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Öğe A hybrid framework for assessing Pakistani commercial bank performance using multi-criteria decision-making(Springer, 2025) Isik, Ozcan; Shabir, Mohsin; Demir, Gulay; Puska, Adis; Pamucar, DraganOverall bank performance in a particular year or period is important to all banking industry stakeholders, as it indicates their success or failure relative to predetermined targets. Due to conflicting criteria and uncertainties, assessing bank performance is a complicated decision-making problem. The current paper proposes the Fuzzy Level Based Weight Assessment (F-LBWA), the Fuzzy Logarithm Methodology of Additive Weights (F-LMAW), and the Measurement Alternatives and Ranking according to the Compromise Solution (MARCOS) combination as a practical and robust decision-making tool to cope with many complex ambiguities. In the first phase, the suggested hybrid Multi-Criteria Decision-Making (MCDM) approach estimates the weight coefficients of the performance criteria with the aid of a combined version of the F-LBWA and F-LMAW methods. In the second phase, the MARCOS method determines the ranking performance of the decision alternatives. The introduced model is tested and validated on a case study assessing publicly traded bank performance in Pakistan. The findings obtained from the sensitivity analysis revealed that the presented F-LBWA-F-LMAW-MARCOS approach produces consistent solutions and is a reliable and effective procedure in rational decision-making.Öğe A systematic investigation of multi-attributive border approximation area comparison approach with Gaussian membership function for optimizing water quality(Springer, 2024) Yasin, Yasir; Demir, Gulay; Riaz, Muhammad; Aslam, Muhammad; Pamucar, DraganEnsuring the safety of drinking water is of utmost importance for the well-being of the general population. This study presents a new framework to assist specialists in selecting and assessing water samples, dealing with the urgent requirement for accurate and consistent analysis of water quality. We utilize the Gaussian Membership Function (GMF) to handle the inherent uncertainty in a dataset of 3276 samples obtained from Kaggle. The criteria importance through the inter-criteria correlation (CRITIC) technique is employed to evaluate and rank the significance of several criteria. We use the weighted aggregate sum product assessment (WASPAS) and multi-attributive border approximation area comparison (MABAC) methods to rank the water samples. Each technique has a comprehensive pseudocode to support it, which offers clear instructions for putting it into practice on various datasets. A comparative analysis confirms the efficacy and computational efficiency of these methods, showcasing their ability to improve assessments of water quality greatly. This research not only creates a strong and practical foundation for decision-making in water quality analysis but also adds to the progress of techniques. The acquired insights provide useful guidance for future research, potentially impacting the establishment of optimal methods in the evaluation of water quality.Öğe Artificial Intelligence in Aviation Safety: Systematic Review and Biometric Analysis(Springernature, 2024) Demir, Gulay; Moslem, Sarbast; Duleba, SzabolcsThis study aims to offer aviation safety researchers, practitioners, and decision-makers a comprehensive exploration of integrating advanced technologies, such as artificial intelligence and machine learning, to inform and fortify future safety strategies. Focusing on systematic and bibliometric perspectives, the paper reviewed 224 articles in the Scopus database from 2004 to 2024 (January). Key findings highlight China's notable contributions to aviation safety research, underscoring its leadership in international collaboration. The techniques employed encompass machine learning, time series models, deep learning, AI, neurophysiological modeling, and optimization algorithms. The analysis discerns prominent research trends, including aviation accident analysis, pilot behavior, aviation safety measures, and endeavors to enhance safety standards. The aviation industry's steadfast commitment to safety, efficiency, and technological innovation is evident. By uncovering the main structures, foci, and trends in aviation safety research, this study equips researchers and practitioners with crucial insights into ongoing endeavors and potential future developments, fostering a more profound understanding of aviation safety.Öğe Artificial Intelligence in Aviation Safety: Systematic Review and Biometric Analysis ( vol , 17 ,279 , 2024)(Springernature, 2024) Demir, Gulay; Moslem, Sarbast; Duleba, Szabolcs[No abstract available]Öğe Efficiency of Investment Incentives in Reducing Regional Development Disparities in Türkiye(Sosyoekonomi Soc, 2024) Dundar, Sinan; Demir, Gulay; Noyan-Yalman, Ilkay; Kosaroglu, Serife Merve; Yildiz, Selcuk YasinThis study aims to determine to what extent the investment incentive system implemented in Turkiye effectively reduces regional development disparities. For this purpose, more than 100,000 investment incentive certificates issued between 2001-2022 are examined. The Logarithm Methodology of Additive Weights (LMAW) determines the criteria's importance and ranks the provinces' investment performances. The results obtained indicate that investment incentive applications cannot provide sufficient effectiveness in reducing regional development disparities. In this respect, there is a severe need for revision in the incentive policies currently implemented.Öğe How will I break AI? Post-Luddism in the AI age: Fuzzy MCDM synergy(Elsevier Science Inc, 2024) Darlcl, Sefer; Riaz, Muhammad; Demir, Gulay; Gencer, Zekiye Tamer; Pamucar, DraganThis study proposes a fuzzy multi-criteria model to assess the risk of unemployment among professionals in the communication sector in Turkey, prompted by the rapid development and evolution of artificial intelligence (AI) technologies. The method integrates Fuzzy The Decision Making Trial and Evaluation Laboratory (F-DEMATEL) and Fuzzy Logarithm Methodology of Additive Weights (F-LMAW) procedures. Data were collected from 20 experts representing professions such as public relations, advertising, journalism, and design through a 12-question survey. In the analysis, the F-DEMATEL procedure was initially employed to determine attitudes towards AI technologies, followed by the application of the F-LMAW procedure to assess the magnitude of AI's impact on occupational groups. Findings reveal a nuanced stance: while professionals acknowledge the necessity of AI for their work, they are unwilling to accept unemployment due to more advanced AI. This newly identified structure, termed Post-Luddism, highlights concerns over technological unemployment, particularly pronounced in professions like journalism where job prospects are limited and creative thinking is paramount. In other communication fields, the intensive use of technology mitigates fears of AI harm. However, even in journalism, there exists a propensity to perceive AI as detrimental. These insights shed light on communication professionals' apprehensions and attitudes towards AI's effects. Policymakers and stakeholders can leverage this understanding to formulate strategic measures, considering the divergent perspectives among professional groups regarding AI, towards mitigating potential unemployment risks and fostering AI-adaptive strategies.Öğe Multi-criteria decision making in evaluation of open government data indicators: An application in G20 countries(Amer Inst Mathematical Sciences-Aims, 2023) Demir, Gulay; Riaz, Muhammad; Almalki, YahyaOpen data has a large means of identifying commonly reachable information on different platforms. One of the open data sources is open government data. The goals of open governments are about building transparency, accountability and participation to strengthen governance and inform citizens. The aim of this study is twofold: (i) to propose a reliable decision-making tool for dealing with real-life problems and (ii) to demonstrate the practicality of the proposed model through a case study of its ranking with an open government data indicator for G20 countries. This study proposes a multi-criteria methodology that evaluates open data management systems used in e-government development. First, a set of evaluation criteria is established that cover the indicators used in the Global Open Data Index. Second, weights from the Logarithm Methodology of Additive Weights (LMAW) and Logarithmic Percentage Change-driven Objective Weighting (LOPCOW) methods were combined with the Bayesian approach to determine the weights of these criteria. Finally, the Weighted Aggregated Sum Product Assessment (WASPAS) method was used to obtain the ranking results. The novelties of the study lie in the combination of objective and subjective weighting methods, both in determining the ranking of G20 countries with open government data indicators and in deciding the importance levels of the criteria used. The air quality and procurement criteria are the top two criteria, with weights of 0,1378 and 0,1254 respectively. The findings also show that Australia is the best performer, while the United Kingdom is the second best performing. Comprehensive sensitivity analysis verifies the validity, robustness and effectiveness of the proposed framework. According to research findings and analysis, the methodology applied has the potential to assist policymakers and decision-makers in the process of modernization of existing public services in terms of open data and the opportunities it presents.Öğe Selection of optimum renewable energy sources under smart city environment for energy management and planning: An eclectic decision(Regional Association for Security and crisis management, 2023) Bhowmik, Chiranjib; Khare, Manjeet; Mewada, Bhavesh; Chatterjee, Prasenjit; Demir, GulayThe purpose of this paper is to present a decision support framework, able to assess and optimize the energy use in smart cities. This paper has taken a sincere endeavour to develop an innovative integrated analytical framework as a benchmark to understand to what extent the energy has been consumed in smart city spectrum. Initially five sectors (construction, water management, transport, waste treatment and public services) of smart city and their corresponding sub-factors are identified based on industry, academia partnership. Once the data were gathered, those were analysed using various statistical tools. This research is useful for the policymakers, executive people, especially those are working or involved in smart city development projects. The developed framework helps to identify the significant energy consumption sector and also suggest the suitable green energy alternatives for developing a cleaner and sustainable future. As this study discusses the various parameters related to smart city energy consumption sector in western India, it will have a huge practical potential on the proposed operational smart cities in India. Literature has witnessed minimum number of studies have been carried out on this proposed framework and that could improve the wellbeing of the people living in the cities. Copyright © 2023 Regional Association for Security and crisis management and European centre for operational research. All rights reserved.Öğe Toward Sustainable Urban Mobility by Using Fuzzy-FUCOM and Fuzzy-CoCoSo Methods: The Case of the SUMP Podgorica(Mdpi, 2022) Demir, Gulay; Damjanovic, Milanko; Matovic, Bosko; Vujadinovic, RadojeSustainable urban mobility plans (SUMPs) have become increasingly popular in cities with environmental problems to reduce pollution, often caused by urban transportation. Therefore, this study aims to provide a practical framework for the selection decisions of final measures and policies to be carried out to achieve SUMP workspace goals using a fuzzy multi-criteria decision-making (MCDM) methodology. Alternatives are created with the strategic pillar, which was first adopted by the Podgorica city council. With the measurements in this pillar, the main criteria and the recommended measures for these measures create sub-criteria. Secondly, a Fuzzy Full Consistency Method (F-FUCOM) was used to determine the weights of the main and sub-criteria. The Fuzzy Combined Compromise Solution (F-CoCoSo) method was then applied to rank the alternatives. The implementation and assurance of the SUMP and establishing a system for regular data collection, monitoring and evaluation of selected mobility indicators were decided as the most important main and sub-criteria with weights of 0.286 and 0.1079, respectively. The findings suggest that the comprehensive planning for sustainable urban mobility alternative is first and the valorization of cycling potential alternative is second. A comprehensive sensitivity analysis confirms the validity, robustness, and effectiveness of the proposed framework. The applied methodology has the potential to assist decision makers in the process of developing SUMPs.Öğe Understanding twitter in crisis: a roadmap for public sector decision makers with multi-criteria decision making(Springer, 2025) Tamer, Zekiye; Demir, Gulay; Darici, Sefer; Pamucar, DraganThis study was developed to emphasize the critical role of social media in large-scale crises and the importance of effective information flow management. By analyzing how the Twitter platform (now X) can be utilized in crisis management, this paper presents an integrated framework that combines Multi-Criteria Decision-Making (MCDM) methods. The Improved Entropy technique is employed to prioritize classified tweets, while the Compromise Ranking of Alternatives from Distance to Ideal Solution (CRADIS) approach is used to evaluate the significance of crisis days. To validate the applicability and consistency of the proposed approach, a case study was conducted using tweets from the official Twitter account of the Disaster and Emergency Management Authority (AFAD) related to the earthquake that occurred in Turkey on February 6, 2023. The findings reveal that the Improved Entropy method identifies calls for help as the highest priority category in crisis response. CRADIS results further highlight that the second day of the disaster is the most critical, as it is the period when the scope of the crisis becomes clearer and coordination efforts are most intense. Comprehensive sensitivity analyses confirm that the proposed unified MCDM framework is both reliable and consistent. This study underscores the importance of timely and accurate information dissemination through social media in crisis management and offers a decision-support model that facilitates flexible and rational decision-making for authorities. This model can guide the development of more effective response strategies in future crisis scenarios.Öğe Wind farm site selection using geographic information system and fuzzy decision making model(Pergamon-Elsevier Science Ltd, 2024) Demir, Gulay; Riaz, Muhammad; Deveci, MuhammetAs the demand for renewable energy sources increases, finding the right places to install wind turbines becomes more and more important. The goal of this research is to create and implement a technique that uses geographic information system (GIS) technology to discover appropriate wind farm locations utilizing multi-criteria decision-making (MCDM) approaches. The complexity of this decision-making process, which includes multiple criteria and uncertainty, requires the use of advanced techniques. Fuzzy MCDM methods provide a framework for evaluating and prioritizing potential wind farm sites, taking into account subjective judgments and linguistic terms. In this article, Fuzzy Stepwise Weight Evaluation Ratio Analysis (F-SWARA) is preferred for prioritizing and ranking the criteria in the wind farm installation, while Fuzzy Measurement Alternatives and Ranking by Compromise Solution (F-MARCOS) are used to determine the most suitable location for the wind farm. A database of alternatives and criteria was created using GIS, which was converted into a fuzzy decision matrix via triangular fuzzy numbers. In order to make this evaluation, Sivas province, located in the middle of Turkey, was chosen as the study area. Results obtained show that 36,5% of the whole study area is very suitable for wind farm, and G & uuml;r & uuml;n and Kangal districts are suitable for wind farm. According to the result of F-SWARA method used to evaluate the criteria, wind speed is the most important criteria with a weight of 0,45039. According to the F-MARCOS method used for wind farm site selection, Ulas , district was determined the most suitable location. Furthermore, a sensitivity analysis was performed to test the robustness of the proposed methodology and the results revealed that the proposed integrated MCDM framework is feasible.
