Easy, reliable method for mid-term demand forecasting based on the Bass model: A hybrid approach of NLS and OLS

Jungsik Hong, Hoonyoung Koo, Taegu Kim

Research output: Contribution to journalArticlepeer-review

14 Scopus citations

Abstract

For mid-term demand forecasting, the accuracy, stability, and ease of use of the forecasting method are considered important user requirements. We propose a new forecasting method using linearization of the hazard rate formula of the Bass model. In the proposal, reduced non-linear least square method is used to determine the market potential estimate, after the estimates for the coefficient of innovation and the coefficient of imitation are obtained by using ordinary least square method with the new linearization of the Bass model. Validations of 29 real data sets and 36 simulation data sets show that the proposed method is accurate and stable. Considering the user requirements, our method could be suitable for mid-term forecasting based on the Bass model. It has high forecasting accuracy and superior stability, is easy to understand, and can be programmed using software such as MS Excel and Matlab.

Original languageEnglish
Pages (from-to)681-690
Number of pages10
JournalEuropean Journal of Operational Research
Volume248
Issue number2
DOIs
StatePublished - 16 Jan 2016

Keywords

  • Forecasting
  • Genetic algorithm
  • New product diffusion
  • Nonlinear least square
  • Ordinary least square

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