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- W2336259170 abstract "It is very important for a firm to be able to forecast the sales volumes of new products. However, current environments usually have uncertain factors and rapid changes, and decision makers must make forecasts in these fluctuating situations with minimal data. Previous studies combine scenario analysis and the technology substitution model to forecast the market share of multigenerational technologies, which is one kind of interpolation method. However, a technology substitution model based on a logistic curve does not always fit the S-curve well. Therefore, based on historical data and the data forecasted by the scenario and Delphi methods, a two-stage fuzzy piecewise logistic growth model is proposed. The piecewise concept is adopted in order to understand the market impact of a new product so that it will be possible to determine the effective length of sales forecasting intervals even when handling large-variation data. In order to demonstrate the model’s performance, the researchers used Tseng et al.’s data from 2009, the market share of an organic light-emitting diode (OLED) television (TV), and four other TV technologies in three possible scenarios of the global market: optimistic, pessimistic, and most possible. The results show that the proposed model outperforms the technology substitution model." @default.
- W2336259170 created "2016-06-24" @default.
- W2336259170 creator A5041656462 @default.
- W2336259170 date "2014-01-01" @default.
- W2336259170 modified "2023-10-17" @default.
- W2336259170 title "A Two-Stage Fuzzy Piecewise Logistic Model for Two Different Harmonic Excitations" @default.
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- W2336259170 doi "https://doi.org/10.20855/ijav.2014.19.3348" @default.
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