Abstract The banking sector assumes a pivotal role in the economic development of nations. The assessment of financial indicators pertaining to banks holds fundamental importance in the evaluation of bank stability and sustainability. This research employs the MEREC (Method based on the Removal Effects of Criteria) and MARCOS (Measurement of Alternatives and Ranking according to COmpromise Solution) methodologies to delve deeper into the financial landscape of the banking sector in Bosnia and Herzegovina (BiH). Specifically, the objective is to rank banks according to their financial indicators, utilizing financial data from the year 2022. The MEREC method is applied to gauge the significance of financial indicators and ascertain their respective weights, while the MARCOS method is employed to rank banks within BiH based on their financial indicators. The examination of financial indicators within the BiH banking sector, facilitated by the MEREC and MARCOS methodologies, yields a more comprehensive understanding of the sector’s present condition. Limitations of this research, which primarily stem from its reliance on available financial data and predefined methodologies, lies within limited consideration for external factors. To provide a broader contextual perspective, the inclusion of additional financial indicators and comparative analyses with banking sectors of other nations would be imperative. The findings of this research reveal that Raiffeisen Bank exhibits the most favourable financial indicators and demonstrates the highest level of efficiency within this context. Consequently, this research offers insights into identifying exemplary banks that can serve as models for enhancing the performance of others.

In this study, the selection of suppliers within an alternative food supply network for fruits and vegetables, specifically Box Schemes, was conducted using multi-criteria decision-making methods. The Entropy-MABAC method was used as the multi-criteria decision-making approach, and the research focused on five suppliers from the city of Novi Sad. Eleven socioeconomic criteria were chosen for the research to identify the most favourable supplier. The results indicate that the criterion "product character," i.e., whether the final agricultural product is organic or conventional, was rated the highest, and the first supplier was selected as the most favourable. These results provide a solid foundation for future research, which should focus on further examining the impact of supply methods on end consumers of agricultural products within the alternative food network and developing new methods to aid in selecting the most favourable supplier.

Introduction/purpose: The paper presents the multi-criteria Fuzzy DIBR-Fuzzy DIBR II-EWAA-BM-DEXi-Fuzzy LMAW model for choosing a location for crossing water obstacles by fording in a defense operation. After the identification of the criteria by experts in this field, the mentioned model was applied and the optimal point was determined. In order to test the consistency of the results and the validity of the model, experts were consulted again, and the sensitivity analysis and the comparative analysis were performed. Methods: The Fuzzy DIBR and Fuzzy DIBR II methods were used to determine the weighting coefficients of the identified criteria, while the aggregation of the expert opinions and the obtained values was performed using the EWAA and BM operators. To select the optimal location, the Fuzzy LMAW method was applied, while the linguistic descriptors were determined using the DEXi decision support system. Results: The proposed methodology made it possible to identify all the criteria that determine the choice of a location and the choice of the optimal point for crossing a water obstacle in a defense operation. The testing of the model by experts, the analysis of the sensitivity of the output results to changes in the weights of the criteria and the comparison of the obtained results with the results of other methods indicated the fact that the model is valid and that it gives consistent results. Conclusion: It was concluded that the multi-criteria model provides the necessary help to decision makers in conditions of imprecise and unspecified information and that it is applicable in real situations. Also, the proposed model takes into consideration all the aspects that must be considered when making such a complex decision and helps less experienced officers in the decision-making process, reducing the possibility of errors, which can result in human casualties. Finally, directions for further research in the field of overcoming water obstacles and multicriteria decision making are suggested.

The development of agriculture is closely linked to technology and innovation. Drones have become a practical tool that helps improve agricultural production. This research focuses on choosing the spraying drone with the best features for the companyAgricultural goods Semberija. A multi-criteria decision-making process based on expert opinions was used to evaluate eight different drones across ten criteria. The fuzzy SiWeC (Simple Weight Calculation) method was applied to determine theimportance of each criterion, showing that all criteria were similarly important in the decision-making process. To select the best drone, the fuzzy COmpromise Ranking from Alternative SOlutions (CORASO) method was used. The results show that theDJI Agras T30 drone has the best features and is the preferred choice for purchase. These findings were confirmed by further comparative and sensitivity analyses. This study highlights the use of new methods for selecting equipment in agriculture.

The process of deep sheet metal drawing is accepted in all industrial branches. This process is, therefore, very important to maintain a certain level of quality. For this reason, measurements and tests must be carried out to determine how much sheet metal deformation occurred after the deep drawing process. For this purpose, an experiment of deep drawing of sheet metal was carried out using the example of kitchen utensils. In addition, the Taguchi method was used in this experiment to test the quality of the obtained kitchenware. In the experiment, three factors were taken with three alternatives that affect the deep drawing of sheet metal, and 27 experiments were used for the Taguchi method. The results of this experiment showed that the best results were achieved by the smallest drawing depth of 65 mm and the worst results were obtained by the drawing thickness of 70 mm. Regarding the thickness of the material, the best results were achieved by the material of 21 mm, and the material of 15 mm achieved the worst results. In addition, an analysis of variance was carried out, which determined the relationship between force and deformation of the material.

The knowledge that is based on science, technology, engineering, and mathematics is the basis for the development of any country. Less developed countries lack experts in these areas. Therefore, the ENABLE-BIH project (Enhancing and Advancing Basic Learning and Education in Bosnia and Herzegovina) was introduced in Bosnia and Herzegovina, which aims to improve the situation in the education sector. This study included the Public Institution “Ninth Elementary School” in Brcko District of Bosnia and Herzegovina in which this project was implemented. The study included a total of 125 students from this school. The aim of this study is to examine the difference between attitudes about STEM from the point of view of gender differences and the age of students. After the data were collected, the statements were grouped into appropriate factors using factor analysis. The factor analysis showed that five factors stand out in this research. The results of multiple regression analysis showed that there is no difference between students ‘attitudes regarding gender differences, while there is a difference regarding students’ age. The results of this research showed that the ENABLE-BIH project delivered good results and suggests the importance of implementing similar projects in the future.

This study presents the MCDM model created for the selection of a dump truck for the needs of the army engineering units, based primarily on the truck’s construction features and purchasing and maintenance costs. In this study was used the Methodology of Additive Weights (LMAW) in Fuzzy surrounding for determination of weight coefficients of criteria, while for the selection of the optimal alternative (for a dump truck) it was used the Measurement of Alternatives and Ranking according to Compromise Solution (MARCOS) method, modified by interval grey numbers. Input data for this methodology were obtained by engaging experts. Finally, the analysis was made of the sensitivity of output results of the proposed MCDM methodology to the change of weight coefficients of criteria, as well as the comparison of the obtained results with the results of other methodologies. In the conclusion, the proposed model showed stability but it was sensitive to weight coefficients change which should be taken into account by defining the same by experts.

Abstract The COVID-19 virus pandemic had an impact on all segments of life, including dally operations of companies. Companies had to adapt to market developments and change their business philosophy in order to survive in the market. This paper showed how the crisis caused by the COVID-19 virus pandemic affects the business of companies. This study aims to examine the business performance indicators (BPI) of companies listed on the Warsaw Stock Exchange (WSE) before and during the COVID-19 pandemic with a focus on corporate social responsibility (CSR). In order to examine this, a multivariate regression analysis was conducted. The findings show that there were no changes in the BPIs before and during the COVID-19 pandemic in companies in relation to CSR strategy. The only exception was found in the group of CSR companies that reported a lower profit margin during the COVID-19 pandemic. Companies with better BPIs may be willing to introduce CSR principles into their strategy and during the pandemic, intangibles influenced CSR strategy in a negative way. The limitations of the article are related to the study of only one market. Identified relationships allowed for a better understanding of the application of social responsibility principles among enterprises in Central Europe.

Urban logistics implementation causes environmental pollution; therefore, it is necessary to consider the impact on the environment when carrying out such logistics. Electric vehicles are alternative vehicles that reduce the impact on the environment. For this reason, this study investigated which electric vehicle has the best indicators for urban logistics. An innovative approach when selecting such vehicles is the application of a fuzzy–rough method based on expert decision making, whereby the decision-making process is adapted to the decision makers. In this case, two methods of multi-criteria decision making (MCDM) were used: SWARA (stepwise weight assessment ratio analysis) and MARCOS (measurement alternatives and ranking according to compromise solution). By applying the fuzzy–rough approach, uncertainty is included when making a decision, and it is possible to use linguistic values. The results obtained by the fuzzy–rough SWARA method showed that the range and price of electric vehicles have the greatest influence on the selection of an electric delivery vehicle. The results of applying the fuzzy–rough MARCOS method indicated that the Kangoo E-Tech Electric vehicle has the best characteristics according to experts’ estimates. These results were confirmed by validation and the application of sensitivity analysis. In urban logistics, the selection of an electric delivery vehicle helps to reduce the impact on the environment. By applying the fuzzy–rough approach, the decision-making problem is adjusted to the preferences of the decision makers who play a major role in purchasing a vehicle.

The selection of unmanned aerial vehicles for different purposes is a frequent topic of research. This paper presents a hybrid model of an unmanned aerial vehicle (UAV) selection using the Defining Interrelationships Between Ranked criteria (DIBR), Full Consistency Method (FUCOM), Logarithm Methodology of Additive Weights (LMAW) and grey - Evaluation based on Distance from Average Solution (G-EDAS) methods. The above-mentioned model is tested and confirmed in a case study. First of all, in the paper are defined the criteria conditioning the selection, and then with the help of experts and by applying the DIBR, FUCOM and LMAW methods, the weight coefficients of the criteria are determined. The final values of the weight coefficients are obtained by aggregating the values of the criteria weights from all the three methods using the Bonferroni aggregator. Ranking and selection of the optimal UAV from twenty-three defined alternatives is carried out using the G-EDAS method. Sensitivity analysis confirmed a high degree of consistency of the solutions obtained using other MCDM methods, as well as changing the criteria weight coefficients. The proposed model has proved to be stable; its application is also possible in other areas and it is a reliable tool for decision-makers during the selection process.

This research focuses on the use of electric vehicles (EVs) to transport visitors and cargo within Bosnia and Herzegovina’s Kozara National Park. Reduced air pollution and the preservation of natural resources are required to help protect this aerial spa. Together with the expert employees of this NP, the EV that would best suit their needs was chosen. The process of decision-making combines subjective and objective methods. Employees first chose the criteria and alternatives and then weighed their importance. On that occasion, Z-numbers were used to include uncertainty in the decision, because it is not always possible to make decisions with complete certainty. Furthermore, the weight of these criteria was determined using the fuzzy PIPRECIA (PIvot Pairwise Relative Criteria Importance Assessment) method. Range (C1) became the most important criterion, followed by vehicle cost (C2), and the technical specifications of these EVs were used to compare them. Because these specifications vary, a rough set was used in which the minimum and maximum EV characteristics were taken based on specific criteria. To rank the alternatives, the R-CRADIS (Rough Compromise Ranking of Alternatives with Distance to Ideal Solution) method was used. According to the research results, the Mercedes eVito Tourer 90 kWh is the highest ranked EV and the validation of the results confirmed these findings. According to the research results, the Mercedes eVito Tourer 90 kWh is the highest ranked EV and the validation of the results confirmed these findings. The sensitivity analysis revealed that if criterion C1 is not as important, the other EVs are ranked higher. This research`s methodology has demonstrated flexibility, therefore it is recommended for use in similar research.

This research paper aims to assess the sustainable competitiveness of Balkan countries. Sustainable competitiveness was measured based on the indicators in The Sustainable Competitiveness Report from 2022, published by Solability. According to this report, sustainable competitiveness is evaluated using six grouped criteria. In this paper, the competitiveness of the Balkan countries was assessed through the application of the multicriteria analysis methods Entropy and MARCOS (Measurement Alternatives and Ranking according to the Compromise Solution). The weight of each criterion was determined using the Entropy method. The results highlighted that the most significant criteria were Natural Capital and Resource Efficiency & Intensity, which carried the highest weight, whereas the Social Cohesion criterion was of lesser importance, represented by the lowest weight. Using the MARCOS method, the Balkan countries were ranked, with Greece securing the top position, closely followed by Albania, while North Macedonia exhibited the weakest performance. Sensitivity analysis further substantiated these findings. The outcomes of this study significantly contribute to the academic understanding of sustainable competitiveness and provide valuable practical insights for policymakers and stakeholders interested in advancing sustainable development efforts in the Balkan region.

The purpose of the present study is to propose an interval-valued type 2 fuzzy set (IT2FS)-based analytic hierarchy process (AHP) framework to unfold the critical challenging factors influencing the sustenance and growth of the Indian tea industry. The current work follows an expert opinion-based group decision-making approach. The challenging factors have been identified through a literature review and finalized after a pilot study based on the opinions of professionals, consumers, and experts. Finally, the critical challenging factors and sub-factors have been figured out through analysis of the responses of the experts. To offset the subjective bias, an IT2FS-based granular analysis has been carried out. The findings reveal that market diversification and productivity are the central issues. Additionally, it is important to give attention to improving the quality of the products, increasing the use of modern technology and organic farming, and developing a variety of products. The result shows a considerable level of consistency in the group decision-making (CR < 0.1) for all pairwise comparisons. The present work shall be of use to formulate appropriate strategies and policy decisions. It shows a robust application of IT2FS-AHP for complex decision-making in real life.