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http://dx.doi.org/10.7232/JKIIE.2011.37.1.074

A Parameter Estimation of Bass Diffusion Model by the Hybrid of NLS and OLS  

Hong, Jung-Sik (Department of Industrial and Information Systems Engineering, Seoul National University of Science and Technology)
Kim, Tae-Gu (Department of Industrial Engineering, Seoul National University)
Koo, Hoon-Young (Department of Business Administration, Chungnam National University)
Publication Information
Journal of Korean Institute of Industrial Engineers / v.37, no.1, 2011 , pp. 74-82 More about this Journal
Abstract
The Bass model is a cornerstone in diffusion theory which is used for forecasting demand of durables or new services. Three well-known estimation methods for parameters of the Bass model are Ordinary Least Square (OLS), Maximum Likelihood Estimator (MLE), Nonlinear Least Square (NLS). In this paper, a hybrid method incorporating OLS and NLS is presented and it's performance is analyzed and compared with OLS and NLS by using simulation data and empirical data. The results show that NLS has the best performance in terms of accuracy and our hybrid method has the best performance in terms of stability. Specifically, hybrid method has better performance with less data. This result means much in practical aspect because the avaliable data is little when a diffusion model is used for forecasting demand of a new product.
Keywords
Bass model; OLS; NLS; MLE; Hybrid of NLS and OLS;
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Times Cited By KSCI : 2  (Citation Analysis)
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