Linguistic Information Based Selection Methodology for Building Certification

Deniz Uztürk (), Gülçin Büyüközkan (), A. Fahri Negüs () and M. Yaman Öztek ()
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Deniz Uztürk: Galatasaray University, Department of Business Administration
Gülçin Büyüközkan: Galatasaray University, Department of Industrial Engineering
A. Fahri Negüs: Galatasaray University, Department of Business Administration
M. Yaman Öztek: Galatasaray University, Department of Business Administration

Chapter Chapter 26 in Transactions on Engineering Technologies, 2019, pp 347-360 from Springer

Abstract: Abstract Decision-making is a process encountered in everyday life and is used for evaluating different alternatives in the light of various criteria. Unfortunately, in this process, the data are not always accurate enough to obtain definite and optimum results. The uncertainty of data can quickly increase as information from different sources increases and that lead decision makers to seek new approaches to reduce this uncertainty and create stable environments for decision-making. One of these approaches is linguistic decision making (LDM), where linguistic variables are used. The 2-Tuple linguistic model is an extension of these approaches. This study aims to propose a multi-criteria decision-making (MCDM) model with its 2-Tuple extension to overcome this imprecision on a selection problem. Moreover, in this study, the green building certification selection problem is applied to test the plausibility of the proposed methodology. Linguistic and multi-granular information obtained from various experts have been aggregated under uniform and meaningful form to choose the most appropriate building certification for Turkey.

Keywords: 2-Tuple linguistic model; Certification selection; Green building; Group decision making; MCDM; Multi-granular data; VIKOR (search for similar items in EconPapers)
Date: 2019
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-981-32-9531-5_26

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DOI: 10.1007/978-981-32-9531-5_26

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