|
The composite stores are a mixed style of operation from different industry, which serving different clients and expanding the customers’ purchasing power. Existing forms of composite stores evolve from gas stations and convenience store, enabling customers to buy merchandise while fueling their cars. These kinds of stores have been successfully operating attached with oil filling stations in many countries.
The market size of confectionery, biscuit and commodity in Taiwan is huge. Although its sales channels are various, the thesis focuses on the complex chain of composite stores for the selection of candy and cookies commodity sales forecast. Selecting ten candies and cookies commodities, the study applies sales level criteria fuzzy model to the composite store merchandise. Further, several methods are used from sales experience combined with expert, high-level selection and ranking score, and the weighted value of the global commodity. Experienced experts are surveyed in mixed-mode time series forecasting in order to predict the selection of merchandise sales.
The results show, the selection mode of products found in this study could be predicted for high-level sorting of goods. This prediction model calculation shows that the amount of its sales forecast and the global weighting of the sort order is the same. Theory developed in this study would be applied to predict the sales of goods and a reliable reference for the complex choices of stores.
|