The Bass (1969) model has been a standard for analyzing and predicting the market penetration of new products. The authors demonstrate the insights to be gained and predictive performance of Functional Data Analysis (FDA), on the market penetration of 760 categories drawn from 21 products and 70 countries. The authors compare a Functional Regression approach to several models including the Classic Bass model.
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References
Bass, F. M.:(1969), A new product growth for model consumer durables. Manage-ment Science. 15, 215-227
Chandrasekaran, Deepa and Gerard J Tellis: Di usion of New Products: A Critical Review of Models, Drivers, and Findings, Review of Marketing, 39-80 (2007).
Chandrasekaran, Deepa and Gerard J Tellis: Global Takeo of New Products: Cul-ture, Economics or Vanishing Di erences forthcoming,. Marketing Science. (2008).
Hastie, T. J. and Tibshirani, R. J.: Generalized Additive Models. Chapman and Hall. (1990).
MacQueen, J. B.: Some Methods for classi cation and Analysis of Multivariate ob-servations, Proceedings of 5-th Berkeley Symposium on Mathematical Statistics and Probability, Berkeley, University of California Press, 1, 281-297 (1967).
Peres, Renana, Eitan Mueller and Vijay Mahajan: "Review of Research on Di usion. forthcoming, Marketing Science. (2007).
Ramsay, J.O. and Silverman, B.W.: Functional Data Analysis. Springer (2nd Edi-tion). (2005).
Sugar, C. A. and James, G. M.: Finding the number of clusters in a data set: An information theoretic approach, Journal of the American Statistical Association. 98, 750-763 (2003).
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James, G., Sood, A., Tellis, G. (2008). Marketing Applications of Functional Data Analysis. In: Functional and Operatorial Statistics. Contributions to Statistics. Physica-Verlag HD. https://doi.org/10.1007/978-3-7908-2062-1_32
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DOI: https://doi.org/10.1007/978-3-7908-2062-1_32
Publisher Name: Physica-Verlag HD
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