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Improving Forecast Accuracy through Application of Temporal Aggregation

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216275%3A25310%2F16%3A39901275" target="_blank" >RIV/00216275:25310/16:39901275 - isvavai.cz</a>

  • Result on the web

    <a href="http://dx.doi.org/10.5593/sgemsocial2016B23" target="_blank" >http://dx.doi.org/10.5593/sgemsocial2016B23</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.5593/sgemsocial2016B23" target="_blank" >10.5593/sgemsocial2016B23</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    Improving Forecast Accuracy through Application of Temporal Aggregation

  • Original language description

    Hierarchical forecasting (HF) has traditionally been applied to decrease the time and financial demands of the demand planning process in the cases where the company forecasts demand for a large number of items with a large number of customers. The current surveys show that application of a suitable HF method can result in improved accuracy of demand forecasts on different levels of its cross-sectional aggregation (based on products or territory). However, the area of temporal aggregation does not enjoy sufficient attention in the literature. This paper aims to analyze the influence of the choice of an HF method on the accuracy of corporate forecasts created on different levels of temporal aggregation of the demand. A case study conducted in a manufacturing company of the food industry included time series forecasting in 23 key products of the company on 3 levels of temporal aggregation of sales (yearly, quarterly and monthly sales) using 4 fundamentally different approaches to hierarchical forecasting (bottom-up, middle-out, top-down and optimal combination methods). The forecast accuracy was evaluated through MdAPE indicator. Testing of statistical hypotheses helped to confirm whether choice of an HF method has a significant effect on a change in the monitored forecast error. The study outcomes showed that choice of an HF method affects the accuracy of corporate forecasts. However, the forecasting error was significantly decreased on all the levels of temporal aggregation only when the bottom-up method was applied.

  • Czech name

  • Czech description

Classification

  • Type

    D - Article in proceedings

  • CEP classification

    BB - Applied statistics, operational research

  • OECD FORD branch

Result continuities

  • Project

  • Continuities

    S - Specificky vyzkum na vysokych skolach

Others

  • Publication year

    2016

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Article name in the collection

    SGEM 2016 : Political Sciences, Law, Finance, Economics and Tourism Conference Proceedings. Book 2. Vol. 3

  • ISBN

    978-619-7105-74-2

  • ISSN

    2367-5659

  • e-ISSN

  • Number of pages

    8

  • Pages from-to

    901-908

  • Publisher name

    STEF92 Technology Ltd.

  • Place of publication

    Sofie

  • Event location

    Albena

  • Event date

    Aug 22, 2016

  • Type of event by nationality

    EUR - Evropská akce

  • UT code for WoS article

    000395727000113