Abstract To preserve resources for future generations and promote rural development, supporting ecotourism is essential. This paper provides guidelines for developing ecotourism, highlighting its role in environmental conservation. While mass tourism benefits rural communities, it can cause significant environmental harm. Therefore, this research promotes ecotourism as a sustainable alternative. In rural areas, ecotourism supports development by responsibly using natural resources. The study focuses on the potential of rural settlements in the Semberija region of Bosnia and Herzegovina, assessing their capacity for ecotourism to aid local development. A decision model was developed, considering four main criteria - natural, infrastructure, socio-cultural, and economic - and their sub-criteria. This model evaluates six rural communities’ ecotourism potential. To determine the importance of each criterion, a fuzzy weighting method with the Bonferroni mean operator was used, revealing economic factors as the most influential. The fuzzy ranking method then ranked the settlements, with Amajlije identified as having the highest ecotourism potential. The findings suggest that promoting ecotourism in Amajlije and similar communities can support sustainable rural development, balancing environmental preservation with economic growth.

The primary objective of this study was to develop a predictive model for the supply of live livestock in the Republic of Croatia for the period 2024-2029, based on the analysis of historical data. Livestock production has long been a strategically important sector in Croatia, supported by a strong tradition and a notable presence of indigenous breeds. Nevertheless, despite these advantages, the supply of live livestock per production unit has demonstrated persistent negative trends. The study applies the Autoregressive Integrated Moving Average (ARIMA) model to analyze time series data from 2019 to 2023 in order to identify structural patterns and forecast future supply dynamics. Supplementary statistical and econometric methods are employed to examine variation, autocorrelation, and the significance of fluctuations within the series. The analysis also highlights that the cost of production, as a key non-price determinant, plays a decisive role in shaping livestock supply trends. Findings indicate a regressive trend across most livestock sectors, emphasizing the need for targeted policy measures to stabilize and enhance future production.

The purpose of the paper is to show, through the selection of given criteria, which of them has the greatest impact on food losses in an agricultural-food company. For this purpose, an innovative expert method of multi-criteria decision-making, SiWeC (Simple Weight Calculation), and its fuzzy variant, was applied. The results show that the criteria “poor handling of products during transport” and “inadequate packaging and handling of products” have the greatest impact. Considering the already existing plan of the company to train this part of the work processes, the expert assessment confirms the results of the research. Also, the successful use of this method with the application of fuzzy logic was confirmed, and future research should be directed towards the development of new ways of researching the influence of individual factors on the entire process of supplying food to end consumers.

The aim of this study was to select the best marketing communication channel for a medium-sized agricultural company in the area of the city of Bijeljina by applying multi-criteria decision-making methods. Eight criteria were used for the research, and five communication channels were selected. The research on the importance of individual criteria was influenced by the commercial management of the company in question with their common attitude, i.e. assessment. The Entropy - MABAC method of multi-criteria decision-making was used for the methodology. The results show that the criterion of diversity of new information is the most significant. The best-rated communication channel is the company’s good image. The second-best rated alternative is the use of the internet, specifically social media. The results provide a good basis for further research in this area with the aim of determining the factors that influence the choice of future promotion methods and obtaining useful information.

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.

Paper presents a model for the optimization of primary milk production in the hillymountainous regions of the Republic of Serbia. The goal of creating the model is to demonstrate and analyze the conditions and outcomes of production at the farm, while to find the optimal production structure, considering the organizational, economic, technical, and technological circumstances in which the farm performs its agricultural activities. The model is based on the linear programming optimization method. A mathematical model, or objective function, was established, and constraints were identified. A logical model was created for optimization. The main goal of solving the linear programming problem is to find the maximum or minimum of the objective function. In presented model, the task is to maximize the objective function, what is represented by the farm's net income. By using the linear programming, it is possible to determine the optimal quantities of resources and products to maximize net income, while adhering to resource constraints and other relevant factors.

The agriculture sector in the Republic of Serbia holds significant economic and social importance due to its substantial contribution to domestic gross domestic product (GDP) and employment of a large number of people. Agricultural products play a crucial role in Serbia's export structure. Food is one of Serbia's major export products, with a trade surplus steadily increasing since 2005. Fruit cultivation, as part of the agricultural sector, is of great importance, with domestic producers effectively utilizing natural advantages for production, thus achieving recognition and competitiveness internationally. This study aims to analyze the trends in foreign trade parameters over a decade, focusing on one agricultural product, specifically apricots. The research employs a quantitative research method using standard descriptive statistical instruments. Results indicate that Serbia maintains a trade surplus in apricots, with significant fluctuations and varying growth and decline trends in analyzed trade parameters over the period.

This study focuses on the theoretical analysis of the application of modeling and mathematical, particularly linear programming, in managerial processes within the agro-industrial complex. The authors have dedicated themselves specifically to defining planning processes, classifying models, and organizing production structures, including vertical and horizontal structures. Despite the fact that the benefits of linear programming have been proven, it is still not widely accepted and applied in our region. The reasons for this can be found in the relative complexity of the process, both in creating logical and mathematical models, and in interpreting results. Although there are specialized software and add-ons such as Solver in MS Excel, they are still not accessible enough to a wider range of users in the agro-industrial sector. It is evident that there is a need for the development of new specialized software solutions with user-friendly interfaces, which would make them more accessible, primarily to advisors, and then to agricultural producers.

The aim of the study was to use a multi-criteria decisionmaking method to make a rational choice for a new location for the distribution centre of agricultural products in the northeastern part of Bosnia and Herzegovina, specifically in five populated areas. The required criteria were selected based on experiences from previous research in this field, and decision-makers involved in the selection were engineers and technologists from the company in question. The results indicate that the criteria of construction cost and market connectivity gained the greatest importance, and Brčko was chosen as the location for the future distribution centre among the five populated areas. Additionally, the successful application of the used multi-criteria decision-making method, in this case, the CoCoSo method, was demonstrated. This could lead to improvements in making future business decisions within this economic sector.

The evolving customer demands have significantly influenced the operational landscape of agricultural companies, including the transformation of their supply chains. As a response, many organizations are increasingly adopting green supply chain practices. This paper focuses on the initial step of selecting a green supplier, using the case study of the Semberka Company. The objective is to align the company with customer requirements and market trends. Expert decision making, grounded in linguistic values, was employed to facilitate the transformation of these values into fuzzy numbers and subsequently derive rough number boundaries. Ten economic-environmental criteria were identified, and six suppliers were evaluated against these criteria. The fuzzy rough LMAW (Logarithm Methodology of Additive Weights) method was employed to determine the criteria weights, with emphasis placed on the quality criterion. The fuzzy rough MABAC (Multi-Attributive Border Approximation Area Comparison) method was then utilized to rank the suppliers and identify the top performer. The validity of the results was established through validation techniques and sensitivity analysis. This research contributes a novel approach to green supplier selection, employing the powerful tool of fuzzy rough sets. The flexible nature of this approach suggests its potential application in future investigations. The limitation of this study is more complicated calculations for the decision maker. However, this approach is adapted to human thinking and minimizes ambiguity and uncertainty in decision making, and in future research, it is necessary to combine this approach with other methods of multi-criteria analysis.

The aim of the study was to evaluate rural households from five different regions of Bosnia and Herzegovina based on predetermined economic, ecological, and sociological criteria, using assessments from five expert professionals in the field. The study employed the fuzzy multi-criteria decision-making method called TOPSIS to ensure research accuracy. The results indicated that the rural household “Radoja” received the highest rating, which could serve as a solid foundation for future rural tourism development in Bosnia and Herzegovina. Based on the obtained results, it is possible to conduct future research in other regions of the country, providing appropriate guidelines for the development of rural tourism in Bosnia and Herzegovina.

Crop insurance is used to reduce risk in agriculture. This research is focused on selecting an insurance company that provides the best policy conditions for crop insurance. A total of five insurance companies that provide crop insurance services in the Republic of Serbia were selected. To choose the insurance company that provides the best policy conditions for farmers, expert opinions were solicited. In addition, fuzzy methods were used to assess the weights of the various criteria and to evaluate insurance companies. The weight of each criterion was determined using a combined approach based on fuzzy LMAW (the logarithm methodology of additive weights) and entropy methods. Fuzzy LMAW was used to determine the weights subjectively through expert ratings, while fuzzy entropy was used to determine the weights objectively. The results of these methods showed that the price criterion received the highest weight. The selection of the insurance company was made using the fuzzy CRADIS (compromise ranking of alternatives, from distance to ideal solution) method. The results of this method showed that the insurance company DDOR offers the best conditions for crop insurance for farmers. These results were confirmed by a validation of the results and sensitivity analysis. Based on all of this, it was shown that fuzzy methods can be used in the selection of insurance companies.