A Study On Demand Forecasting For Electronic Products With Short Life Cycle

With the rapid development of science and technology, the trend of global competition becomes obviously. Competition is intensified among enterprises, which results in that its ability of researching strengthened. In addition, consumers’preference is changing and the number of personalized products is increasing, so that shorter and shorter life cycle of new product is becomes a tendency. As for enterprises which product electronic products, it is necessary to predict the demand of products accurately because of life circle shortened. Only in this way, can it be better to meet the market demand and guide enterprises in actual production, which is beneficial to make appropriate production plan and gain higher profits. Accordingly, it is practical meaning that researching in demand forecasting for electronic products with short life cycle.Traditional forecasting methods do not take the characteristics of electronic products with short life cycle into consideration, so they may not be applied to the demand forecasting for electronic products with short life cycle. Therefore research in demand forecasting for electronic products with short life cycle will be of great theoretical value in enriching the forecasting theories and broadening the forecasting methods.This thesis has following contents:First of all, it proposes that Bass diffusion model can be applied to the demand forecasting for electronic products with short life cycle by summarizing the relevant literature. Secondly, it introduces some related theoretical knowledge, and then makes some further research in Bass model’s structure and application methods. Thirdly, based on summarizing the characteristics of electronic products with short life cycle and analyzing feasibility of application of Bass model, it can be applied to demand forecasting for electronic products with short life cycle. Besides, in order to improve the Bass model, parameters in it are modified according to consumers’preference. Finally, prediction in demand forecasting of mobile phones from company M indicates that modified Bass model is superior to the old Bass model in the MAD, RMSE, MAPE and other error indicators when applied to demand forecasting for electronic products with short life cycle. Finally, further direction of research interests has been put forward base on this study. The model can be modified by making consumers’preference affecting demand forecasting dynamically. The model can be modified continuously with the appearance of new sales data. Different forecasting methods also can be combined to forecast the demand according to a certain weight. And the model this study proposed can be combined with the sales experiences of salesmen. Then, the more accurate prediction of demand forecasting for electronic products with short life cycle will be obtained.