| Summary: | 碩士 === 大葉大學 === 工業工程研究所 === 90 === Demand forecasting is an important work in demand management, and diffusion model had been used to forecast the demand of innovation products for several years. Bass diffusion model describes the empirical adoption curve by using two important factors, namely, the coefficients of innovation and imitation. In 1975, R-L model incorporated the decision variable─price into diffusion model. A generalized Bass model incorporated price and advertising policies into the original Bass model to analyze empirical new product diffusion process. A system dynamics diffusion model was constructed to model the dynamical diffusion process of a new product in this research. In addition to the four factors, the effect of product brand was added into the system dynamic model, and use fuzzy theory to fuzzify some subjective parameters. In this thesis, a graphic user interface and a dynamic link file that include fuzzy control mechanism are programmed with Microsoft Visual C++. The model was tested and results revealed that the prediction capability of the proposed system dynamics model is better than those of Bass diffusion model, R-L model and generalized Bass model.
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