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Predicting the development of the construction equipment market demand using economic indicators: Artificial Neural Networks approach.
KTH, School of Industrial Engineering and Management (ITM), Industrial Economics and Management (Dept.), Economics.
2017 (English)Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
Abstract [en]

Demand forecasting plays an important role for every business and gives companies an opportunity to prepare for coming shifts in the market. The empirical findings of this study aim to support construction equipment manufacturers, distributors, and suppliers in apprehending the equipment market in more depth and foreseeing market demand to be able to adjust their business strategies and production capacities, allocate resources more efficiently, optimize the level of output and stock and, as a result, reduce associated costs, increase profitability and competitiveness. It is demonstrated that demand for construction equipment is heavily influenced by changes in economic conditions and country-specific economic indicators can serve as reliable input parameters to anticipate fluctuations in the construction equipment market. The Artificial Neural Networks (ANN) forecasting technique has been successfully employed to predict sales of construction equipment four quarters ahead in selected countries (Germany, The United Kingdom, France, Italy, Norway, Russia, Turkey and Saudi Arabia) with country related economic indicators used as an input.

Place, publisher, year, edition, pages
2017. , 31 p.
Series
Examensarbete INDEK
Keyword [en]
construction equipment, economic indicators, artificial neural networks, demand forecasting.
National Category
Economics
Identifiers
URN: urn:nbn:se:kth:diva-209044OAI: oai:DiVA.org:kth-209044DiVA: diva2:1110017
Educational program
Degree of Master - Economics of Innovation and Growth
Presentation
2017-05-24, 09:39 (English)
Supervisors
Examiners
Available from: 2017-07-11 Created: 2017-06-15 Last updated: 2017-07-11Bibliographically approved

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CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf