Asymmetrical Evaluation of Forecasting Models Through Fresh Food Product Characteristics

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Abstract

Forecasting accuracy in context of fresh meat products with short shelf life is studied. Main findings are that forecasting accuracy measures (i.e. errors) should penalize deviations differently according to product characteristics, mainly dependent on whether the deviation is large or small, negative or positive. This study proposes a decision-based mean hybrid evaluation which penalize deviations according to type of animal, demand type, product life cycle and product criticality, i.e. shelf life, inventory level and future demand.

Original languageEnglish
Title of host publicationAdvances in Production Management Systems. Production Management for the Factory of the Future : IFIP WG 5.7 International Conference, APMS 2019, Austin, TX, USA, September 1–5, 2019, Proceedings, Part I
EditorsFarhad Ameri, Kathryn E. Stecke, Gregor von Cieminski, Dimitris Kiritsis
Number of pages9
Volume1
PublisherSpringer
Publication date2019
Pages155-163
ISBN (Print)978-3-030-29999-6
ISBN (Electronic)978-3-030-30000-5
DOIs
Publication statusPublished - 2019
EventIFIP WG 5.7 International Conference, APMS 2019 - Austin, United States
Duration: 1 Sep 20195 Sep 2019

Conference

ConferenceIFIP WG 5.7 International Conference, APMS 2019
Country/TerritoryUnited States
CityAustin
Period01/09/201905/09/2019
SeriesIFIP AICT - Advances in Information and Communication technology
Volume566
ISSN1571-5736

Keywords

  • Differentiation
  • Error
  • Forecast
  • Fresh food
  • Shelf life

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