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Forecasting and stock control: A study in a wholesaling context

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  • Syntetos, A.A.
  • Babai, M.Z.
  • Davies, J.
  • Stephenson, D.

Abstract

Wholesalers add value to the products they deal with by essentially bringing them closer to the end consumers. In that respect, the effective control of stock levels becomes an important measure of operational performance especially in the context of achieving high customer service levels. In this paper, we address issues pertinent to forecasting and inventory management in a wholesaling environment and discuss the recommendations proposed in such a context in a case study organization. Our findings demonstrate the considerable scope that exists for improving current practices and offers insights into possible managerial issues.

Suggested Citation

  • Syntetos, A.A. & Babai, M.Z. & Davies, J. & Stephenson, D., 2010. "Forecasting and stock control: A study in a wholesaling context," International Journal of Production Economics, Elsevier, vol. 127(1), pages 103-111, September.
    • Handle: RePEc:eee:proeco:v:127:y:2010:i:1:p:103-111
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    1. Boylan, J.E. & Syntetos, A.A., 2007. "The accuracy of a Modified Croston procedure," International Journal of Production Economics, Elsevier, vol. 107(2), pages 511-517, June.
    2. H Chen & J E Boylan, 2007. "Use of individual and group seasonal indices in subaggregate demand forecasting," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 58(12), pages 1660-1671, December.
    3. Germain, Richard & Droge, Cornelia, 1990. "Wholesale operations and vendor evaluation," Journal of Business Research, Elsevier, vol. 21(2), pages 119-129, September.
    4. Gutierrez, Rafael S. & Solis, Adriano O. & Mukhopadhyay, Somnath, 2008. "Lumpy demand forecasting using neural networks," International Journal of Production Economics, Elsevier, vol. 111(2), pages 409-420, February.
    5. Syntetos, Aris A. & Boylan, John E., 2005. "The accuracy of intermittent demand estimates," International Journal of Forecasting, Elsevier, vol. 21(2), pages 303-314.
    6. Syntetos, Aris A. & Nikolopoulos, Konstantinos & Boylan, John E. & Fildes, Robert & Goodwin, Paul, 2009. "The effects of integrating management judgement into intermittent demand forecasts," International Journal of Production Economics, Elsevier, vol. 118(1), pages 72-81, March.
    7. Porras, Eric & Dekker, Rommert, 2008. "An inventory control system for spare parts at a refinery: An empirical comparison of different re-order point methods," European Journal of Operational Research, Elsevier, vol. 184(1), pages 101-132, January.
    8. Suraj M. Alexander, 1985. "Discovering and Correcting Problems in a Naval Stock Control System," Interfaces, INFORMS, vol. 15(4), pages 41-47, August.
    9. Altay, Nezih & Rudisill, Frank & Litteral, Lewis A., 2008. "Adapting Wright's modification of Holt's method to forecasting intermittent demand," International Journal of Production Economics, Elsevier, vol. 111(2), pages 389-408, February.
    10. Syntetos, A. A. & Boylan, J. E., 2001. "On the bias of intermittent demand estimates," International Journal of Production Economics, Elsevier, vol. 71(1-3), pages 457-466, May.
    11. Willemain, Thomas R. & Smart, Charles N. & Shockor, Joseph H. & DeSautels, Philip A., 1994. "Forecasting intermittent demand in manufacturing: a comparative evaluation of Croston's method," International Journal of Forecasting, Elsevier, vol. 10(4), pages 529-538, December.
    12. Pearson, Michael, 2006. "The application of prediction capability and adaptive target control to the newspaper business," European Journal of Operational Research, Elsevier, vol. 168(2), pages 475-491, January.
    13. Schneider, Helmut & Rinks, Dan B., 1991. "Empirical study of a new procedure for allocating safety stock in a wholesale inventory system," International Journal of Production Economics, Elsevier, vol. 24(1-2), pages 181-189, November.
    14. R Fildes & K Nikolopoulos & S F Crone & A A Syntetos, 2008. "Forecasting and operational research: a review," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 59(9), pages 1150-1172, September.
    15. Leven, Erik & Segerstedt, Anders, 2004. "Inventory control with a modified Croston procedure and Erlang distribution," International Journal of Production Economics, Elsevier, vol. 90(3), pages 361-367, August.
    16. A H C Eaves & B G Kingsman, 2004. "Forecasting for the ordering and stock-holding of spare parts," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 55(4), pages 431-437, April.
    17. Morris A. Cohen & Yu-Sheng Zheng & Yunzeng Wang, 1999. "Identifying Opportunities for Improving Teradyne's Service-Parts Logistics System," Interfaces, INFORMS, vol. 29(4), pages 1-18, August.
    18. Ritchie, E. & Kingsman, B. G., 1985. "Setting stock levels for wholesaling: Performance measures and conflict of objectives between supplier and stockist," European Journal of Operational Research, Elsevier, vol. 20(1), pages 17-24, April.
    19. Morris Cohen & Pasumarti V. Kamesam & Paul Kleindorfer & Hau Lee & Armen Tekerian, 1990. "Optimizer: IBM's Multi-Echelon Inventory System for Managing Service Logistics," Interfaces, INFORMS, vol. 20(1), pages 65-82, February.
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    Cited by:

    1. Grzegorz Chodak, 2020. "The problem of shelf-warmers in electronic commerce: a proposed solution," Information Systems and e-Business Management, Springer, vol. 18(2), pages 259-280, June.
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    3. Bruzda, Joanna, 2020. "Demand forecasting under fill rate constraints—The case of re-order points," International Journal of Forecasting, Elsevier, vol. 36(4), pages 1342-1361.
    4. Grzegorz, Chodak, 2016. "The Nuisance of Slow Moving Products in Electronic Commerce," MPRA Paper 69817, University Library of Munich, Germany.
    5. Ferbar Tratar, Liljana, 2015. "Forecasting method for noisy demand," International Journal of Production Economics, Elsevier, vol. 161(C), pages 64-73.
    6. Rego, José Roberto do & Mesquita, Marco Aurélio de, 2015. "Demand forecasting and inventory control: A simulation study on automotive spare parts," International Journal of Production Economics, Elsevier, vol. 161(C), pages 1-16.
    7. Omar, Haytham & Klibi, Walid & Babai, M. Zied & Ducq, Yves, 2023. "Basket data-driven approach for omnichannel demand forecasting," International Journal of Production Economics, Elsevier, vol. 257(C).
    8. Altay, Nezih & Litteral, Lewis A. & Rudisill, Frank, 2012. "Effects of correlation on intermittent demand forecasting and stock control," International Journal of Production Economics, Elsevier, vol. 135(1), pages 275-283.
    9. Teunter, R.H. & Syntetos, A.A. & Babai, M.Z., 2017. "Stock keeping unit fill rate specification," European Journal of Operational Research, Elsevier, vol. 259(3), pages 917-925.
    10. Bacchetti, A. & Plebani, F. & Saccani, N. & Syntetos, A.A., 2013. "Empirically-driven hierarchical classification of stock keeping units," International Journal of Production Economics, Elsevier, vol. 143(2), pages 263-274.
    11. Daniel Y. Mo & Chris Y. T. Ma & Danny C. K. Ho & Yue Wang, 2022. "Design of a Reverse Logistics System with Internet of Things for Service Parts Management," Sustainability, MDPI, vol. 14(19), pages 1-15, September.

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