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Method and system for multi-attribute market value assessment in analysis of construction and retrofit projects

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Date
2011
Author
Kanapeckienė, Loreta
Kaklauskas, Artūras
Zavadskas, Edmundas Kazimieras
Raslanas, Saulius
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Abstract
Multi-Attribute Decision-Making (MADM) methods prioritize the alternatives of comparative projects quite accurately. Problems arise when there is a need to determine the utility degrees and market values of the project alternatives. This becomes especially important for establishing the market value of real estate property in tender offers. However, the available MADM methods cannot accomplish this. Thus the authors of this article developed the MAMVA method, which permits determining the utility degrees and market values of project alternatives, and also developed a system on the basis of this developed method. This article presents the proposed Multi-Attribute Market Value Assessment (MAMVA) Method and the Decision Support System for Construction and Retrofit Projects (DSS-CRP). It also presents a case study to demonstrate the effectiveness of this method and system. The application of the MAMVA Method and DSS-CRP System for prioritizing and for determining the utility degrees and market values of construction and retrofit projects under consideration for financing by the European Economic Area (EEA) and Norway Financial Mechanism Grant made it possible to decrease the amount of requested support. This article also presents the analysis and comprehensive assessment of the noted construction and retrofit projects. These were performed in consideration of the entire life cycle of a project and of needs satisfaction relevant to all the groups interested in a project. The developed MAMVA Method and DSS-CRP System permit assessing the appropriateness of projects under analysis in conceptual and qualitative forms. This method and system automatically submit the values of the project alternatives.
Issue date (year)
2011
URI
https://etalpykla.vilniustech.lt/handle/123456789/132895
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  • Straipsniai Web of Science ir/ar Scopus referuojamuose leidiniuose / Articles in Web of Science and/or Scopus indexed sources [7946]

 

 

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