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Forecasting demand for single-period products: A case study in the apparel industry

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  • Mostard, Julien
  • Teunter, Ruud
  • de Koster, René

Abstract

The problem considered is that of forecasting demand for single-period products before the period starts. We study this problem for the case of a mail order apparel company that needs to order its products pre-season. The lack of historical demand data implies that other sources of data are needed. Advance order data can be obtained by allowing a selected group of customers to pre-order at a discount from a preview catalogue. Judgments can be obtained from purchase managers or other company experts. In this paper, we compare several existing and new forecasting methods for both sources of data. The methods are generic and can be used in any single-period problem in the apparel or fashion industries. Among the pre-order based methods, a novel 'top-flop' approach provides promising results. For a small group of products from the case company, expert judgment methods perform better than the methods based on advance demand information. The comparative results are obviously restricted to the specific case study, and additional testing is required to determine whether they are valid in general.

Suggested Citation

  • Mostard, Julien & Teunter, Ruud & de Koster, René, 2011. "Forecasting demand for single-period products: A case study in the apparel industry," European Journal of Operational Research, Elsevier, vol. 211(1), pages 139-147, May.
  • Handle: RePEc:eee:ejores:v:211:y:2011:i:1:p:139-147
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    References listed on IDEAS

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    Cited by:

    1. Madhukar Nagare & Pankaj Dutta & Naoufel Cheikhrouhou, 2016. "Optimal ordering policy for newsvendor models with bidirectional changes in demand using expert judgment," OPSEARCH, Springer;Operational Research Society of India, vol. 53(3), pages 620-647, September.
    2. repec:spr:annopr:v:257:y:2017:i:1:d:10.1007_s10479-016-2204-6 is not listed on IDEAS
    3. Halkos, George & Kevork, Ilias, 2012. "Unbiased estimation of maximum expected profits in the Newsvendor Model: a case study analysis," MPRA Paper 40724, University Library of Munich, Germany.
    4. Koppius, O.R. & Ozdemir, O. & van der Laan, E.A., 2011. "Beyond Waste Reduction: Creating Value with Information Systems in Closed-Loop Supply Chains," ERIM Report Series Research in Management ERS-2011-024-LIS, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
    5. Mei, Wanxia & Du, Li & Niu, Baozhuang & Wang, Jincheng & Feng, Jiejian, 2016. "The effects of an undisclosed regular price and a positive leadtime in a presale mechanism," European Journal of Operational Research, Elsevier, vol. 250(3), pages 1013-1025.
    6. Hong, Jungsik & Koo, Hoonyoung & Kim, Taegu, 2016. "Easy, reliable method for mid-term demand forecasting based on the Bass model: A hybrid approach of NLS and OLS," European Journal of Operational Research, Elsevier, vol. 248(2), pages 681-690.

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