| As a new shopping way, online shopping is based on contemporary informationtechnology. In the case of online shopping, the market demand is influenced not only byconsumer preferences, but also by the impact of development of technology and logisticsand other factors. However, traditional diffusion models may be inappropriate for demandforecasting in the case of this particular market. Therefore, the research on demanddiffusion model in the case of online shopping has important theoretical andpractical significance.This thesis, beginning with the base theory of online shopping and demand diffusion,summarized the characteristics of online shopping and fashionable dress, presented theregression model and the diffusion model. Then, taking sales of dress products in Taobaoand Tmall as an example, this thesis analyzed how the online shopping population andlogistic capacity reacted to potential adopter population, and the result showed that theyboth have a significant positive correlation. Based on this linear relationship andfundamental diffusion model, this thesis estimated monthly sales in Hubei by takingBeijing, Shanghai and Zhejiang as similar products. Next, this thesis relaxed theassumption of constant population of adopters in fundamental model and presented a newdynamic diffusion model with the assumption of the dynamic potential adopter populationchanging with online shopping population. Except May and June, the forecasting errorsare better than the fundamental one’s. |
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