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
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
BB - Applied statistics, operational research
OECD FORD branch
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Result continuities
Project
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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