| Title of paper:
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Ranking of factors affecting pricing in construction projects by intuitionistic fuzzy analytic hierarchy process with ordered pairs
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| Author(s):
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| Selçuk Çebi
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Department of Industrial Engineering, Yildiz Technical University, Beşiktaş 34349, Türkiye
Industrial Data Analytics and Decision Support Systems Center, Azerbaijan State University of Economics (UNEC), Baku 1001, Azerbaijan
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| scebi@yildiz.edu.tr
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| Cengiz Kahraman
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| Department of Industrial Engineering, Istanbul Technical University, Beşiktaş 34349, Türkiye
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| kahramanc@yildiz.edu.tr
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| Sezi Çevik Onar
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| Department of Industrial Engineering, Istanbul Technical University, Beşiktaş 34349, Türkiye
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| cevikse@itu.edu.tr
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| Başar Öztayşi
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| Department of Industrial Engineering, Istanbul Technical University, Beşiktaş 34349, Türkiye
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| oztaysib@itu.edu.tr
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| Presented at:
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Proceedings of the 27th International Conference on Intuitionistic Fuzzy Sets, 5–6 July 2024, Burgas, Bulgaria
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| Published in:
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Notes on Intuitionistic Fuzzy Sets, Volume 30 (2024), Number 2, pages 131–141
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| DOI:
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https://doi.org/10.7546/nifs.2024.30.2.131-141
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| Download:
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 PDF (665 Kb, Info)
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| Abstract:
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The construction industry faces various challenges related to uncertainties in project bids and unstable pricing. These challenges include situations where uncertainties in bid documents can affect project pricing and performance. In order to resolve these uncertainties and clarify project requirements, risks and uncertainties within the document need to be identified early in the project life cycle. This study aims to rank the factors affecting project pricing. For this purpose, firstly, the parameters that have an impact on pricing are defined and then these factors are weighted by using Intuitionistic Fuzzy Analytic Hierarchy Process with Ordered Pairs.
The analysis of factors affecting construction pricing reveals some important insights. Environmental uncertainties and uncertainties in prices and labor costs are the most important factors influencing pricing, while past project experience is the least important factor. Overall, these findings shed light on the multifaceted nature of construction pricing, which is shaped by the complex interaction of environmental, economic and market factors.
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| Keywords:
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Pricing, Construction industry, Intuitionistic fuzzy sets, Analytic hierarchy process.
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| AMS Classification:
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03E72.
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| References:
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