以層級貝氏模型預測廠商異質性下之銷售量—以晶片廠商為例

Abstract

Abstract Sales forecast has been an integral part of business planning, especially to the high-tech industry where product life cycle is short and intensive capital expenditure is required. However, forecasts in industrial product are usually less accurate and companies tend to adopt different forecast practices compared with consumer product industry. Coupled with the fact that the market structure for high-tech industry has been undergone several waves of evolutions, forecast method should be modified to adjust for improvements. This research paper proposed using a 2 level Hierarchical Bayesian Model that takes customer heterogeneity into account. The first level will address the aggregate factors affecting sales in the industry, whereas the second level utilizes firm specific factors to explain variations among customer purchasing behavior. Empirical analysis was accomplished with the data that recorded sales volume and firm attributes of 8 key accounts from an IC design company.