Estimation of Forecast Errors for Seasonal-Style-Goods Sales

Seasonal-style-goods inventories are characterized by the substantial losses associated with those merchandise items which are unsold at the end of a season. If the probability distribution for sales for the entire season were known, the decision problem would reduce to determining the optimal lot size, as in the classical newsboy problem. In reality, however, it may be possible to consider sales estimation as a multi-period inventory problem because there may be opportunities during the course of the season to review the earlier sales performance to reestimate forecast errors made earlier in the season, and to take appropriate action based on the new estimates. In this paper Kalman-Shaw linear feedback filtering is used to estimate previous forecast errors. The model is formulated in such a way that, given an initial forecast, the subsequent reestimation of the initial forecast error requires only the actual sales experience to date.

• 저널Management Science · 18(2) · B–89
• 토픽Advanced Statistical Process Monitoring · Statistics, Probability and Uncertainty
• DOI10.1287/mnsc.18.2.b89
• 저자Sang Hoon Chang, David E. Fyffe