The choice of Bass model coefficients to forecast diffusion for innovative products: An empirical investigation for new automotive technologies
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DOI: 10.1016/j.retrec.2015.06.003
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- Jérôme Massiani & Andreas Gohs, 2016. "The choice of Bass model coefficients to forecast diffusion for innovative products: An empirical investigation for new automotive technologies," Working Papers 2016: 37, Department of Economics, University of Venice "Ca' Foscari".
References listed on IDEAS
- David C. Schmittlein & Vijay Mahajan, 1982. "Maximum Likelihood Estimation for an Innovation Diffusion Model of New Product Acceptance," Marketing Science, INFORMS, vol. 1(1), pages 57-78.
- Boswijk, H. Peter & Franses, Philip Hans, 2005.
"On the Econometrics of the Bass Diffusion Model,"
Journal of Business & Economic Statistics, American Statistical Association, vol. 23, pages 255-268, July.
- Boswijk, H.P. & Franses, Ph.H.B.F., 2002. "The Econometrics Of The Bass Diffusion Model," ERIM Report Series Research in Management ERS-2002-66-MKT, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
- 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.
- 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.
- Frank M. Bass, 2004. "Comments on "A New Product Growth for Model Consumer Durables The Bass Model"," Management Science, INFORMS, vol. 50(12_supple), pages 1833-1840, December.
- 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.
- Frank M. Bass, 1969. "A New Product Growth for Model Consumer Durables," Management Science, INFORMS, vol. 15(5), pages 215-227, January.
- Rajkumar Venkatesan & Trichy V. Krishnan & V. Kumar, 2004. "Evolutionary Estimation of Macro-Level Diffusion Models Using Genetic Algorithms: An Alternative to Nonlinear Least Squares," Marketing Science, INFORMS, vol. 23(3), pages 451-464, August.
- Lee, Duk Hee & Park, Sang Yong & Kim, Jong Wook & Lee, Seong Kon, 2013. "Analysis on the feedback effect for the diffusion of innovative technologies focusing on the green car," Technological Forecasting and Social Change, Elsevier, vol. 80(3), pages 498-509.
- Hyman, Michael R., 1988. "The timeliness problem in the application of bass-type new product-growth models to durable sales forecasting," Journal of Business Research, Elsevier, vol. 16(1), pages 31-47, January.
- 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.
- 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.
- Massiani, Jérôme, 2015.
"Cost-Benefit Analysis of policies for the development of electric vehicles in Germany: Methods and results,"
Transport Policy, Elsevier, vol. 38(C), pages 19-26.
- J�r�me Massiani & J�rg Radeke, 2013. "Cost-Benefit Analysis of policies for the development of electric vehicles in Germany: methods and results," Working Papers 2013:02, Department of Economics, University of Venice "Ca' Foscari".
- van den Bulte, C. & Stremersch, S., 2003. "Contagion and heterogeneity in new product diffusion: An emperical test," ERIM Report Series Research in Management ERS-2003-077-MKT, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
- Frank M. Bass, 2004. "A New Product Growth for Model Consumer Durables," Management Science, INFORMS, vol. 50(12_supple), pages 1825-1832, December.
- J?rome Massiani, 2012. "Using Stated Preferences to Forecast the Market Diffusion of Alternative Fuel Vehicles," SCIENZE REGIONALI, FrancoAngeli Editore, vol. 2012(3), pages 93-121.
- 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.
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More about this item
Keywords
Bass diffusion model; Innovation; Electric vehicles;All these keywords.
JEL classification:
- Q55 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Environmental Economics: Technological Innovation
- O33 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Technological Change: Choices and Consequences; Diffusion Processes
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