.
    8. 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.
    9. 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.
    10. 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.
    11. 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.
    12. 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.
    13. 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.
    14. 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.
    15. 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.
    16. 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.
    17. 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.
    18. 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.
    19. 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.
    20. 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.
    21. 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.
    22. Frank M. Bass, 1969. "A New Product Growth for Model Consumer Durables," Management Science, INFORMS, vol. 15(5), pages 215-227, January.
    23. 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.
    24. 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.
    25. Dan Horsky, 1990. "A Diffusion Model Incorporating Product Benefits, Price, Income and Information," Marketing Science, INFORMS, vol. 9(4), pages 342-365.
    26. 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.
    27. 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.
    28. 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.
    29. Dan Horsky & Karl Mate, 1988. "Dynamic Advertising Strategies of Competing Durable Good Producers," Marketing Science, INFORMS, vol. 7(4), pages 356-367.
    30. Lund, Peter, 2006. "Market penetration rates of new energy technologies," Energy Policy, Elsevier, vol. 34(17), pages 3317-3326, November.
    31. 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.
    32. 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.
    33. Christophe Van den Bulte, 2000. "New Product Diffusion Acceleration: Measurement and Analysis," Marketing Science, INFORMS, vol. 19(4), pages 366-380, June.
    34. 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.
    35. Dan Horsky & Leonard S. Simon, 1983. "Advertising and the Diffusion of New Products," Marketing Science, INFORMS, vol. 2(1), pages 1-17.
    36. 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.
    37. 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.
    38. 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.
    39. 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.
    40. Shlomo Kalish, 1985. "A New Product Adoption Model with Price, Advertising, and Uncertainty," Management Science, INFORMS, vol. 31(12), pages 1569-1585, December.
    41. Bruce Robinson & Chet Lakhani, 1975. "Dynamic Price Models for New-Product Planning," Management Science, INFORMS, vol. 21(10), pages 1113-1122, June.
    42. 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.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Fan, Zhi-Ping & Che, Yu-Jie & Chen, Zhen-Yu, 2017. "Product sales forecasting using online reviews and historical sales data: A method combining the Bass model and sentiment analysis," Journal of Business Research, Elsevier, vol. 74(C), pages 90-100.
    2. Lee, Youseok & Kim, Sang-Hoon & Cha, Kyoung Cheon, 2021. "Impact of online information on the diffusion of movies: Focusing on cultural differences," Journal of Business Research, Elsevier, vol. 130(C), pages 603-609.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Elmar Kiesling & Markus Günther & Christian Stummer & Lea Wakolbinger, 2012. "Agent-based simulation of innovation diffusion: a review," 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. 20(2), pages 183-230, June.
    2. 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.
    3. John Hauser & Gerard J. Tellis & Abbie Griffin, 2006. "Research on Innovation: A Review and Agenda for," Marketing Science, INFORMS, vol. 25(6), pages 687-717, 11-12.
    4. Kurdgelashvili, Lado & Shih, Cheng-Hao & Yang, Fan & Garg, Mehul, 2019. "An empirical analysis of county-level residential PV adoption in California," Technological Forecasting and Social Change, Elsevier, vol. 139(C), pages 321-333.
    5. Peters, Kay & Albers, Sönke & Kumar, V., 2008. "Is there more to international Diffusion than Culture? An investigation on the Role of Marketing and Industry Variables," EconStor Preprints 27678, ZBW - Leibniz Information Centre for Economics.
    6. Dong, Changgui & Sigrin, Benjamin & Brinkman, Gregory, 2017. "Forecasting residential solar photovoltaic deployment in California," Technological Forecasting and Social Change, Elsevier, vol. 117(C), pages 251-265.
    7. Avagyan, Vardan & Esteban-Bravo, Mercedes & Vidal-Sanz, Jose M., 2014. "Licensing radical product innovations to speed up the diffusion," European Journal of Operational Research, Elsevier, vol. 239(2), pages 542-555.
    8. Ramírez-Hassan, Andrés & Montoya-Blandón, Santiago, 2020. "Forecasting from others’ experience: Bayesian estimation of the generalized Bass model," International Journal of Forecasting, Elsevier, vol. 36(2), pages 442-465.
    9. Huh, Sung-Yoon & Lee, Chul-Yong, 2014. "Diffusion of renewable energy technologies in South Korea on incorporating their competitive interrelationships," Energy Policy, Elsevier, vol. 69(C), pages 248-257.
    10. 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.
    11. Ruiz-Conde, Enar & Wieringa, Jaap E. & Leeflang, Peter S.H., 2014. "Competitive diffusion of new prescription drugs: The role of pharmaceutical marketing investment," Technological Forecasting and Social Change, Elsevier, vol. 88(C), pages 49-63.
    12. Petropoulos, Fotios & Apiletti, Daniele & Assimakopoulos, Vassilios & Babai, Mohamed Zied & Barrow, Devon K. & Ben Taieb, Souhaib & Bergmeir, Christoph & Bessa, Ricardo J. & Bijak, Jakub & Boylan, Joh, 2022. "Forecasting: theory and practice," International Journal of Forecasting, Elsevier, vol. 38(3), pages 705-871.
      • Fotios Petropoulos & Daniele Apiletti & Vassilios Assimakopoulos & Mohamed Zied Babai & Devon K. Barrow & Souhaib Ben Taieb & Christoph Bergmeir & Ricardo J. Bessa & Jakub Bijak & John E. Boylan & Jet, 2020. "Forecasting: theory and practice," Papers 2012.03854, arXiv.org, revised Jan 2022.
    13. Stefan Stremersch & Eitan Muller & Renana Peres, 2010. "Does new product growth accelerate across technology generations?," Marketing Letters, Springer, vol. 21(2), pages 103-120, June.
    14. Saurabh Panwar & P. K. Kapur & Ompal Singh, 2021. "Technology diffusion model with change in adoption rate and repeat purchases: a case of consumer balking," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 12(1), pages 29-36, February.
    15. Goodwin, Paul & Meeran, Sheik & Dyussekeneva, Karima, 2014. "The challenges of pre-launch forecasting of adoption time series for new durable products," International Journal of Forecasting, Elsevier, vol. 30(4), pages 1082-1097.
    16. Ferreira, Kevin D. & Lee, Chi-Guhn, 2014. "An integrated two-stage diffusion of innovation model with market segmented learning," Technological Forecasting and Social Change, Elsevier, vol. 88(C), pages 189-201.
    17. Deepa Chandrasekaran & Gerard J. Tellis, 2008. "Global Takeoff of New Products: Culture, Wealth, or Vanishing Differences?," Marketing Science, INFORMS, vol. 27(5), pages 844-860, 09-10.
    18. Toka, Agorasti & Iakovou, Eleftherios & Vlachos, Dimitrios & Tsolakis, Naoum & Grigoriadou, Anastasia-Loukia, 2014. "Managing the diffusion of biomass in the residential energy sector: An illustrative real-world case study," Applied Energy, Elsevier, vol. 129(C), pages 56-69.
    19. Krishnan, Trichy V. & Feng, Shanfei & Jain, Dipak C., 2023. "Peak sales time prediction in new product sales: Can a product manager rely on it?," Journal of Business Research, Elsevier, vol. 165(C).
    20. Brito, Thiago Luis Felipe & Islam, Towhidul & Stettler, Marc & Mouette, Dominique & Meade, Nigel & Moutinho dos Santos, Edmilson, 2019. "Transitions between technological generations of alternative fuel vehicles in Brazil," Energy Policy, Elsevier, vol. 134(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:tefoso:v:89:y:2014:i:c:p:43-61. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.sciencedirect.com/science/journal/00401625 .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.