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

NLS와 OLS의 하이브리드 방법에 의한 Bass 확산모형의 모수추정

  • 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)
  • 홍정식 (서울과학기술대학교 IT정책전문대학원 산업정보시스템) ;
  • 김태구 (서울대학교 산업공학과) ;
  • 구훈영 (충남대학교 경영학과)
  • Received : 2010.12.18
  • Accepted : 2011.02.07
  • Published : 2011.03.01

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

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