Commenced in January 2007
Paper Count: 31113
Forecast of the Small Wind Turbines Sales with Replacement Purchases and with or without Account of Price Changes
Abstract:The purpose of the paper is to estimate the US small wind turbines market potential and forecast the small wind turbines sales in the US. The forecasting method is based on the application of the Bass model and the generalized Bass model of innovations diffusion under replacement purchases. In the work an exponential distribution is used for modeling of replacement purchases. Only one parameter of such distribution is determined by average lifetime of small wind turbines. The identification of the model parameters is based on nonlinear regression analysis on the basis of the annual sales statistics which has been published by the American Wind Energy Association (AWEA) since 2001 up to 2012. The estimation of the US average market potential of small wind turbines (for adoption purchases) without account of price changes is 57080 (confidence interval from 49294 to 64866 at P = 0.95) under average lifetime of wind turbines 15 years, and 62402 (confidence interval from 54154 to 70648 at P = 0.95) under average lifetime of wind turbines 20 years. In the first case the explained variance is 90,7%, while in the second - 91,8%. The effect of the wind turbines price changes on their sales was estimated using generalized Bass model. This required a price forecast. To do this, the polynomial regression function, which is based on the Berkeley Lab statistics, was used. The estimation of the US average market potential of small wind turbines (for adoption purchases) in that case is 42542 (confidence interval from 32863 to 52221 at P = 0.95) under average lifetime of wind turbines 15 years, and 47426 (confidence interval from 36092 to 58760 at P = 0.95) under average lifetime of wind turbines 20 years. In the first case the explained variance is 95,3%, while in the second – 95,3%.
Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1106927Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1535
 Churkin, V., Forecast of the innovative products sale (photovoltaic systems are considered). Proceedings of the 2nd International Conference Innovation Management and Company Sustainability, Prague, 2014, pp.482-493 http://imacs.vse.cz/wp-content/uploads/ 2014/08/IMACS-2014_Proceedings_final.pdf.
 Miller, A.H., Strong patent growth for renewables indicates bright future for solar. http://www.cleanenergyauthority.com/solar-energy-news/ strong-patent-growth-for-renewables-indicates-bright-future-for-solar- 101413.
 Churkin, V.I., Sales forecasts of innovative products within the macroeconomic factors (using the example of small wind turbines). St. Petersburg State Polytechnical University Journal. Economics, 1(1), 2013, pp. 104– 112.
 Bass, Frank M., A new product growth model for consumer durables. Management Science, 15(5), 1969, pp. 215–227.
 Mahajan, V., Mason, C.H., & Srinivasan, V., An evaluation of estimation procedures for new product diffusion models. Innovation Diffusion Models of New Product Acceptance, eds. V. Mahajan and Y. Wind, (Ballinger Cambridge, Massachusetts), 1986, pp. 203-232.
 Srinivasan, V., & Mason C.H., Nonlinear least squares estimation of new product diffusion model. Marketing Science, 5(2), 1986, pp. 169- 178.
 Schmittlein, D. C., & Mahajan V., Maximum likelihood estimation for an innovational diffusion model of new-product acceptance. Management Science, 1(1), 1982, pp. 57-78.
 Mahajan, V., & Sharma S., A simple algebraic estimation procedure for innovation diffusion models of new product acceptance. Technological Forecasting and Social Change, 30, 1986, pp. 331-346.
 Bass, F. M., Krishnan, T. V., & Jain, D. C., Why the Bass model fits without decision variables. Marketing Science, 13, 1994, pp. 119–130.
 Stimmel, Ron., Status of the U.S. Small-wind market. www.awea.org/smallwind.
 United States Department of Energy (DOE). 2012 Wind technologies market report, www.osti.gov/bridge.
 Wiser R.H., Tracking and understanding trends in the U.S. Wind power market: 2007 Annual report on U.S. Wind power installation, cost, and performance trends. Lawrence Berkeley National Laboratory DOE/NREL Wind Powering America Webinar, July 9, 2008. http://apps2.eere.energy.gov/wind/windexchange/pdfs/wpa/2008/wiser_ 2007_annual_wind_market_report_webcast.pdf.
 Wiser R., Bolinger M., Annual report on U.S. wind power installation, cost, and performance trends: 2006. http://www1.eere.energy.gov/wind/ pdfs/wiser_data_report_summary_2006.pdf.
 Brian T. Ratchford, Siva K. Balasubramanian, Wagner A. Kamakura, Diffusion models with replacement and multiple purchases (Chapter 6). New-product diffusion models, ed. Vijay Mahajan, Eitan Muller, Yoram Wind. Springer Science+Business Media, Inc. 2000, Springer Science+Business Media Inc., New York, 2000, pp. 123-140.
 Olson, J. and Choi, S., A product diffusion model incorporating repeat purchases. Technological Forecasting and Social Change, 27 (4), 1985, pp. 385-397.
 Kamakura, W. A. and Balasubramanian, S. K., Long-term forecasting with innovation diffusion models: The impact of replacement purchases. Journal of Forecasting, 6, 1987, pp. 1-19.