Fuzzy reasoning demand forecasting model by using meteorological factors — Case of apparel shop

In this paper, the day-to-day base sales of a store were investigated for one year - from September 2005 to August 2006. The purpose of the investigation was to establish a consumer demand forecasting model. Also, the writers observed some meteorological factors like temperature and humidity during this period in order to consider the model in relation to those factors. Then, a statistic analysis was attempted to clarify the mutual relationship between sales and meteorological factors. The paper, firstly, tried to analyze, by applying analysis of variance and correlation analysis, the relationship between the sales of each day, and the meteorological factors. And secondly, on the basis of this analysis, the meteorological factors which are thought to be the most important are selected. This leads to the construction of the fuzzy reasoning model in which demand is forecasted by using the selected meteorological factors. Then, his time, the fuzzy reasoning model of each month proposed previously is applied. By doing this, the accuracy of the forecast is thought to be improved. Finally, the writers attempt to compare the above-mentioned previous model, the one established in this paper, and a prediction from regression analysis. The utility of the fuzzy reasoning model proposed in the present paper is then discussed. The present study has found that meteorological factors affect, if not to a great extent then somewhat, peoples consumption.