| Summary: | 碩士 === 國立臺灣大學 === 國際企業學研究所 === 107 === The tastes and preferences of the current customer are changing rapidly, one of the biggest problems for retail channels is to do a sales forecast in this dynamic market. Sales forecasting can play a major role in driving company''s stock prices by optimizing inventory management, human resource allocation, marketing budget allocation, etc. More specifically, with a precise new product demand forecasting model, we can predict a company’s revenue growth from product plans to reduce operational risk and improve operational efficiencies.
As one of the most popular forecasting models, the Bass diffusion model was originally designed to predict the demand for consumer durable goods. In recent years, it is also applied to non-durable goods such as movie in many theses. This study aims to predict the sales volume for non-durable and cross-category products by using Bass diffusion model and Seemingly unrelated regression model (SUR). Although the price range, sales volume, product life cycle, and price sensitivity might be different for the products, this study will standardize the important variables affecting sales and find the best prediction model with good predictive validity.
According to the Ministry of Economic Affairs, R.O.C., the public traditional market was 96.5 billion NTD in 1999, 80 billion NTD in 2010, and fell to 69.8 billion NTD in 2013. This trend shows that modern supermarket gradually replaced the traditional market and consumers'' buying behavior changed. In addition, the keys to attracting potential customers are abundant products, convenience, and price. A good sales forecasting model can optimize the use of inventory space and reduce the cost of management to facilitate those key factors. Therefore, the present study used the actual sales data of Taiwan Matsusei Supermarket from 2009 to 2010 as the object of empirical analysis, predicting the sales volume of different types of products through the innovative product sales forecasting model, and expect to provide a reference for retail channels.
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