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Öğe Clustering countries on logistics performance and carbon dioxide (CO2) emission efficiency: an empirical analysis(2022) Polat, Mustafa; Kara, Karahan; Yalçın, Galip CihanThe logistics industry is among the industries that affect carbon dioxide emissions. The logistics activities of the countries produce CO2 emissions. For this reason, there is a significant relationship between the logistics performance of countries and their CO2 emissions. In this study, it is aimed to make a cluster analysis by considering the CO2 emission per capita efficiency of the countries and their logistics performance. The empirical study was completed in three stages. In the first stage, hierarchical clustering analysis was conducted with the logistics performances of the countries and the CO2 emission per capita. In the second stage, the CO2 emission per capita efficiency based on the logistics performance sub-indicators of the countries were determined by data envelopment analysis. In the third stage, non-hierarchical clustering analysis was performed with the variables of logistics performances and CO2 emission per capita efficiency of the countries. 2018 logistics performance index (LPI) and CO2 emission per capita data of 150 countries were used. According to the research findings, there are differences in the findings of hierarchical clustering analysis and nonhierarchical clustering analysis. In the conclusion part of the study, the differences between the clusters were explained and suggestions were developed for the researchers.Öğe Competitiveness based logistics performance index: An empirical analysis in Organisation for Economic Co-operation and Development countries(SAGE Publications Ltd, 2023) Polat, Mustafa; Kara, Karahan; Acar, Avni ZaferLogistics, beyond being a strategically important function for global supply chains, is a sector of considerable size in terms of the global economy. Thus, economy-wide logistics capabilities have a strategic impact at the national level, supporting countries to achieve a global competitive advantage. For this reason, the logistics performances of the countries not only show the success of using their existing logistics capabilities but also provide significant indications about their competitiveness at the global level. Due to this strategic impact, this study aims to deal with the logistics performances of OECD countries from the perspective of competitiveness and to determine the competitiveness-based logistics performance index (CB-LPI). For this purpose, data envelopment analysis has been applied with two different techniques. The input variables are the Global Competitiveness Index, and the output variables are the Logistic Performance Index. In this empirical study, 7 inputs (infrastructure, skills, product market, financial system, information and communication technology adoption, business dynamism, innovation capability) and 6 output variables (Customs, Infrastructure, International shipments, Logistics quality and competence, Tracking and tracing, Timeliness) have been used. This study is handled in a total of 5 periods. These periods are 2010, 2012, 2014, 2016 and 2018. As a result, it was determined that the competitive logistics performances of 8 countries (Australia, Germany, Italy, Mexico, Poland, Portugal, Spain, and Turkey) were at the level of full efficiency in each period in the application of both techniques. In addition, the CB-LPI covering all OECD countries has been established. Based on the scores obtained, country-based suggestions for countries have been developed.Öğe Developing a hybrid methodology for green-based supplier selection: Application in the automotive industry(Elsevier Ltd, 2024) Kara, Karahan; Acar, Avni Zafer; Polat, Mustafa; Önden, İsmail; Yalçın, Galip CihanThe 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.Öğe An integrated neutrosophic Schweizer-Sklar-based model for evaluating economic activities in organized industrial zones(Elsevier Ltd, 2024) Kara, Karahan; Yalçın, Galip Cihan; Simic, Vladimir; Polat, Mustafa; Pamucar, DraganOrganized 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.
