Yazar "Yalcin, Galip Cihan" seçeneğine göre listele

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    An integrated neutrosophic Schweizer-Sklar-based model for evaluating economic activities in organized industrial zones
    (Pergamon-Elsevier Science Ltd, 2024) Kara, Karahan; Yalcin, Galip Cihan; Simic, Vladimir; Polat, Mustafa; Pamucar, Dragan
    Organized industrial zones (OIZs) are specialized areas where industrial activities are concentrated, and various economic activities take place collectively. Within OIZs, diverse economic activities coexist, forming shared industrial spaces. However, different regions tend to cluster different economic activities within OIZs. Given the significance of determining suitable economic activities for OIZs, developing a model for this decision problem, and testing its practical applicability is crucial. This research presents a multi-criteria decision-making approach to develop an economic activity selection model for OIZs. This model is based on type-2 neutrosophic numbers (T2NNs). Furthermore, two T2NNs aggregation operators, namely T2NN Schweizer-Sklar weighted arithmetic mean and T2NN Schweizer-Sklar weighted geometric mean aggregation operators, are developed based on the Schweizer-Sklar operations for use in determining decision-maker weights and ranking economic activities. The T2NN-based criteria importance through intercriteria correlation (CRITIC) method is employed for criterion weighting. An algorithm specific to the proposed model is devised for ranking economic activities. As a case study, this algorithm is applied to the Artvin-Arhavi OIZ, which is in the process of establishment in Turkey. Sensitivity and comparative analyses are conducted to assess the robustness of the developed aggregation operators and the model. In the case study findings, the most significant criterion is identified as investment risk, and forestry, logging, and related service activities are determined as the best economic activity. This research contributes to the field by introducing the model and novel aggregation operator for the selection of economic activities in OIZs.
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    An intuitionistic fuzzy-based model for performance evaluation of EcoPorts
    (Pergamon-Elsevier Science Ltd, 2023) Yalcin, Galip Cihan; Kara, Karahan; Toygar, Arda; Simic, Vladimir; Pamucar, Dragan; Köleoğlu, Nilay
    The EcoPort performance level serves as a basic indicator to determine the environmental status of a port and its achievement of certification standards. The European Sea Ports Organization has defined ten essential EcoPort criteria that contribute significantly to the assessment of EcoPort performance. The primary motivation for this study is to determine the importance of the criteria from the perspective of academics and chief officers, as well as to evaluate the EcoPort performance of six port authorities that comply with three basic certification standards for environmental management systems. The research methodology and application are conducted in four phases. In the first phase, experts, criteria, and alternative ports are identified. In the second phase, the importance levels of experts are determined using neutrosophic sets, while the criteria are weighted using the intuitionistic fuzzy weighting averaging operator. In the third phase, the alternative ranking order method ac-counting for two-step normalization (AROMAN) based on the intuitionistic fuzzy sets is introduced to evaluate the EcoPort performance of the ports. In the fourth phase, the results are supported by sensitivity analysis scenarios. The research results identified air pollution as the most critical criterion, while the Valencia Port Authority secured the highest rank in terms of EcoPort performance. Ultimately, this research contributes to the literature by developing and applying the new IF-AROMAN method for EcoPort performance evaluation.
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    DETERMINATION OF LOGISTICS INNOVATION PERFORMANCE INDEX WITH ENTROPY AND COMBINED COMPROMISE SOLUTION TECHNIQUES
    (Symmetrion, 2022) Kara, Karahan; Yalcin, Galip Cihan; Kaygisiz, Esra Gokcen
    Logistics innovation performance is the resultant force of countries' logistics and innovation performance. Indices show the logistics performance and innovation performance of countries. However, the countries' logistics innovation performance index (LIPI) has not yet developed. The primary purpose of this research is to create the LIPI of developing countries for 2021. The global innovation index (GII) and Agility Emerging Market Logistics Index (AEMLI) scores of 48 developing countries were used. Ten criteria of the research have been used. Three criteria (domestic logistics opportunities, international logistics opportunities, business fundamentals) are from AEMLI, and seven criteria (institutions, human capital, research, infrastructure, market sophistication, business sophistication, knowledge and technology outputs, and creative outputs) are from GII. The criteria are weighted using the Entropy technique. The Combined Compromise Solution (CoCoSo) technique is used to determine LIPI scores. As a result of the research, 2021 LIPI scores and rankings of developing countries have been created. Both AEMLI and GII scores have been compared with LIPI scores. In comparison, symmetric and asymmetric rank distributions are presented. In addition, suggestions have been shown to developing countries and researchers based on the implications.
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    Developing a hybrid methodology for green-based supplier selection: Application in the automotive industry
    (Pergamon-Elsevier Science Ltd, 2024) Kara, Karahan; Acar, Avni Zafer; Polat, Mustafa; Onden, Ismail; Yalcin, Galip Cihan
    The green performance values of businesses are of great importance in terms of sustainability, which includes long-term economic, social, and environmental effects. Thus, today, enterprises and managers are increasingly interested in this issue, and related topics, including supplier selection, have been inserted into decision-making procedures. However, how to predict the effects of green performance criteria, which represent environmental sustainability, on social and economic sustainability remains unclear. In this regard, the main purpose of this research is to develop a supplier selection methodology considering green performance criteria by applying multiple regression analysis and the Evidential Fuzzy Multi-Criteria Decision Making (F-MCDM) method based on Dempster-Shafer Theory (DST), which are both powerful methods in statistical analysis and decision-making under uncertainty. In the first phase of the research, variables that significantly affect green performance have been determined by testing the eight generated hypotheses with multiple regression analysis. Then, the best supplier was determined using those green supplier selection criteria in the Evidential F-MCDM method. Since using environmentally hazardous paints in the production process continues, the automobile paint production sector has been chosen as the application area of this green-based supplier selection methodology. In this respect, green dynamic capacity, green purchasing, eco-design, investment recovery, and green product innovation variables have been inserted into the Evidential F-MCDM method as the determinant variables of green performance. This research reveals that integrating multiple regression and Evidential F-MCDM methods can be a hybrid methodology in supplier selection. Thus, a different perspective is introduced into the green supplier selection decision-making process by considering the effects of criteria in the MCDM model on green performance. This innovation enhances the criteria determination and selection processes in classical MCDM approaches. In addition, green dynamic capacity is the most critical criterion in supplier selection based on their green performance, especially in the scope of this research.
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    Enhancing decision support system for finished vehicle logistics service provider selection through a single-valued neutrosophic Dombi Bonferroni-based model
    (Pergamon-Elsevier Science Ltd, 2024) Kara, Karahan; Yalcin, Galip Cihan; Gurol, Pinar; Simic, Vladimir; Pamucar, Dragan
    Finished vehicle logistics (FVL) activities are executed through agreements with service provider firms. Vehicle manufacturers make efforts to select the most successful FVL service provider. The motivation for this research lies in developing and demonstrating the application of a decision support system for FVL service provider selection. Within this scope, it is necessary to develop a decision model that includes both quantitative and qualitative criteria. Considering the decision process as a group decision-making process allows for simultaneous consideration of different perspectives on the decision. Single-valued neutrosophic (SVN) sets are used for expert evaluations. The SVN weighted Dombi Bonferroni mean aggregation operator is employed for criteria weighting. The SVN-alternative ranking using two-step logarithmic normalization (ARLON) method is developed for ranking FVL service providers. The feasibility of the SVN-Dombi Bonferroni-ARLON hybrid algorithm is supported by the case study application. It is concluded that supply chain and logistics managers hold greater importance in FVL service provider selection, with the number of ships being the most critical selection criterion. The robustness of the proposed hybrid method for FVL service provider selection is supported by sensitivity analyses, while its consistency is supported by comparative analyses.
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    Exploring the adoption of the metaverse and chat generative pre-trained transformer: A single-valued neutrosophic Dombi Bonferroni-based method for the selection of software development strategies
    (Pergamon-Elsevier Science Ltd, 2024) Onden, Abdullah; Kara, Karahan; Onden, Ismail; Yalcin, Galip Cihan; Simic, Vladimir; Pamucar, Dragan
    The contemporary era has witnessed remarkable developments that seek to transform and reshape traditional software development methodologies. Notably, artificial intelligence (AI) supported software development as well as software development in virtual reality environments have gained considerable prominence. This article introduces software development strategies to examine how software developers and companies respond to this transformation. Also, an advanced decision model is developed using the alternative ranking order method accounting for two-step normalization (AROMAN) method and further analyzed with the single-valued neutrosophic set-based AROMAN technique. The single-valued neutrosophic weighted Dombi Bonferroni operator is employed in the analysis process. This research offers two case studies investigating the preferences of developers and managers in software development strategies. The first case study examines the preferences of developers, while the second focuses on the preferences of managers. In both case studies, three fundamental software development methods are presented. These include the traditional developers approach, AI-supported developers approach, and mixed reality and AI-supported developers approach. These methods are ranked based on expert opinions concerning 10 criteria that influence the software development process. In both case studies, output quality is identified as the most influential criterion. From the perspective of software development methods, in both case studies, the mixed reality and AI-supported developers approach is identified as the most effective. Recommendations are provided for developers and managers. The findings also have significant implications for guiding developers and managers in making informed decisions and optimizing software development practices to align with the evolving AI and virtual reality landscape.
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    Supplier selection of companies providing micro mobility service under type-2 neutrosophic number based decision making model
    (Pergamon-Elsevier Science Ltd, 2024) Onden, Ismail; Deveci, Muhammet; Kara, Karahan; Yalcin, Galip Cihan; Onden, Abdullah; Eker, Mert; Hasseb, Mouad
    Environmental approaches play an active role in the production platform as well as in the supply chain. Studies that deal with supplier selection problems in the supply chain with a green focus have recently intensified. In this research, the supplier selection problem of companies providing last mile service, which is seen as the last step of transportation, is handled with a green focus. The supplier selection problem of these companies is differentiated according to strategic and non -strategic product groups. In this study, a green -oriented supplier selection proposal is presented for both the strategic product group and the non -strategic product group. The supplier selection problem is accepted as a multi criteria decision making problem (MCDM). Thus, the type -2 neutrosophic numbers (T2NNs) - based CRiteria Importance Through Intercriteria Correlation (CRITIC) - based Multi -Attributive Border Approximation Area Comparison (MABAC) hybrid model is applied to evaluate the green -oriented supplier. The motivation of the study is to determine the best alternative supplier type for strategic and non -strategic products groups. In this context, two cases are created, ten criteria are selected, and three supplier types are determined. Supplier types are as follows: (i) Classical suppliers, (ii) Hybrid -Classical to green centric suppliers, and (iii) Start -Ups & green centric suppliers. To devise a solution for addressing the research problem, the selection of the optimal green supplier type was accomplished through a recommended T2NNCRITIC-MABAC hybrid model. Accordingly, for both strategic and non -strategic product groups, micromobility service providers identified Hybrid -Classical to Green Centric Suppliers as the most suitable green supplier type. In addition, the findings are strengthened by creating twenty-two sensitivity analysis scenarios. In conclusion, the T2NN-CRITIC-MABAC hybrid method introduced in this study represents a methodologically diverse, fuzzy logic -based approach with practical implications for supplier selection in the micro mobility services sector. Its application and empirical testing contribute to the literature and provide valuable insights for decision -makers in the industry.
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    Sustainable brand logo selection using an AI-Supported PF-WENSLO-ARLON hybrid method
    (Pergamon-Elsevier Science Ltd, 2025) Kara, Karahan; Ergin, Elif Akagun; Yalcin, Galip Cihan; Celik, Tugce; Deveci, Muhammet; Kadry, Seifedine
    Brands use logos to reflect their identities and convey their company character to target customers. Logos not only represent brand value but also provide various information about brands. Companies aiming to emphasize sustainable brand value also seek to showcase this aspect in their logos. Therefore, sustainable brand design and development are preferred. The focus of this research is on sustainable brand development through Artificial Intelligence-supported logo design and developing a decision support system for selecting the best logo among Artificial Intelligence-generated logos. In this study, Artificial Intelligence-supported logo design is explained, and the Multi Attribute Group Decision Making approach is adopted for identifying the best logo among the obtained logos. The Picture Fuzzy - Weights by Envelope and Slope - Alternative Ranking using Two-Step Logarithmic Normalization hybrid method is proposed for logo decision-making, combining the Weights by Envelope and Slope criterion weighting method using picture fuzzy sets with Alternative Ranking using Two-Step Logarithmic Normalization alternative ranking methods. Additionally, the Picture Fuzzy Yager Weighted Average aggregation operator based on Yager t-norm and t-conorm operations is employed. The steps of the hybrid method are outlined, and its algorithm is formulated. To test the applicability and robustness of the algorithm, sustainable logo design for an architectural firm is developed and executed as a real-case study. The research concludes that Artificial Intelligence-supported sustainable logo design can be achieved, and the hybrid method can support determining the best logo based on expert opinions. Based on the research findings, the hybrid method is recommended for sustainable logo design and selection.
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    The alternative ranking using two-step logarithmic normalization method for benchmarking the supply chain performance of countries
    (Elsevier Science Inc, 2024) Kara, Karahan; Yalcin, Galip Cihan; Simic, Vladimir; Baysal, Zeynep; Pamucar, Dragan
    Supply chain performance signifies the success of countries in material and information flow within international trade activities. Countries strive to enhance their supply chain performance by increasing connectivity with partner countries and reducing dwell times at logistics hubs. In this study, the supply chain performance of countries based on international tracking indicators is examined using a multi -criteria decision -making approach. The paper encompasses two primary objectives. The first objective is the determination of the supply chain performance of countries. The second one is the development of a novel alternative ranking method. The study employs 10 supply chain key performance indicators as criteria and utilizes data from 72 countries. The data is sourced from logistics performance index reports published by the World Bank. The modified preference selection index (MPSI) is employed for criterion weighting. For the ranking of countries, a novel alternative ranking method named the Alternative Ranking using two-step LOgarithmic Normalization (ARLON) method is proposed. Through the implementation of the MPSI-ARLON hybrid method, supply chain performance and rankings of countries are computed. The findings are supported by sensitivity and comparative analyses. Furthermore, robustness tests are conducted for the ARLON method. The research concludes by presenting implications and managerial insights derived from the ARLON method.
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    The MEREC-AROMAN method for determining sustainable competitiveness levels: A case study for Turkey
    (Elsevier Science Inc, 2024) Kara, Karahan; Yalcin, Galip Cihan; Acar, Avni Zafer; Simic, Vladimir; Konya, Serkan; Pamucar, Dragan
    Sustainable competitiveness represents a multifaceted phenomenon encompassing economic, environmental, and social dimensions. Macro-level competitiveness strategies are formulated based on the diverse capitals possessed by individual countries, thereby giving rise to variations in the sustainable competitiveness strategies of each country. This research introduces a novel hybrid method called the method based on the removal effects of criteria (MEREC)-alternative ranking order method accounting for two-step normalization (AROMAN) for determining sustainable competitiveness levels. This study aims to assess Turkey's sustainable competitiveness position vis -`a-vis its border neighbors. Natural capital, resource efficiency and intensity, social capital, intellectual capital and innovation, economic sustainability, and governance efficiency are the Global Sustainable Competitiveness Index (GSCI) indicators. The GSCI indicators are employed as criteria for determining the sustainable competitiveness scores of countries. The findings show that the resource efficiency and intensity criterion has the highest level of significance. The sustainable competitiveness level of Turkey to its neighboring countries is elucidated based on the results. Recommendations are formulated for the development of strategies aimed at determining Turkey's position in the race for sustainable competitiveness. The introduced MEREC-AROMAN can be utilized to provide rules of thumb for other countries to improve their sustainable competitiveness. This research offers decision support for the formulation of countries' sustainable competitiveness strategies and policies, fostering awareness in the planning and establishment of regional collaborations among nations.
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    Vehicle routing software selection for last mile delivery companies using Fermatean fuzzy-based model
    (Pergamon-Elsevier Science Ltd, 2024) Kara, Karahan; Yalcin, Galip Cihan; Simic, Vladimir; Gurol, Pinar; Pamucar, Dragan
    Vehicle routing software (VRS) is utilized by last mile delivery (LMD) companies for route optimization. The problem of VRS selection is of paramount importance for LMD companies. In this research, a VRS selection model tailored to LMD companies is developed and proposed. This model is based on Fermatean fuzzy sets (FFS). The FFS-preference selection index (PSI) method is proposed for weighting the criteria. The FFS-alternative ranking order method accounting for two-step normalization (AROMAN) method is defined for ranking the VRS alternatives. This hybrid approach, developed as FFS-PSI-AROMAN, incorporates the FFYWA operator based on Yager t-norm and t-conorm operations as the aggregation operator to enhance the strength of aggregation operations. Additionally, an algorithm has been developed for the model. The developed model is applied through a real-life case study conducted in an LMD company operating in Turkey. An expert group is formed, criteria are defined, alternative VRS options are identified, and the proposed algorithm is employed to make the optimal VRS selection. Sensitivity analysis scenarios are created, and robustness tests are conducted to evaluate the model's reliability. Comprehensive implications for both the research and managerial insights are provided, along with recommendations for future research endeavors.