Yazar "Pamucar, Dragan" seçeneğine göre listele

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    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, Dragan
    Overall 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.
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    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, Dragan
    Ensuring 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.
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    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, Dragan
    This 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.
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    Mapping the Evolution of Multi-Attributive Border Approximation Area Comparison (MABAC) Method: A Bibliometric Analysis
    (Regional Association for Security and crisis management, 2024) Demir, Gülay; Chatterjee, Prasenjit; Zakeri, Shervin; Pamucar, Dragan
    This paper presents a comprehensive bibliometric analysis of Multi-Attributive Border Approximation Area Comparison (MABAC) method using the Biblioshiny application of the bibliometrix package, R program and VOSviewer tools to provide a holistic view of the research landscape by identifying its evolution, major contributors and most influential research areas. The study, analyzing 264 articles from the Scopus database (January 2015 to September 2023), reveals China as the leading contributor, with India spearheading international collaboration. The most impactful publication, "The selection of transport and handling resources in logistics centres using MABAC," by Pamucar and Cirovic [2], boasts 537 citations. Notably, the "University of Defence in Belgrade" is a prominent institution in this domain. "Pamucar D" emerges as the most cited author. Key terms include "MABAC," "MABAC method," and "MCDM," commonly associated with MABAC method. The top three cited journals are "Expert Systems with Applications," "Decision Making: Applications in Management And Engineering," and "Symmetry." The study provides valuable insights for researchers, practitioners, and decision-makers interested in MABAC's applications and future developments in MCDM, contributing to ongoing discussions about its relevance. © 2024 Regional Association for Security and crisis management. All rights reserved.
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    Sensitivity analysis in multi-criteria decision making: A state-of-the-art research perspective using bibliometric analysis
    (Pergamon-Elsevier Science Ltd, 2024) Demir, Guelay; Chatterjee, Prasenjit; Pamucar, Dragan
    In the present era, the implementation of scientifically grounded Multi-Criteria Decision Making (MCDM) has emerged as a pivotal solution to diverse decision-making challenges across various domains. Although a sub-stantial body of exploratory, conceptual, and experimental studies exists, only 9.457% studies have incorporated sensitivity analyses to assess the robustness of MCDM methods. An exhaustive scientific exploration of sensitivity analysis within the scope of MCDM is thus lacking. This research aims to address this gap through Bibliometric Analysis while examining 1374 articles published between January 2000 and March 2023 from the Scopus database. Using RStudio (Biblioshiny), CiteSpace, and VOSviewer software, the study constructs a visual rep-resentation of the most prolific countries, institutions, and authors. Impressively, China takes the lead in article publications, while India excels in international collaboration. An extended TODIM multi-criteria group decision-making method for green supplier selection in an interval type-2 fuzzy environment, featured in the Journal of Environmental Management, emerges as the most cited paper with a total citation of 455. The study also identifies the top three most cited journals, namely Journal of Cleaner Production, Expert Systems With Applications, and Computers and Industrial Engineering. North China Electric Power University is the leading institute with the highest research outputs. Pamuc ?ar D is the most cited author, with 2594 citations and 39 articles, followed by Kahraman C and Zavadskas EK. This study sheds light on trends in scientific de-velopments and collaborations, providing a model for the application of sensitivity analysis in MCDM research and highlighting global trends. An understanding of the current state of sensitivity analysis research can assist researchers working in the entire domain of MCDM. Additionally, the visualization provides prescriptive data for future work and applications related to sensitivity analysis.
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    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, Dragan
    This 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.