Yazar "Pamucar, Dragan" seçeneğine göre listele

Listeleniyor 1 - 3 / 3
  • Küçük Resim Yok
    Öğe
    Determining Objective Characteristics of MCDM Methods under Uncertainty: An Exploration Study with Financial Data
    (Mdpi, 2022) Baydas, Mahmut; Pamucar, Dragan
    A major difficulty in comparing and even choosing MCDM methods is the uncertainty of information about the consistent and unique characteristics of the results produced. The objective information content of the final scores produced by MCDM methods and their relevance to real life can give us an important idea about them. In this study, first of all, seven MCDM methods with different methodologies were applied to evaluate companies' financial performance. Then, the obtained MCDM scores were compared using two different objective verification mechanisms. The first validation criterion is the relationship of a MCDM method to real-life rankings (share price). The second criterion is the standard deviation (SD) technique used to discover the objective information content of MCDM final scores. According to the results of this study, PROMETHEE and FUCA definitely outperform other methods in terms of both SD values and strength of correlation with reference real-life rankings. Also, FUCA is methodologically simpler than other methods. However, it produced nearly identical results as the sophisticated PROMETHEE method.
  • Küçük Resim Yok
    Öğe
    Exploring the specific capacity of different multi criteria decision making approaches under uncertainty using data from financial markets
    (Pergamon-Elsevier Science Ltd, 2022) Baydas, Mahmut; Elma, Orhan Emre; Pamucar, Dragan
    Even if the MCDM methods produce statistically significant and similar rankings in a given problem, they can present the best alternatives in a different order. Random selection of the best alternative can create a complexity for the decision maker in reaching the most suitable outcome in a scenario. It is extremely challenging to oversee what the capacity or capability strengths of the more than 100 MCDM methods are, based on the results they produce. This issue is still regarded as a paradox, as there is no approved criterion to compare MCDM methods under uncertainty, in the literature. This study is aimed to determine the capacity of MCDM methods by outputs rather than inputs, unlike the previous literature. Discussions in the recent literature points out that the capacity of a MCDM method that better fits real life problems can be higher. In this respect, share returns were regarded as a reference in comparing MCDM methods objectively by financial performance of companies in this study. A multi-criteria approach that consistently produced significantly higher correlations with share returns compared to other methods has been accepted as the most appropriate MCDM method in the framework of this research. The study was conducted on 23 companies in the BIST30 index, which lists the largest companies in Borsa Istanbul. 10 MCDM methods were compared according to their significance in producing a higher relationship with share returns. As a result, PROMETHEE and FUCA methods clearly shared the first place as the most efficient compared to other methods, which are TOPSIS, GRA, S-, WSA, SAW, COPRAS, MOORA and LINMAP.
  • Küçük Resim Yok
    Öğe
    A Novel Methodology for Prioritizing Zero-Carbon Measures for Sustainable Transport
    (Elsevier, 2021) Pamucar, Dragan; Deveci, Muhammet; Canitez, Fatih; Paksoy, Turan; Lukovac, Vesko
    Achieving a zero-carbon city requires a long-term strategic perspective. Transport emissions are a major source of carbon emissions, and cities grapple with reducing carbon emissions, and improving the air quality for their citizens. London's new transport strategy document, called Mayor's Transport Strategy 2018, aims to achieve a zero-carbon city by 2050 and set out many actions to facilitate this transition. However, London needs a prioritisation framework which would take into account the financial, environmental and social impacts of these actions. Considering the uncertainties around these actions, which has been now significantly more crucial during the COVID-19 pandemic, this study proposes a novel extension of Best-Worst Method (BWM) and extension of the TODIM (an acronym in Portuguese for Iterative Multi-Criteria Decision Making (MCDM)) method using D numbers. This TODIM-D based fuzzy MCDM approach provides a prioritisation framework for the actions associated with zero-carbon city policies set out in London's strategy document. According to the results of the proposed method, introducing zero-emission zones should be selected as the first initiative to implement. The prioritization of this initiative allows London to achieve a zero-carbon transport by having the greatest impact on the modal shift from cars to sustainable mobility modes with a lower operational and implementation cost as well as having greater public support. The proposed method used in this study can be transferred to other cities which aim to achieve a zero-carbon transport. (C) 2021 Institution of Chemical Engineers. Published by Elsevier B.V. All rights reserved.