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Inventory Management Using Cross Prediction

In: New Approaches in Social and Humanistic Sciences

Author

Listed:
  • Răzvan Daniel ZOTA

    (The Bucharest University of Economic Studies, Bucharest, Romania)

  • Yasser AL HADAD

    (The Bucharest University of Economic Studies, Bucharest, Romania)

Abstract

Inventory management involves determining optimum inventory stock that should be held. It is necessary to introduce a set of policies and controls that establish and track levels of inventory and determine when stock should be refilled. At a firm level, identifying all opportunities for optimizing the value chain and lowering the warehouse cost is a main requirement for an efficient stock management. In this paper a supply chain application is modelled to support and optimize the stock management activity. This topic is addressed by using autoregressive method to model a supply chain application. Also, the potential of cross prediction is tested for increasing the performance of the auto regression method. SQL server Analysis services and visual basic for application is used for implementing the supply chain application.

Suggested Citation

  • 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.
    • Handle: RePEc:lum:prchap:03-51
    DOI: https://doi.org/10.18662/lumproc.nashs2017.51
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    References listed on IDEAS

    as
    1. Radojko LUKIC, 2012. "The Effects of Application of Lean Concept in Retail," Economia. Seria Management, Faculty of Management, Academy of Economic Studies, Bucharest, Romania, vol. 15(1), pages 88-98, June.
    2. Daniela Magdalena Dinu, 2013. "Inventory management within a food factory," International Conference on Competitiveness of Agro-food and Environmental Economy Proceedings, The Bucharest University of Economic Studies, vol. 2, pages 269-274.
    3. Ovidiu-Alin DOBRICAN, 2013. "Forecasting Demand for Automotive Aftermarket Inventories," Informatica Economica, Academy of Economic Studies - Bucharest, Romania, vol. 17(2), pages 119-129.
    Full references (including those not matched with items on IDEAS)

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    More about this item

    Keywords

    Inventory management; BI (Business intelligence); SAS (SQL analysis services); cross prediction; Data analysis;
    All these keywords.

    JEL classification:

    • A3 - General Economics and Teaching - - Multisubject Collective Works
    • I2 - Health, Education, and Welfare - - Education
    • I3 - Health, Education, and Welfare - - Welfare, Well-Being, and Poverty
    • M0 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - General

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