8 research outputs found
Determining the logistics market performance of developing countries by entropy and MABAC methods
No full textBackground: The levels of logistics market performance of developing countries are published with Agility Emerging Markets Logistics Index (AEMLI) reports. The main purpose of this research is to propose a new model to determine the logistics market performance of developing countries in 2022 and to reorder the developing countries according to their logistics market performance. Methods: AEMLI indicators have been accepted as the basic criteria for determining the logistics market performance. The importance levels of these criteria have been determined by the Entropy technique. The logistics market performance rankings of developing countries according to the criteria were determined using the Multi-Attributive Border Approximation Area Comparison (MABAC) technique. The data set of 50 developing countries included in the 2022 AEMLI report has been used in the investigation. Results: According to the proposed new model, the weights of the criteria and logistics market performance rankings of developing countries have been determined. The importance levels of the criteria have been determined as Business Fundamentals (BF), Digital Readiness (DR), International Logistics Opportunities (ILO), and Domestic Logistics Opportunities (DLO), respectively. The ranking based on the new model was compared with the rankings in the 2022 AEMLI report. 21 of the 50 developing countries have improved their rankings. The ranking of 20 countries has been dropped. There is no change in the ranking of 9 countries. Additionally, according to AEMLI, the country with the highest logistics market performance is China, while the country with the best logistics market performance according to the proposed model is the United Arab Emirates (UAE). Conclusions: Contrary to the literature, Entropy and MABAC techniques were used to rank the logistics market performances of developing countries by making use of AEMLI reports. The issues that countries should focus on in the development of their logistics market performance are shown
DETERMINATION OF LOGISTICS INNOVATION PERFORMANCE INDEX WITH ENTROPY AND COMBINED COMPROMISE SOLUTION TECHNIQUES
No full textLogistics 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
A hybrid spherical fuzzy logarithmic decomposition of criteria importance and alternative ranking technique based on Adaptive Standardized Intervals model with application
No full textThis study presents a hybrid fuzzy Multi-Attribute Group Decision Making (MAGDM) model with application to commercial insurance selection. The proposed hybrid model uses Spherical Fuzzy (SF) sets using Yager t-norm and t-conorm operations. The Logarithmic Decomposition of Criteria Importance (LODECI) method is used for criterion weighting due to its efficacy in stabilizing scenarios that may challenge other weighting techniques. For alternative ranking, the study employs the Alternative Ranking Technique based on Adaptive Standardized Intervals (ARTASI), offering enhanced flexibility in handling uncertainties inherent in expert evaluations. The combination of these methods and the utilization of SF sets gives rise to the proposed SF-LODECI-ARTASI hybrid model. The paper systematically delineates the procedural steps involving SF sets, Yager t-norm and t-conorm operations, SF-LODECI, and SF-ARTASI methods. Subsequently, the developed hybrid model is applied to a case study of commercial insurance selection, supported by a numerical example. The research application results emphasize the consistency of these findings with other alternative methods. Additionally, sensitivity scenarios are constructed to scrutinize the robustness of the proposed hybrid model. The study concludes by elucidating implications and contributions to the existing literature. © 2024 The Author(s
An integrated neutrosophic Schweizer-Sklar-based model for evaluating economic activities in organized industrial zones
No full textOrganized 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
Developing a hybrid methodology for green-based supplier selection: Application in the automotive industry
No full textThe 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
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
No full textThe 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
Enhancing decision support system for finished vehicle logistics service provider selection through a single-valued neutrosophic Dombi Bonferroni-based model
No full textFinished 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
An intuitionistic fuzzy-based model for performance evaluation of EcoPorts
No full textThe 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
