SwePub
Sök i LIBRIS databas

  Extended search

onr:"swepub:oai:DiVA.org:his-18248"
 

Search: onr:"swepub:oai:DiVA.org:his-18248" > Distributions of fo...

  • 1 of 1
  • Previous record
  • Next record
  •    To hitlist

Distributions of forecasting errors of forecast combinations : Implications for inventory management

Barrow, Devon K. (author)
School of Strategy and Leadership, Faculty of Business and Law, Coventry University, Coventry, West Midlands, United Kingdom
Kourentzes, Nikolaos (author)
Lancaster University Management School, Department of Management Science, Lancaster, United Kingdom
 (creator_code:org_t)
Elsevier, 2016
2016
English.
In: International Journal of Production Economics. - : Elsevier. - 0925-5273 .- 1873-7579. ; 177, s. 24-33
  • Journal article (peer-reviewed)
Abstract Subject headings
Close  
  • Inventory control systems rely on accurate and robust forecasts of future demand to support decisions such as setting of safety stocks. The combination of multiple forecasts is shown to be effective not only in reducing forecast errors, but also in being less sensitive to limitations of a single model. Research on forecast combination has primarily focused on improving accuracy, largely ignoring the overall shape and distribution of forecast errors. Nonetheless, these are essential for managing the level of aversion to risk and uncertainty for companies. This study examines the forecast error distributions of base and combination forecasts and their implications for inventory performance. It explores whether forecast combinations transform the forecast error distribution towards desired properties for safety stock calculations, typically based on the assumption of normally distributed errors and unbiased forecasts. In addition, it considers the similarity between in- and out-of-sample characteristics of such errors and the impact of different lead times. The effects of established combination methods are explored empirically using a representative set of forecasting methods and a dataset of 229 weekly demand series from a leading household and personal care UK manufacturer. Findings suggest that forecast combinations make the in- and out-of-sample behaviour more consistent, requiring less safety stock on average than base forecasts. Furthermore we find that using in-sample empirical error distributions of combined forecasts approximates well the out-of-sample ones, in contrast to base forecasts. 

Subject headings

NATURVETENSKAP  -- Matematik -- Sannolikhetsteori och statistik (hsv//swe)
NATURAL SCIENCES  -- Mathematics -- Probability Theory and Statistics (hsv//eng)
SAMHÄLLSVETENSKAP  -- Ekonomi och näringsliv -- Nationalekonomi (hsv//swe)
SOCIAL SCIENCES  -- Economics and Business -- Economics (hsv//eng)
TEKNIK OCH TEKNOLOGIER  -- Samhällsbyggnadsteknik -- Transportteknik och logistik (hsv//swe)
ENGINEERING AND TECHNOLOGY  -- Civil Engineering -- Transport Systems and Logistics (hsv//eng)

Keyword

Combination
Forecasting
Inventory
Safety stock
Time series
Errors
Inventory control
Normal distribution
Safety engineering
Combination forecast
Forecast combinations
Inventory performance
Risk and uncertainty
Safety-stock calculations

Publication and Content Type

ref (subject category)
art (subject category)

Find in a library

To the university's database

  • 1 of 1
  • Previous record
  • Next record
  •    To hitlist

Find more in SwePub

By the author/editor
Barrow, Devon K.
Kourentzes, Niko ...
About the subject
NATURAL SCIENCES
NATURAL SCIENCES
and Mathematics
and Probability Theo ...
SOCIAL SCIENCES
SOCIAL SCIENCES
and Economics and Bu ...
and Economics
ENGINEERING AND TECHNOLOGY
ENGINEERING AND ...
and Civil Engineerin ...
and Transport System ...
Articles in the publication
International Jo ...
By the university
University of Skövde

Search outside SwePub

Kungliga biblioteket hanterar dina personuppgifter i enlighet med EU:s dataskyddsförordning (2018), GDPR. Läs mer om hur det funkar här.
Så här hanterar KB dina uppgifter vid användning av denna tjänst.

 
pil uppåt Close

Copy and save the link in order to return to this view