IDEAS home Printed from https://ideas.repec.org/a/vrn/journl/y2023i3p213-223.html
   My bibliography  Save this article

An Approach To Modeling The Probable Consumers Demand Of Food Products Using Pearson Distribution System And Johnson Distribution System

Author

Listed:
  • Julieta MIHAYLOVA

    (Department of Statistics and Applied Mathematics, Univercity of Economics - Varna, Bulgaria)

Abstract

To meet the random consumers demand the distributors maintain inventory. For optimal inventory control under random demand it is necessary to know the cumulative distribution function (CDF). The practical determination of CDF is related with a number of difficulties. This paper proposes a way to construct a probability distribution function of demand. Data on weekly sales of over 400 types of food products over a period of five years in a small distribution company were analyzed. The ARIMA model was used for primary analysis of the consumption data. Random variables are modeled using Pearson Distribution System and Johnson Distribution System and can be used to determine inventory management strategies.

Suggested Citation

  • Julieta MIHAYLOVA, 2023. "An Approach To Modeling The Probable Consumers Demand Of Food Products Using Pearson Distribution System And Johnson Distribution System," Business & Management Compass, University of Economics Varna, issue 3, pages 213-223.
  • Handle: RePEc:vrn:journl:y:2023:i:3:p:213-223
    as

    Download full text from publisher

    File URL: https://journal.ue-varna.bg/uploads/20231024113258_6184927586537ab6aa4c10.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Nick T. Thomopoulos, 2015. "Demand Forecasting for Inventory Control," Springer Books, in: Demand Forecasting for Inventory Control, edition 127, chapter 1, pages 1-10, Springer.
    2. Nick T. Thomopoulos, 2015. "Demand Forecasting for Inventory Control," Springer Books, Springer, edition 127, number 978-3-319-11976-2, January.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Tasdemir, Cagatay & Hiziroglu, Salim, 2019. "Achieving cost efficiency through increased inventory leanness: Evidences from oriented strand board (OSB) industry," International Journal of Production Economics, Elsevier, vol. 208(C), pages 412-433.
    2. Sagaert, Yves R. & Kourentzes, Nikolaos & De Vuyst, Stijn & Aghezzaf, El-Houssaine & Desmet, Bram, 2019. "Incorporating macroeconomic leading indicators in tactical capacity planning," International Journal of Production Economics, Elsevier, vol. 209(C), pages 12-19.
    3. Koussaila Hamiche & Michel Fliess & Cédric Join & Hassane Abouaïssa, 2019. "Bullwhip effect attenuation in supply chain management via control-theoretic tools and short-term forecasts: A preliminary study with an application to perishable inventories," Post-Print hal-02050480, HAL.

    More about this item

    Keywords

    Food distribution; ARIMA model; Pearson distribution system; Johnson distribution system;
    All these keywords.

    JEL classification:

    • C02 - Mathematical and Quantitative Methods - - General - - - Mathematical Economics
    • L81 - Industrial Organization - - Industry Studies: Services - - - Retail and Wholesale Trade; e-Commerce

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:vrn:journl:y:2023:i:3:p:213-223. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Yana Doneva (email available below). General contact details of provider: https://edirc.repec.org/data/uevarbg.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.