Yazar "Simic, Vladimir" seçeneğine göre listele

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    A neutrosophic WENSLO-ARLON model for measuring sustainable brand equity performance
    (Elsevier Science Inc, 2024) Kara, Karahan; Yalcin, Galip Cihan; Ergin, Elif Akagun; Simic, Vladimir; Pamucar, Dragan
    Sustainable brand equity denotes the perceived brand equity by consumers, influenced by companies' nonfinancial and environmental practices. To cultivate sustainable brand equity, corporations undertake green initiatives and engage in social responsibility endeavors, thereby communicating environmentally oriented messages to consumers. Companies feel the necessity to establish a competitive position in sustainability relative to their counterparts. Hence, the primary objective of this research is to conduct an inquiry aimed at identifying sustainable brand equity to meet this exigency of companies. In this context, the motivation of this study lies in treating the calculation of sustainable brand equity as a decision-making process and developing a decision support system for this purpose. The proposed decision support system for determining sustainable brand equity levels in this research has three fundamental inputsss: experts, criteria, and brands. The impact levels of experts on the decision-making process are quantified utilizing type-2 neutrosophic number (T2NN) sets. The weights of criteria are ascertained employing the weight by envelope and slope (WENSLO) method extended with T2NN sets. The ranking of sustainable brand equities is established through the innovative T2NN-based alternative ranking using two-step logarithmic normalization (ARLON) method. These methodologies are amalgamated, and the T2NN-WENSLO-ARLON hybrid model is posited as a decision support system for evaluating sustainable brand equity performance. An algorithm for T2NN-WENSLO-ARLON is formulated and elucidated alongside a case study focusing on companies operating in the cosmetics sector in Turkey. The case study identifies the green product leadership criterion as the most influential factor in determining sustainable brand equity. Furthermore, the cosmetic company Misbah & ccedil;e Inc. is identified as the brand with the highest sustainable brand equity. Sensitivity and comparative analyses are conducted to ascertain the robustness of the results and the decision model. All scenario outcomes bolster the decision model. The research provides comprehensive insights into both the developed tool for calculating sustainable brand equity and develops implications for the cosmetics industry.
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    A picture fuzzy CIMAS-ARTASI model for website performance analysis in human resource management
    (Elsevier, 2024) Kara, Karahan; Yalcin, Galip Cihan; Kaygisiz, Esra Gokcen; Simic, Vladimir; Ornek, Ali Sahin; Pamucar, Dragan
    The central emphasis of human resource management resides in the precise delineation of job responsibilities, engaging in systematic inquiry to identify well-suited candidates, and discerningly electing the most qualified individual from the pool whose qualifications align with the job description. The selection of a well-suited candidate is dependent on the creation of an appropriate candidate pool. Digital platforms are preferred over traditional approaches to reach human resources. The main objective of this research is to identify the most suitable digital platform for posting job advertisements based on website performance. The multiple-attribute group decision-making approach is adopted in this research, considering both qualitative and quantitative criteria. A decision support system for website selection is developed, where expert importance levels are calculated based on picture fuzzy sets (PFS). The weight levels of criteria are determined using the introduced PFS-based criteria importance assessment (CIMAS) method. The ranking of websites is calculated using the proposed PFS-based alternative ranking technique based on adaptive standardized intervals (ARTASI) method. These methods are hybridized into the PFS-CIMAS-ARTASI model. Additionally, an algorithm for this hybrid model is developed. A case study is conducted to demonstrate the applicability of the PFS-CIMAS-ARTASI hybrid model for website performance calculations. Robustness tests based on various sensitivity analysis scenarios are performed. The research results indicate that PFS-CIMAS-ARTASI is both applicable and robust. Comprehensive managerial implications are presented and elaborated on.
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    A single-valued neutrosophic CIMAS-CRITIC-RBNAR decision support model for the financial performance analysis: A study of technology companies
    (Elsevier Science Inc, 2024) Kara, Karahan; Yalcin, Galip Cihan; Cetinkaya, Asli; Simic, Vladimir; Pamucar, Dragan
    Financial performance stands as a fundamental performance indicator that reflects companies' current financial conditions, providing information to investors and stakeholders about companies' financial well-being. In this research, a decision support system is developed for identifying the financial performance of companies traded on stock exchanges. This decision support system is based on a multicriteria decision -making (MCDM) approach and neutrosophic logic. The research introduces a novel method for calculating and ranking financial performance, using financial ratio indicators as selection criteria. The importance levels of financial ratio indicators are weighted through two different approaches. In the first approach, expert opinions and criteria importance assessment (CIMAS)-based on single -valued neutrosophic (SVN) sets are utilized for calculation. In the second approach, criteria importance through intercriteria correlation (CRITIC) -based on reference -based normalization processes is employed for criteria weighting. Subsequently, the results of the two criterion weightings are combined to calculate the final criterion weights. The SVN reference -based normalization alternative ranking (RBNAR) method is presented for ranking companies based on their financial performance. Thus, SVN-CIMASCRITIC-RBNAR is developed and its algorithm is presented. The novel hybrid decision support model is applied to a case study of technology companies traded on the Borsa Istanbul. The research results support the applicability of the SVN-CIMAS-CRITIC-RBNAR hybrid method. The results of the case study and sensitivity analyses affirm the applicability and robustness of the SVN-CIMAS-CRITIC-RBNAR hybrid model. The research provides detailed implications and insights for financial managers.
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    A single-valued neutrosophic-based methodology for selecting warehouse management software in sustainable logistics systems
    (Pergamon-Elsevier Science Ltd, 2024) Kara, Karahan; Yalcin, Galip Cihan; Simic, Vladimir; Onden, Ismail; Edinsel, Sercan; Bacanin, Nebojsa
    Warehouse operations cover activities that must be carried out systematically. Warehouse management systems (WMS) are needed for successful warehouse management. With digitalization, alternative software programs for WMS have increased. In this study, the selection of the WMS software program for the general warehouse type is discussed. The main motivation of the research is to develop a suitable alternative selection methodology based on criteria for warehouse managers. The research is carried out in several stages. In the first stage, the software selection criteria are determined based on the literature review. In the second stage, the criteria are weighted with the criteria importance through the intercriteria correlation (CRITIC) method based on single-valued neutrosophic sets (SVNSs). In the third stage, alternatives for WMS software are ranked with the technique for order preference by similarity to an ideal solution (TOPSIS) based on SVNSs. Three decision-makers, four al-ternatives, and eight criteria are used in the study. The empirical research is conducted on a warehouse providing general storage services in Turkey. In addition, the sensitivity analyses are performed and the results are compared. According to the research findings, the most valuable criterion in WMS software selection is deter-mined as ease of use. As a result of the research, suggestions are developed for WMS software manufacturers, warehouse managers, and researchers. The novelty of this research is that WMS selection is applied for the first time using multi-criteria decision-making methods.
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    A spherical fuzzy-based DIBR II-AROMAN model for sustainability performance benchmarking of wind energy power plants
    (Pergamon-Elsevier Science Ltd, 2024) Kara, Karahan; Yalcin, Galip Cihan; Simic, Vladimir; Yildirim, Ali Tugrul; Pamucar, Dragan; Siarry, Patrick
    Wind energy power plants (WEPPs) are renewable energy generation facilities that are increasingly used today. The performance evaluations of these energy plants are generally based on technical performance. Although there are studies in the literature focusing on determining the technical performance of WEPPs, there is a lack of research on evaluating their sustainable performance. The primary motivation of this study is to develop a decision model for identifying the sustainable performance of WEPPs. The model incorporates fuzzy logic and multi-criteria decision-making (MCDM) approaches, incorporating expert opinions and both qualitative and quantitative criteria. To determine the influence levels of experts, spherical fuzzy (SF) sets are utilized. The weighting of criteria is achieved using the SF-defining interrelationships between ranked criteria II (DIBR II) method, which is a novel extension of the DIBR II method based on SF sets. Additionally, an SF-alternative ranking order method accounting for two-step normalization (AROMAN) method is developed for ranking the sustainable performance of WEPPs, building upon the AROMAN method, and adapting it to SF sets. This hybrid model is named the SF-DIBR II-AROMAN hybrid model. The step-by-step procedures of this model are presented in the research, and an algorithm for these procedures is developed. To demonstrate its practicality, a case study is conducted, focusing on WEPPs with a capacity ranging from 25 to 150 megawatts in & Ccedil;anakkale, Turkey. According to the research results, among the fifteen WEPPs in the & Ccedil;anakkale region, Saros WEPP is identified as having the best one. The robustness of the obtained results is ensured through sensitivity analyses. Based on the results of two sensitivity analysis scenarios, Saros WEPP is found to have the highest sustainable performance. The SF-DIBR II-AROMAN hybrid model results are compared with different alternative ranking method results, highlighting its superior aspects. Overall, SF-DIBR II-AROMAN is consistent and robust. The research also provides insights and managerial implications, as well as explains the benefits of the proposed model for evaluating WEPPs' sustainable performance.
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    A type-2 neutrosophic entropy-based group decision analytics model for sustainable aquaculture engineering
    (Pergamon-Elsevier Science Ltd, 2024) Kara, Karahan; Yalcin, Galip Cihan; Simic, Vladimir; Erbay, Murat; Pamucar, Dragan
    Fish cages are crucial for the establishment of sustainable fish farms. The selection of fish cages is an essential subject to be examined for ensuring sustainability. This research introduces an advanced decision support model for the selection of fish cage types used in fish farming in reservoirs (R-FFs). The decision support model is based on multi-criteria decision-making (MCDM) approach and utilizes type-2 neutrosophic numbers (T2NNs). The importance levels of criteria are determined using the T2NN-Entropy method, and the ranking of fish cage types is achieved through the alternative ranking order method accounting for two-step normalization (AROMAN). The developed model is referred to as the T2NN-Entropy-AROMAN hybrid method and relies on expert opinions. Two advanced aggregation operators based on Yager t-norm and t-conorm operations, named T2NN Yager weighted arithmetic mean and T2NN Yager weighted geometric mean, are developed for aggregating T2NNs. The validity of these two aggregation operators is demonstrated. A real-life case study is developed to confirm the applicability of the T2NN-Entropy-AROMAN hybrid method. This case study focuses on the selection of fish cage types for the Artvin-Bor & ccedil;ka R-FF in Artvin province, Turkey. The research results indicate that floating cages are the best alternative type for sustainable fish farming. Sensitivity analysis scenarios confirm the robustness of the research model and findings. The research findings, coupled with the developed model, offer valuable insights and guidance to decision-makers, researchers, and practitioners within the sector.
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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 interval-valued spherical fuzzy CIMAS-WISP group decision-analytic model for blockchain platform selection in digital projects
    (Elsevier, 2024) Kara, Karahan; Yalcin, Galip Cihan; Simic, Vladimir; Korkuc, Cagatay; Cicek, Ilhan; Afacan, Erkan; Pamucarg, Dragan
    Digital projects aspiring to reach target audiences are executed through decentralized and trustworthy block- chain platforms (BPs). Once the objectives and target audience of a digital project are defined, the selection of suitable BPs is undertaken. The primary objective of this research is to develop a decision support system that aids in the selection of BPs for transferring digital data and assets. Numerous quantitative parameters determine the performance of BPs, alongside qualitative parameters indicating their performance. In this study, the aim is to determine the performance of BPs based on both qualitative and quantitative parameters. Within this scope, a multi-criteria decision-making approach and interval-valued spherical fuzzy (IVSF) sets are adopted. IVSF sets are utilized to determine expert importance levels. The IVSF-criteria importance assessment (CIMAS) method is introduced for the weighting of criteria. IVSF-CIMAS enables the determination of reliability levels in calculating criterion weights. The IVSF-simple weighted sum product (WISP) method is formulated to obtain the performance ranking of BPs. Thus, in this research, the IVSF-CIMAS-WISP hybrid model is developed, and an algorithm for this novel decision-analytic model is presented. A case study is developed focusing on BP selection for a digital project to demonstrate the applicability of the proposed hybrid model. The robustness of IVSF-CIMAS
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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; Koleoglu, 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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    Electric vehicle selection for industrial users using an interval-valued intuitionistic fuzzy COPRAS-based model
    (Springer, 2024) Gorcun, Omer Faruk; Simic, Vladimir; Kundu, Pradip; Ozbek, Asir; Kucukonder, Hande
    According to reports from international bodies such as the World Health Organization and the United Nations, transportation is one of the leading contributors to environmental pollution and climate change. Electric vehicles present a practical solution to reducing emissions, particularly for industrial users. However, industrial users' selection of electric vehicles involves different dynamics than individual users, making it a more complex process for companies. This paper aims to evaluate the selection criteria for electric vehicle fleets among industrial users using a novel multi-criteria decision-making framework based on interval-valued intuitionistic fuzzy sets. The model assesses various factors influencing industrial users' decisions and ranks the available electric vehicle options accordingly. The results indicate that driving range, purchase price, and charging time are the most influential factors in the decision-making process. Furthermore, the findings confirm that the Tesla Model S P100D is the most suitable option for industrial users, given its superior performance in these critical criteria.
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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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    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.