Article ID: | iaor19941758 |
Country: | Netherlands |
Volume: | 9 |
Issue: | 4 |
Start Page Number: | 517 |
End Page Number: | 526 |
Publication Date: | Dec 1993 |
Journal: | International Journal of Forecasting |
Authors: | Bunn Derek W., Vassilopoulos A.I. |
Keywords: | forecasting: applications, retailing |
Methods for dealing with seasonal patterns of product sales can be categorized into two groups: those that forecast the demand for seasonal products by estimating the individual seasonal components for each product, and those that estimate the seasonal component by combining ‘similar’ products into a product line. An approach is proposed for the latter case, based on a synthesis of time series decomposition techniques and cluster analysis. Some initial experiments on a sample of retail sales data demonstrate its feasibility and give some comparative insights into this and alternative methods.