The development of technology has influenced agricultural production and the establishment of the Agriculture 4.0 system in practice. This research is focused on the selection of equipment and machinery suppliers for the needs of the MAMEX Company. When selecting suppliers, an approach based on the application of an intuitionistic fuzzy set for decision-making was used. This approach allows the uncertainty present in decision-making to be incorporated, considered, and, hopefully, reduced in order to make a final decision on which of the observed suppliers is the most suitable for this company. Ten criteria were used that enable the application of sustainability in the supply chain. Eight local suppliers of equipment and machinery were observed with these criteria. The results obtained by applying the SWARA (Step-wise Weight Assessment Ratio Analysis) method showed that the most important criterion for selecting suppliers is the reliability and quality of equipment and machinery, while the results of the CORASO (COmpromise Ranking from Alternative Solutions) method showed that the SUP2 supplier is the best choice for establishing partnership relations with the MAMEX company. This supplier should help the MAMEX company improve its business and achieve better results in the market. The contribution of this research is to improve the application of intuitionistic fuzzy sets in decision-making, and to emphasize the importance of equipment and machinery in agricultural production in the Agriculture 4.0 system.

Abstract Consumers of agricultural products represent a sensitive category of society, therefore communication with them is particularly important. Communication is influenced by a large number of factors, and in this regard, making the right decision about the way to communicate is an extremely complex job. In previous research, the emphasis was placed mostly on the entire supply chain, much more than on the method of choosing communication with end consumers of agricultural products. Therefore, this research represents an attempt to make an additional contribution to rational decision-making in this part of the agricultural supply chain. In this paper, the selection of criteria used in the process of communicating with consumers in a country was carried out by applying expert fuzzy multi-criteria decision-making. The innovative fuzzy method SiWeC (Simple Weight Calculation) was applied to evaluate ten given criteria with the aim of their selection. The subject of the research were several agricultural companies and the experts were six experts from the marketing department of the companies in question. The results show that the method of communication itself is the best evaluated criterion, as well as the delivery time, i.e. the impact of delivery speed on the demand for a particular agricultural product. Uncertainty in decision-making is reduced by applying fuzzy decision-making logic, and the results provide the basis for future research that should be directed at selecting the most favorable methods of communication when products of this type are in question, as well as the development of the existing methodology, which in this case has proven to be adequate.

Overcoming water obstacles is a demanding combat action that requires serious planning under conditions of uncertainty and risk. Choosing a planning method for the implementation of engineering works in the army, as well as how to choose them, has always been a challenge that engineering officers have faced. In this paper, for the selection of the network planning technique, the use of the multi-criteria decision-making (MCDM) model, which contains the methods Logarithm Methodology of Additive Weights (LMAW) and Grey Operational Competitiveness Rating (OCRA), as well as the Einstein weighted arithmetic average (EWAA) operator for aggregating expert opinions, is presented. The LMAW method was used to define the weights of the criteria, while the Grey OCRA method was used to select the optimal planning technique. The Event Chain Methodology (ECM) was identified as the most suitable method for planning the engineering works in question, while the Critical Path Method (CPM) and Precedence Diagramming Method (PDM) are also suitable. In order to check the consistency and validation of the obtained results, a sensitivity analysis to changes in criteria weights and a comparative analysis were performed, where the results were compared with four other MCDM methods in a grey environment. The results of the analyses indicate that the model provides consistent and valid results.

The paper focuses on the role of artificial intelligence in tourism

The authors used a quantitative research method to analyze the market trends of fresh plums in Serbia. For this purpose, they used competitiveness parameters that were processed using standard descriptive statistics tools. The goal was to review the foreign trade of plums, as well as to determine the trend of competitiveness indicators for this fruit. The results show that during the analyzed ten-year period from 2014 to 2023, there was a slight downward trend in all production parameters of this fruit, but that Serbia was self-sufficient in its production, as well as price-competitive on the world market. Also, a downward trend in certain competitiveness indicators was observed, which indicates a further strengthening of the market position of this fruit species. Further research should be focused on determining the causes of the trend in competitiveness indicators, as well as ways to strengthen them.

In competitive organizations and projects, assessing risks related to human capital is essential for improving workplace conditions and ensuring project success. This study evaluates primary, secondary, and residual human capital risks in urban water transfer projects using an innovative hybrid DEMATEL–MARCOS approach. The DEMATEL method was employed to analyze causal relationships and interdependencies among risks, while the MARCOS method ranked their significance. The key findings reveal that “accidents during material transportation” (primary risk), “corrosion” (secondary risk), and “pipeline pressure” (residual risk) are the most critical factors influencing human capital in such projects. The study provides a structured framework for prioritizing risk mitigation strategies, offering actionable insights for policymakers and project managers to enhance safety, efficiency, and workforce well-being. By integrating multi-criteria decision-making techniques, this research bridges a gap in the water industry’s risk management practices and contributes to safer, more sustainable infrastructure development.

Abstract Digital transformation significantly impacts all aspects of the economic system, particularly the functioning of monetary policy and the financial sector. As a key process in modernization, digital transformation encompasses innovations that enable faster, safer and more efficient financial transactions, contributing to greater transparency and better economic integration. This paper analyzes the impact of digital transformation on the monetary policies of Southeast European (SEE) countries, with a particular focus on the development and implementation of digital payment systems. The aim of the research is to examine the potential of digital technologies to improve the monetary policies of these countries, enabling them to achieve greater financial stability and alignment with European Union (EU) standards. The focus is on identifying the benefits of implementing digital payments, including reducing transaction costs, improving trust in monetary institutions, and increasing the transparency of financial flows. The methodological framework of the research is based on multi-criteria decision-making (MCDM), using the CRITIC and MARCOS methods. The CRITIC method was used to evaluate the importance of individual criteria relevant to digital payments, while the MARCOS method enabled the ranking of countries based on their potential for implementing digital payments. The results of the research show that alignment with EU legislation is the most important factor, while Romania has the best potential for implementing digital payments among the observed countries. The contribution of this paper is reflected in the development of a strategic framework and the encouragement of regional cooperation, through which SEE countries could realize the full potential of digital transformation to accelerate economic growth and integration with the EU.

Ethnic villages are examples of tourism products based on historical representations of the region. Within these villages, tourists participate in various customs and traditions, gaining insights into the heritage of local communities. As heritage should be the basis for improving rural tourism, this research was conducted to investigate the extent to which ethnic villages safeguard their heritage. The examination of cultural heritage was carried out by experts who evaluated the importance of the criteria for assessing heritage and the application of cultural heritage in these ethnic villages. A fuzzy approach was used to assess the criteria and ethnic villages using fuzzy Logarithm Methodology of Additive Weights (LMWA) and fuzzy Additive Ratio Assessment (ARAS). The sampling process included an initial pool of 28 ethnic villages identified through various associations and agencies. The villages included in this research were chosen by randomly selecting eight villages using a random number generator. Through collaboration with experts and thorough literature research, 12 criteria were established for evaluating heritage use degree in these villages. Results highlighted tourist participation as the most significant criterion, with the Lubac Valley ethnic village demonstrating superior performance. As this research has shown, applying heritage in tourism provides a unique experience, which is the base for developing rural tourism, and the Lubac Valley could serve as an example to other ethnic villages on building a tourist offer based on heritage. In addition, this research contributes to understanding the current landscape and strengthening the promotion of heritage in ethnic villages by developing a sustainable tourist offer.

The banking sector plays a key role in the economic, social, and political development of a country. The study of the financial performance of banks is essential for investors, creditors, and other interested parties. The aim of this research was to rank the second-tier banks in Albania by financial performance using a fuzzy multi-criteria decision model (fuzzy MCDM). For the ranking of banks, eight financial criteria were taken into account during the years 2020, 2021, and 2022 for 11 banks in the Albanian banking sector. Based on the selected indicators, a decision-making model was created. The Fuzzy Analytic Hierarchy Process (FAHP) and the Technique for Order of Preference by Similarity to the Ideal Solution (TOPSIS) methods were used in this research. The results of the FAHP method showed that the most important indicators are Equity and EBT. The results of the TOPSIS method showed that Banka Kombëtare Tregtare (BKT) had the best indicators for the observed years. The contribution of this research is in understanding the financial operations of banks in Albania.

Overall bank performance in a particular year or period is important to all banking industry stakeholders, as it indicates their success or failure relative to predetermined targets. Due to conflicting criteria and uncertainties, assessing bank performance is a complicated decision-making problem. The current paper proposes the Fuzzy Level Based Weight Assessment (F-LBWA), the Fuzzy Logarithm Methodology of Additive Weights (F-LMAW), and the Measurement Alternatives and Ranking according to the Compromise Solution (MARCOS) combination as a practical and robust decision-making tool to cope with many complex ambiguities. In the first phase, the suggested hybrid Multi-Criteria Decision-Making (MCDM) approach estimates the weight coefficients of the performance criteria with the aid of a combined version of the F-LBWA and F-LMAW methods. In the second phase, the MARCOS method determines the ranking performance of the decision alternatives. The introduced model is tested and validated on a case study assessing publicly traded bank performance in Pakistan. The findings obtained from the sensitivity analysis revealed that the presented F-LBWA-F-LMAW-MARCOS approach produces consistent solutions and is a reliable and effective procedure in rational decision-making.

The objective of this study was to provide decision-making assistance in selecting electric vehicles (EVs). The multi-criteria decision-making methods (MCDM), criteria importance through inter-criteria correlation (CRITIC) and evaluation by distance from ideal solution of alternatives (EDISA), along with the technical specifications of EVs, were employed to facilitate the decision on purchasing an EV. A total of 14 minivans were analysed based on 10 criteria. The findings from the CRITIC method indicated that the most significant criteria are battery charging and vehicle consumption. The EDISA method indicated that EV11 exhibited the best characteristics and represented a prudent purchase decision. Nevertheless, the ultimate decision must consider additional factors beyond just the technical specifications, as numerous elements affect the final choice, necessitating an examination of other attributes of the EV.

Selecting a tractor is one of the most complex investment decisions an agricultural producer faces. There are numerous types of tractors on the market, each differing in technical, economic, and ecological characteristics. The aim of this research is to demonstrate how multi-criteria analysis methods can aid in this decision-making process, using a practical example of selecting an optimal tractor for the Myzeqe area in Albania. In this study, a decision-making model was developed based on a hybrid fuzzy methodology, combining the fuzzy LOPCOW (Logarithmic Percentage Change-Driven Objective Weighting) and fuzzy MABAC (Multi-Attributive Border Approximation Area Comparison) methods. The findings show that the determination of criterion weights is less crucial, with the T15 tractor exhibiting the best overall indicators. This research primarily contributes to developing a methodology in agriculture that enhances production outcomes.