Juvenile victims of crime face the risk of secondary traumatization during court proceedings. In practice, the selection of protective measures often depends on judges' subjective decisions rather than systematic evaluation. This research addresses this issue by developing a decision-support system to select protective measures for juvenile victims of crime in Montenegro. Here, 22 experts from the justice and social protection systems evaluated 6 protective measures against 10 criteria using a fuzzy approach. The results of the fuzzy SiWeC (Simple Weight Calculation) method show that experts prioritize Additional trauma prevention, Recovery support, and Physical safety as the most important criteria. The results of the fuzzy TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution) method show that professional support emerged as the highest-rated protective measure, followed by video-link testimony and identity anonymization. Sensitivity analysis indicates that no single measure fits all cases; thus, the choice should be tailored to the specific needs and circumstances of each case. This research offers a transparent, repeatable framework for judges and social workers when making decisions about protective measures. It contributes to more consistent protection for juvenile victims. The findings also have direct implications for legislative reform, resource allocation, and professional training in Montenegro to better assist juvenile victims of crime.

Each local community has distinct traditions and customs that define its cultural heritage and make it recognizable. This paper examines how cultural heritage can strengthen and develop rural tourism. To do so, a model was developed to assess the extent to which cultural heritage is integrated into tourism activities in rural areas. The model includes seven rural households in Bosnia and Herzegovina (BiH) engaged in rural tourism, along with ten criteria for evaluating them. Using multi-criteria decision-making (MCDM), the importance of the criteria and the selected rural households were first assessed through expert evaluation. The results of fuzzy LMAW (Logarithmic Methodology of Additive Weights) indicate that attractiveness (C9) and economic potential (C7) are the most important criteria for evaluating rural households. Ranking the rural households using the fuzzy RAWEC (Ranking of Alternatives with Weights of Criterion) method shows that the Ibrišimović household is the most successful example of integrating cultural heritage into rural tourism offerings. This research offers a new approach to valuing cultural heritage in tourism and aims to support the continued development of rural tourism in BiH through sustainable practices.

The shift in agricultural production enabled by modern technology has led to the adoption of intelligent and autonomous systems, marking the Agriculture 5.0 era. Drones play a crucial role in this system, and as their use continues to expand, selecting the appropriate drones presents a complex multi-criteria decision-making problem that requires careful consideration of various factors. In this study, drones were evaluated and selected based on technical, economic, and environmental criteria. The decision-making process used interval type-2 fuzzy sets (IT2F) to incorporate uncertainty, and the model focused on ten criteria and five available drones in the Serbian market. It integrated the SiWeC (Simple Weight Calculation) method to determine criteria weights and the CRADIS (Compromise Ranking of Alternatives from Distance to Ideal Solution) method to rank the drones, forming a hybrid approach. The results indicated that Ease of Use (C6), Price (C8), and Maintenance Costs (C7) had the greatest influence on the final decision. Drone 4 achieved the highest score of 0.969 based on expert assessment, outperforming the second-ranked Drone 1 by 12%. Sensitivity analysis across 30 scenarios confirmed the stability of the ranking and showed that individual criteria did not significantly impact the results. The proposed IT2F SiWeC-CRADIS model demonstrated strong robustness and reliability and could be applied to select other smart technologies within the framework of Agriculture 5.0.

This research assessed management strategies for overtourism in Zadar County. Overtourism has become apparent in both city and seaside destinations, affecting residents’ quality of life. This study defines overtourism as a challenge for urban management, emphasizing that exploring strategies to address overtourism also influences the management of sustainability and quality of life in urban areas. Here, a methodological framework was created with five strategies, each evaluated against seven criteria. The evaluation was carried out by the directors of the county’s tourist boards. Since these strategies have not yet been implemented, the directors had to rate them with some uncertainty, as they lacked complete information about the criteria and potential effects. To handle this uncertainty, the intuitionistic fuzzy set (IFS) approach was used. Additionally, the SiWeC method determined the importance of the criteria, and the TOPSIS method ranked the strategies. Results, based on ratings from 12 directors, indicated that Digital Support and Environmental Sustainability are the most important criteria. Strategy C, which aims to redirect tourists to lesser-known locations within the county, performed best, maintaining visitor numbers while helping preserve the region’s natural resources. This research has shown that strategies for managing overtourism help reduce the pressure tourists place on urban environments, thereby improving the quality of life and sustainable development of these environments.

This research aimed to examine which of the selected strategies can most effectively influence households to reduce their total municipal waste and thus protect the environment. To achieve this goal, a sample of 202 households from the Brčko District of BiH was used. Respondents evaluated six strategies against ten criteria, expressing their assessments through linguistic values. These linguistic inputs were modeled using symmetric fuzzy numbers, ensuring a consistent and mathematically robust representation of uncertainty and subjective judgment. The research used the fuzzy SiWeC (Simple Weight Calculation) method to determine the importance of the criteria, and the fuzzy TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution), ARAS (Additive Ratio Assessment), and SAW (Simple Additive Weighted) methods to rank the strategies. The application of several methods in decision-making helps validate results and verify the robustness of strategy selection. These methods identified “waste reduction efficiency” as the most important criterion and “Strategy 3—Packaging return machines” as the most effective overall. Furthermore, analysis of demographic subgroups revealed significant variations in the perceived value of alternative strategies. Consequently, this study concludes that to optimize municipal waste management, strategies should be tailored to specific demographic profiles. This targeted approach would enhance waste reduction at the source, divert more waste from landfills, and promote the broader implementation of circular economy principles. The use of symmetric fuzzy numbers provided a reliable and stable foundation for this multi-criteria decision-making analysis.

The automotive industry is undergoing a significant transformation towards electric vehicles (EVs) with the main goal of reducing greenhouse gas emissions and for a sustainable and green environment. Different types of EVs are introduced every day in the market where selecting an optimal vehicle for purchase constitutes a complex decision-making. Therefore, the purpose of this research was to evaluate EVs in Albania using multi-criteria decision-making methods (MCDM). A total of 12 vehicles were analyzed based on 4 main criteria and 12 sub-criteria. The fuzzy Logarithm Methodology of Additive Weights (LMAW) method was applied to find the weights of the main criteria while the fuzzy Logarithmic Percentage Change-driven Objective Weighting (LOPCOW) method was applied to find the weights of the sub-criteria. For the EV ranking, the fuzzy Ranking of Alternatives with Weights of Criterion (RAWEC) method was applied. The findings showed that the most important criteria are the technical criteria and the Auto 11 vehicle showed the best results. The combination of Fuzzy LMAW-Fuzzy LOPCOW-Fuzzy RAWEC methods also constitutes the novelty of this research, which has not been applied before in this field. The contribution of this research consists in providing a comprehensive set of selection criteria to choose the best alternative of the EV fleet in Albania. Furthermore, the contribution of this research was the application of a hybrid methodology in the evaluation and selection of an electric vehicle as an ongoing choice faced by vehicle buyers.

The growth of medical tourism has contributed to the expansion of dental tourism. With the rise of tourism in Albania, dental tourism has similarly progressed. This research aims to evaluate the quality of dental tourism services in Tirana, applying fuzzy methods such as CRITIC (CRiteria Importance Through Intercriteria Correlation) and CoCoSo (Combined Compromise Solution). These two methods were integrated into a hybrid approach, as described in this paper. Seven experts evaluated dental practices using linguistic values. The CRITIC method results indicated that, among the ten criteria, the most significant was the variety of services. According to the CoCoSo method, Biodent Denti e Sorrisi, Diamond Dental, and Dental Med Austria practices demonstrated the highest quality in dental tourism services. As research results indicate, these clinics could serve as models for improving dental tourism in Albania through a focus on quality development.

The quality of interpersonal communication is one of the foundations of a functional and stable marriage. The aim of this work is to identify and determine the importance of factors that influence the quality of interpersonal communication in marriage using the fuzzy SIWEC (Simple Weight Calculation) method. The research was conducted on a sample of eight experts, who evaluated ten factors that influence the quality of interpersonal communication in marriage using linguistic values. Using the fuzzy SIWEC method, weighting coefficients were calculated for each factor that determined the importance of the selected factors. The results show that the level of mutual trust is the most important factor, followed by emotional stability, communication style and conflict management. The experts rated the level of education and digital communication as the least important factors. The obtained results show that interventions to improve marital relations should prioritize strengthening trust and emotional stability of partners. The contribution of this work is in connecting the methods of multi-criteria analysis with the psychology of family relationships, and in this way it is possible to rank certain factors and determine which factors influence the quality of interpersonal communication in marriage.

“AIholic” refers to the excessive reliance on artificial intelligence (AI) systems, where users depend on these systems not only for practical support, such as information searching, problem-solving, and task completion, but also for reassurance, validation, and emotional comfort. In higher education, Generative AI chatbots have become widely used in universities because they provide students with instant, personalized, and continuous academic support, not only practical support such as information searching, problem-solving, and task completion but also emotional support such as reassurance and validation. However, this rapid use has also raised concerns about students’ growing dependence on these tools. Based on self-determination theory and compulsive behavior theory, this study examines how situational triggers and psychological needs, namely, competence, relatedness, and autonomy, are associated with students’ actual dependency level on generative AI chatbots and their inability to reduce use. The study also examines the moderating role of risk perception in these relationships. Data collected from 787 university students in Iraq and Oman were analyzed using structural equation modeling. In addition, the MEREC method was used to determine the objective weights of the main criteria, while the VIKOR method was applied to compare the weighted determinants across the two national contexts. The findings indicate that psychological needs, especially competence and autonomy, and contextual triggers are important factors in explaining chatbot dependency. Students use chatbots not only for academic support but also for reassurance, connection, and self-directed learning. Furthermore, the results from using the multi-criteria decision-making approaches reveal contextual differences between the two countries. Risk perception received the highest weight in Oman, whereas triggers received the highest weight in Iraq. This study explains AI dependency as a psychological and behavioral phenomenon and provides practical insights for the responsible use of generative AI tools in higher education.

This research examines which organizational structure would yield the best results for the operations of a selected agro-food company. To do this, a decision-making model was developed, including six organizational structures and 19 criteria. The model was evaluated by experts using linguistic assessments. In addition, uncertainty was incorporated into this decision-making process through an intuitionistic approach. The results were obtained using the SiWeC (Simple Weight Calculation) and RAWEC (Ranking of Alternatives with Weights of Criterion) methods. The SiWeC method identified employee satisfaction and decision-making speed as the most important criteria, while the RAWEC method found that a digital organizational structure provides the best results. However, to achieve even better results in this company, it is necessary to upgrade the digital organizational structure to a network structure, leveraging the strengths of both. In this way, by forming a hybrid organizational structure, better effects would be obtained than using a single organizational structure.