| 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.