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Forecasting Demand for Automotive Aftermarket Inventories

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  • Ovidiu-Alin DOBRICAN

Abstract

Management decisions regarding the resource allocation in the automotive aftermarket in-volves a good understanding of it. This includes a better understanding of the participants in this market, the supply chains, specificities products and demand for these products. A useful instrument to anticipate the latter is the use of simulation methods, one of them being the Monte Carlo method, which, in this paper, is used to create various scenarios of supply.

Suggested Citation

  • Ovidiu-Alin DOBRICAN, 2013. "Forecasting Demand for Automotive Aftermarket Inventories," Informatica Economica, Academy of Economic Studies - Bucharest, Romania, vol. 17(2), pages 119-129.
    • Handle: RePEc:aes:infoec:v:17:y:2013:i:2:p:119-129
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    File URL: http://www.revistaie.ase.ro/content/66/10%20-%20Dobrican.pdf
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    References listed on IDEAS

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    1. Zhang, Allan N. & Goh, Mark & Meng, Fanwen, 2011. "Conceptual modelling for supply chain inventory visibility," International Journal of Production Economics, Elsevier, vol. 133(2), pages 578-585, October.
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    Cited by:

    1. Răzvan Daniel ZOTA & Yasser AL HADAD, 2018. "Optimized Demand Forecasting by Cross-Validation," Book chapters-LUMEN Proceedings, in: Veaceslav MANOLACHI & Cristian Mihail RUS & Svetlana RUSNAC (ed.), New Approaches in Social and Humanistic Sciences, edition 1, volume 3, chapter 50, pages 563-574, Editura Lumen.
    2. Răzvan Daniel ZOTA & Yasser AL HADAD, 2018. "Inventory Management Using Cross Prediction," Book chapters-LUMEN Proceedings, in: Veaceslav MANOLACHI & Cristian Mihail RUS & Svetlana RUSNAC (ed.), New Approaches in Social and Humanistic Sciences, edition 1, volume 3, chapter 51, pages 575-585, Editura Lumen.

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