Serbia Research Articles

Rapid deep learning prediction model using satellite imagery for radiation accident Announcement system in Serbia

Radioactivity environmental monitoring with the help of the Radiation Accident Announcement System (RAAS) established in the Republic of Serbia is of vital importance for rapid response in the event of intervention dose values being reached such as Operational Intervention levels (OILs). There are cases of impossibility of using a ground-based model in order to predict the transport and spread of radiation during a nuclear accident such as the one in the Fukushima Daiichi nuclear power plant 2011. Modern technology has made it possible to use machine learning models with remote sensing data in addition (or an alternative) to atmospheric models with ground data collection methods. Deep learning (DL) model was developed and trained on a satellite-based cloud fraction dataset to forecast diurnal cloud drift. By forecasting the movement of clouds that are potential carriers of radioactive materials, decision-makers can provide an adequate response with an Action Plan in the case of nuclear and radiation accidents and incidents. Designed Application Programming Interface (API) has been developed and integrated between the DL model and the RAAS. In this way, the monitoring, data sharing and exchange processes were automated in order to trigger the DL model when an OILs value of 1 μSv/h is reached. The hyperparameter optimization process of the DL model was done with grid search and Particle Swarm Optimization (PSO) to achieve maximum performance on the data in a reasonable amount of time. The evolution metrics to monitor and measure the performance of the DL model were cosine similarity (CS) and structural similarity (SS) with the best score of 0.78282 and 0.27063 for grid search, respectively, while 0.27065 and 0.78282 for PSO, respectively. It can be concluded that remote sensing imagery with DL model is an alternative approach against a ground-based forecasting system, and is able to predict in near real-time independently of ground network system and data.

Special issue devoted to the IAPC-10 Meeting: Joint World Conferences on Physico-Chemical Methods in Drug Discovery and Development and on ADMET and DMPK

The present issue of ADMET and DMPK is dedicated to the IAPC-10 Meeting, which was organized as a joint event consisting of 10th World Conference on Physico-Chemical Methods in Drug Discovery and Develop¬ment and 6th World Conference on ADMET and DMPK. The meeting took place in the University of Belgrade Rectorate building, Belgrade, Republic of Serbia, September 4-6, 2023. IAPC meetings are organized as annual events in alternating European and East Asia locations. The topics covered the most advanced directions and new achievements in physico-chemical methods, which underlie almost all instrumental techniques used in the research processes in drug discovery and pharmaceutical development. Experimental determination of ADMET properties through the in vitro and in vivo assays was discussed as well as modern theoretical methods for computer-aided drug design. Ten sessions were organized, among which two special sessions: 1) Special Session on Solubility of Multi-Component Solids (Salts and Cocrystals), organized and co-chaired by Kiyohiko Sugano and Alex Avdeef, and 2) Special Session on the ADME properties and toxicity prediction by HPLC, organized and chaired by Klara Valko. Editorial

The resurgence of pertussis in Central Serbia in the period from June to December 2023

Abstract Background There was a registered increase in the number of confirmed pertussis cases in Central Serbia between June and December 2023. Among the possible causes of pertussis resurgence are increased awareness of pertussis among healthcare workers, availability of the sensitive RT PCR method in diagnostic, the limited duration of vaccine-induced immunity as well as decline of immunization coverage influenced by the COVID-19 pandemic. Methods The nasopharyngeal samples from clinics and primary care departments were transferred to Institute of Public Health of Serbia. DNA was extracted from each sample using the MagMAX Viral/Pathogen kit. The presence of B. pertussis was determined using two PCR assays, VIASURE Bordetella Real Time PCR Detection Kit and Bosphore B. pertussis/parapertussis Genotyping Kit, Anatolia Geneworks. Results RT-PCR confirmed a total of 338 pertussis cases in Institute of Public Health of Serbia during the observed period. Most of confirmed cases were among children 9-14 years old (49,7%) followed by infants younger than 12 months (21,9%). The more severe cases were among the unvaccinated and uncomplete vaccinated infants, 78,4% of which required hospitalization with two deaths in this age group. Conclusions Based on the analysis of the obtained results, we can highlight the importance of using sensitive methods in pathogen detection. Rapid diagnosis, laboratory confirmation and notification ensure early public health intervention to minimize the spread of disease. Despite long tradition of mandatory immunization against pertussis in the Republic of Serbia, wanning of vaccine induced immunity poses potential risk for the resurgence of pertussis. For pertussis control, in the future, it will be essential to achieve high immunization coverage as well as to introduce a booster dose of pertussis containing vaccine for children aged 14 and to implement vaccination of pregnant women. Key messages • For the better pertussis control vaccination of adolescents and adults, as well as vaccination of pregnant women should be considered in the future vaccination policies. • Clinicians should consider pertussis in the differential diagnosis of persistent cough illness in people of all ages, even those previously immunized.

The impact of artificial intelligence on labor relations

With the rapid development of technologies, particularly artificial intelligence, which poses a threat to all humanity, questions arise regarding its boundaries and its perspective on labor relations. Given the breadth of its impact, the potential influence on labor relations is unknown. The scope of labor law issues that this phenomenon brings is multifaceted and remains an enigma in our labor law area, and the legislator in the Republic of Serbia has not prepared a response in line with European trends. The potential impact on labor relations, and later through some basic labor law procedures that ac-company labor relations, has given the impression in the professional public of undermining employees and eroding their fundamental rights (individual and collective). Artificial intelligence accumulates its full impact on labor relations at the expense of the quality of labor relations. Many world economies rely on and see the benefits of the market offered by artificial intelligence. The rights derived from labor relations in the future will be subject to revision and reconsideration. Individual and collective labor law, the result of centuries of struggle by humanity, will be tested for maturity and adaptability in the 21st century. The authors aim to elucidate the impact of artificial intelligence and how it affects labor relations in the 21st century, as well as to identify the elements–institutes of labor law most affected by this “tool” or “weapon,” as some experts call it.

Gastronomic Identity Factors in the Function of Sustainable Gastronomy: A Case Study of Tourist Destinations in the Republic of Serbia and Bosnia and Herzegovina

Gastronomic identity is a crucial segment of sustainable gastronomy and its successful positioning in the tourism market. As such, it calls for the creation of a suitable SusGastroIdentity scale that would identify influential factors. The research investigated the opinions of the employees in catering establishments in two tourist destinations in the Balkans: Fruška Gora Mountain, a tourist area in the Autonomous Province of Vojvodina in Serbia, and Jahorina Mountain, a tourist area in the Republic of Srpska entity in Bosnia and Herzegovina. The study involved 606 participants, 66% of whom work in à la carte restaurants. Of these participants, 68% hold operational roles in hospitality establishments, and 58.3% have over 5 years of experience in the hospitality industry. After conducting a survey using a questionnaire and performing appropriate statistical analysis of the responses, four factors of gastronomic identity and sustainable gastronomy were defined: geographic and cultural characteristics of gastronomy, gastro-tourism events, economic aspects of business operations, and commercial aspects of business operations. The present research has shown that employees in hospitality and tourism perceive geographic and cultural characteristics and the economic aspects of business as the significant factors of gastronomic identity that affect both the sustainability of gastronomy in tourism and the tourist destination itself.

The Forecasting Model of the Impact of Shopping Centres in Urban Areas on the Generation of Traffic Demand

The increase in traffic caused by new development affects the change in traffic conditions on the surrounding roads, and shopping centres are significant traffic generators. The development of local travel generation rates and their characteristics for individual land uses from the aspect of traffic demand is a reliable way to plan traffic in order to come up with preventive solutions to traffic problems, that is, prevention of possible negative consequences on traffic conditions in the street network occurring due to the construction of shopping centres. One of the main aims of this paper is to develop a model for objective assessment of the generated traffic demand for significant changes in land use, such as the construction of shopping centres in medium-sized towns. All these would be steps in the right direction for the promotion of reliable traffic planning and adoption of TIA for every new development before a decision regarding the change in land purpose has been made. This kind of process still has not been established systematically in either Bosnia and Herzegovina and the Republic of Serbia, or in surrounding countries. This paper focuses on the formulation of a model for determining the volume of traffic generated by shopping centres in medium-sized towns in two countries of the Southeast Europe region. The survey was conducted in eight different locations (cities) where there are shopping centres with common facilities. The analysis showed that the number of visitors and vehicles attracted by the shopping centre zone can be determined by a model based on a linear regression analysis. The analysis included exploring several different factors of trip generation in shopping centres, including the relationship between trip generation and combinations of several independent variables. The verification of the model was conducted in real conditions of the traffic flow generated by a shopping centre which was not the analysis subject when forming the forecasting model. In this way, the validity of the proposed model is credibly assessed. The developed model can be applied in the procedures of planning the construction of shopping centres in medium-sized cities in the Republic of Serbia and Bosnia and Herzegovina, and wider, in the region of Southeast Europe, in order to estimate the volume of generated traffic demand, that is, its impact on the conditions of traffic on the surrounding traffic network.

Design and operational features of an active condensation system for enhanced energy efficiency in a biomass-fired district heating plant

The study addresses the design and operational features of an active condensation (AC) system aimed at improving the energy efficiency of a 3rd generation district heating (DH) plant. Several similar biomass-utilizing plants have recently been built in the Republic of Serbia. The plant is equipped with biomass-fired boilers totaling 2 MW capacity, utilizing varying qualities of wet wood chips. The goals are: (i) to determine optimal constant and variable quench temperatures; (ii) to calculate the electricity consumption of ancillary devices and assess their impact on AC system performance; (iii) to evaluate the effect of biomass moisture variations on system size and performance; (iv) to assess the economic viability of integrating the AC system; and (v) to establish selection and design criteria for the heat pump (HP). For a given commercial HP, an optimal quench temperature exists, dependent on the minimal temperature lift required by the HP. This temperature can be calculated simply by subtracting the minimal HP lift from the lowest possible temperature that the HP can supply to a DH system at the average outdoor temperature. Consequently, an optimal variable quench temperature exists that should be adjusted to enable the HP to operate with its minimal temperature lift.

Am I Successful? An Answer of Women Entrepreneurs

The success of women entrepreneurs is almost uniformly judged by financial criteria. As a result, the so-called underperformance hypothesis is put forward. However, this hypothesis may be ill-founded, and it may serve to reproduce and reinforce myths about women and entrepreneurship. It is important to understand what success means for women entrepreneurs operating in a given socio-economic context before we label them as underperformers. Moreover, although the importance of the contextual approach is recognized, some contexts are under-researched and less visible. Results from North America and Western Europe cannot be replicated in other contexts, especially in developing countries or patriarchal societies. For different contexts, we need new evidence. And this new evidence can make us realize that some concepts need to be revised to capture the collective vision of entrepreneurs. Instead of one paradigm, we should recognize the existence of a diversity of forms, motives, and understanding of success in entrepreneurship, as well as the contexts in which it occurs, to ensure holistic knowledge on entrepreneurship. To respond to these challenges, the research is conducted on a sample of 300 female entrepreneurs in the Republic of Serbia who operate in manufacturing. The respondents were asked to state what business success means to them and then to subjectively assess how successful they are according to the same criteria. In this way, the research results reveal how successful women entrepreneurs are, but measured in a way that reflects their perceptions of success. Results show that the importance that a certain criterion has for female entrepreneurs as an indicator of success is positively related to their success measured by that criterion. Not imposing on women entrepreneurs the usual measures of business success, the paper responds to calls to de-masculinize women’s entrepreneurship research by introducing gender-specific variables and widening the set of measures of success. In doing so, it is placed in specific and under-researched contexts of a developing country and manufacturing industry. In this way, the paper further contributes to the enrichment of the entrepreneurship knowledge base.

The Institution of the Prime Minister in the Republic of Serbia: Its Systemic Evolution and Constitutional Practice

The article examines the evolution of the political position of the head of government institution in the Serbian state. The analysis covers the different models of government that have developed in Serbia over the last 180 years. During the monarchical period, the prime minister’s position was a function of his relationship with the king and the political alignment in parliament. In turn, during the period of popular democracy and socialism, the prime minister’s position depended on the political alignment at the top of the communist elite. It is also an interesting exercise to analyse the evolution of the post-1990 position of the head of government, especially in the context of the new constitutional order and the rather turbulent changes on Serbia’s political scene.

The Mediation Effect of Customer Satisfaction in the Relationship between CSR and Financial Performance: An Empirical Study in Large Companies in Serbia

Although corporate social responsibility (CSR) can be examined from the point of view of the fundamental philosophy of business and society, many companies focus solely on profit. The main goal of this research is the investigation of the relationship between CSR and organizational financial performance, and the role of customer satisfaction in the proposed relationship. To investigate the proposed relationships, PLS–SEM analysis was performed using the statistical software Smart PLS. The sample used for this study consists of 165 large companies that operate in the Republic of Serbia, each with more than 250 employees (large organizations). The obtained results showed that in companies in Serbia, there is a positive and statistically significant relationship between CSR and customer satisfaction and a positive but statistically insignificant relationship between CSR and financial performance. Regarding the mediating role of customer satisfaction in explaining the relationship between CSR and financial performance, a positive full mediation relationship was found. Theoretical and managerial implications are also provided.

COMPARATIVE ANALYSIS OF THE COMPUTER VISION SYNDROME BETWEEN THE DEVELOPED EU COUNTRIES AND REPUBLIC OF SERBIA

It is hard to envisage any business activity nowadays without the use of computers. The users who in their work utilize computers or some other displays for viewing electronic contents are exposed to the computer vision syndrome effects. This paper defines the computer vision syndrome and explains occurrences of the syndrome, setting out also its consequences. Analysis has been made of the viewpoints of users from the developed EU countries regarding the computer vision syndrome. Comparison has been made of the obtained data with the data showing viewpoints of the users in the Republic of Serbia. The aim of this analysis is to form a comprehensive picture of the computer vision syndrome issues. At the end of the paper, solutions are depicted for reducing the consequences and preventing the computer vision syndrome occurrences.

LEGAL ASPECTS OF A BANK GUARANTEE AS A FINANCIAL SECURITY INSTRUMENT

A bank guarantee is an important instrument for securing financial obligations in legal transactions, creating security and trust between the contracting parties. This paper analyzes the legal aspects of a bank guarantee as a security interest, including its legal nature, types of guarantees, as well as the rights and obligations of the contracting parties. Special focus is placed on the analysis of domestic legislation in the Republic of Serbia and comparative legal practice, highlighting the similarities and differences of approaches across different jurisdictions. The paper also examines the role of bank guarantees in international transactions with reference to relevant international conventions and regulations, especially in the context of globalization of markets. The aim of the paper is to provide a comprehensive overview of the legal framework that governs the issuance and enforcement of bank guarantees and to identify challenges and opportunities for improving this financial instrument in practice. Based on the analysis, recommendations are made for legal entities to optimize the use of bank guarantees in business transactions.

Students’ Perceptions of Workplace Robots in the Republic of Serbia

Research Question: The key research question is what the key positive and negative perceptions of students from the Republic of Serbia regarding workplace robots are. Motivation: Academics, practitioners, and decision-makers are more and more interested in the impact of new technological solutions in the field of robotics on organizations and their functioning. Ongoing technological advancements have accelerated the adoption and use of robots in the workplace. As a result, organizations that plan to introduce robots should consider all effects on employees, both positive and negative. Idea: The main idea is to examine and analyse the perceptions and attitudes of students from the Republic of Serbia regarding robots at the workplace. The results of this study regarding students' perceptions and attitudes towards robots in the workplace are crucial for the future of work and job design. Data: Data were collected via online questionnaire consisting of five profile questions and 13 statements organized in two five-point Likert scales. From January to March 2023, the questionnaire was completed by 164 students from the Republic of Serbia. Tools: The collected answers were analysed using the Statistical Package for Social Sciences – SPSS, version 21.0. (Armonk, NY: IBM Corporation). The Cronbach's Alpha coefficient, Kolmogorov-Smirnov test, descriptive statistics, student t-test and one-way ANOVA test was used for data analysis. Findings: Research results showed that most respondents believe that robots can do dangerous jobs that humans cannot, that robots can free humans from routine and monotonous jobs, and that humans will have more time for creative tasks. Robots in the workplace, on the other hand, will have some negative consequences. Many respondents agree that working with robots without people would make them feel lonely; robots would not know how to react in some unexpected circumstances; and they are not as flexible and mobile as humans. Contribution: The findings of this study could make a significant contribution to a better understanding of students’ attitudes towards robots in the workplace and they may help decision makers, employers, leaders, and managers on how to increase workplace acceptance of robots.

Unveiling the potential of a novel portable air quality platform for assessment of fine and coarse particulate matter: in-field testing, calibration, and machine learning insights.

Although low-cost air quality sensors facilitate the implementation of denser air quality monitoring networks, enabling a more realistic assessment of individual exposure to airborne pollutants, their sensitivity to multifaceted field conditions is often overlooked in laboratory testing. This gap was addressed by introducing an in-field calibration and validation of three PAQMON 1.0 mobile sensing low-cost platforms developed at the Mining and Metallurgy Institute in Bor, Republic of Serbia. A configuration tailored for monitoring PM2.5 and PM10 mass concentrations along with meteorological parameters was employed for outdoor measurement campaigns in Bor, spanning heating (HS) and non-heating (NHS) seasons. A statistically significant positive linear correlation between raw PM2.5 and PM10 measurements during both campaigns (R > 0.90, p ≤ 0.001) was observed. Measurements obtained from the uncalibrated NOVA SDS011 sensors integrated into the PAQMON 1.0 platforms exhibited a substantial and statistically significant correlation with the GRIMM EDM180 monitor (R > 0.60, p ≤ 0.001). The calibration models based on linear and Random Forest (RF) regression were compared. RF models provided more accurate descriptions of air quality, with average adjR2 values for air quality variables in the range of 0.70 to 0.80 and average NRMSE values between 0.35 and 0.77. RF-calibrated PAQMON 1.0 platforms displayed divergent levels of accuracy across different pollutant concentration ranges, achieving a data quality objective of 50% during both measurement campaigns. For PM2.5, uncertainty ( ) was below 50% for concentrations between 9.06 and 34.99μg/m3 in HS and 5.75 and 17.58μg/m3 in NHS, while for PM10, it stayed below 50% from 19.11 to 51.13μg/m3 in HS and 11.72 to 38.86μg/m3 in NHS.

Improving Air Quality Data Reliability through Bi-Directional Univariate Imputation with the Random Forest Algorithm

Forecasting the future levels of air pollution provides valuable information that holds importance for the general public, vulnerable populations, and policymakers. High-quality data are essential for precise and reliable forecasts and investigations of air pollution. Missing observations arise when the sensors utilized for assessing air quality parameters experience malfunctions, which result in erroneous measurements or gaps in the dataset and hinder the data quality. This research paper presents a novel approach for imputing missing values in air quality data in a univariate approach. The algorithm employs the random forest (RF) algorithm to impute missing observations in a bi-directional (forward and reverse in time) manner for air quality (particulate matter less than 2.5 μm (PM2.5)) data from the Republic of Serbia. The algorithm was evaluated against simple methods, such as the mean and median imputation methods, for missing observations over durations of 24, 48, and 72 h. The results indicate that our algorithm yielded comparable error rates to the median imputation method for all periods when imputing the PM2.5 data. Ultimately, the algorithm’s higher computational complexity proved itself as not justified considering the minimal error decrease it achieved compared with the simpler methods. However, for future improvement, additional research is needed, such as utilizing low-code machine learning libraries and time-series forecasting techniques.

Performances of the e-Nauka Portal in the Republic of Serbia and Its Significance for Researchers

In recent years, digitalization has been recognized as a significant and necessary process that leads to better results, both in the education and in the scientific research. The legal and strategic framework in the Republic of Serbia follows the modern trends of the concept of open science, open knowledge, digital transformation and a unique digital format of scientific production. The Ministry of science, technological development and innovation, in cooperation with the Office for information technology and electronic administration, created the necessary conditions for dynamic the development of the scientific research and innovation system, especially in relation to the digitalization process and the establishment of an information platform, in the form of a unified national information system of scientific research activities: eNauka [eScience]. The concept of eNauka is an innovative tool that improves the efficiency and transparency of scientific processes in Serbia. The eNauka portal in the Republic of Serbia is dedicated to promoting scientific research, innovation and academic achievements within the scientific community of the Republic of Serbia. This portal provides access to scientific articles, research papers and academic publications authored by researchers from Serbia, which enables the spread of knowledge and the encouragement of scientific cooperation within the country. The eNauka portal was opened in full capacity for all active researchers in Serbia on July 3, 2023, and contains data on scientific research organizations in the Republic of Serbia, researchers and their scientific results. The goal of this paper was to bring closer to the academic community the capabilities and performance of the eNauka portal, its structure, the way and importance of data editing, with special reference to issues related to researchers’ profiles and their editing. The paper is methodologically based on a theoretical, preliminary desk analysis of relevant contemporary standpoints in domestic and foreign theory, a normative analysis of current legislative sources, an inductive and deductive approach in researching the operational performance and advantages of the eNauka portal, as well as the quantitative analysis of relevant statistical indicators of relevant parameters regarding the profile that each researcher has on the eNauka portal. The results include the analysis of data related to editing the researcher’s profile and the opportunities offered by the eNauka portal. The conclusion refers to the importance and advantages of the eNauke portal. Finally, it should be noted that one of the key functions of eNauka is the evaluation of scientific results. More precisely, the system provides the possibility of monitoring and evaluating research results, which is of great importance for the academic community.

The Effects of the Characteristics of Catering Establishments and Their Managers on the Offering of Dishes Prepared with Traditional Food Products in Bačka Region, Serbia

Traditional food products comprise an important part of the gastronomic identity of every nation. Their significance for national culture is major, which is why they are increasingly studied and included in the development strategies of many countries. This research focuses on the factors—economic, sociocultural, ecological, and tourism—that influence the offering of dishes made with traditional food products. The objective of the research is to examine whether certain characteristics of catering establishments in the Bačka region (Republic of Serbia) and their managers affect the appraisal of the factors that affect the offering of dishes prepared with traditional products. By conducting a survey (n = 187) and analyzing the data using the non-parametric techniques of the Mann–Whitney and Kruskal–Wallis tests, it was found that, although all the factors have a significant influence on the offering of dishes prepared with traditional food products, tourism-related factors were distinguished as the most important. The research also showed that the characteristics of managers like the length of work experience in hospitality, employment tenure at the specific establishment, the work position of the respondent, as well as the type of gastronomic offering and the location of the catering establishment affected the appraisal of the factors that influence the offering of dishes prepared with traditional products.

Innovative Approaches in Hotel Management: Integrating Artificial Intelligence (AI) and the Internet of Things (IoT) to Enhance Operational Efficiency and Sustainability

The integration of artificial intelligence (AI) and the internet of things (IoT) is bringing revolutionary changes to the hospitality industry, enabling the advancement of sustainable practices. This research, conducted using a quantitative methodology through surveys of hotel managers in the Republic of Serbia, examines the perceived contribution of AI and IoT technologies to operational efficiency and business sustainability. Data analysis using structural equation modeling (SEM) has determined that AI and IoT significantly improve operational efficiency, which positively impacts sustainable practices. The results indicate that the integration of these technologies not only optimizes resource management but also contributes to achieving global sustainability goals, including reducing the carbon footprint and preserving the environment. This study provides empirical evidence of the synergistic effects of AI and IoT on hotel sustainability, offering practical recommendations for managers and proposing an innovative framework for enhancing sustainability. It also highlights the need for future research to focus on the long-term impacts of these technologies and address challenges related to data privacy and implementation costs.

URBAN PLANNING AND THE URBANISATION PROCESS IN SERBIA IN THE EARLY 1950s

After suffering extensive damage caused by the Second World War, Serbia went through a reconstruction period. Between 1944 and the mid1950s, the government prioritised economic growth and worked on rebuilding and modernising the infrastructure, urban structures, and systems. Urban planning was seen as crucial in creating the conditions for state development. Societal and five-year plans, supported by urban plans, enabled accelerated economic progress and growth. The urban planning profession was institutionalised, with planning theory and practice introduced alongside social, economic, and political changes. Through an examination of the activities of the Urban Planning Institute of the People’s Republic of Serbia, established in 1946, this paper rethinks the link between urban planning and the social aspect of the planned economy in response to the rapid urbanisation and industrialisation of cities.

Interdependent Influences of Reverse Logistics Implementation Barriers in the Conditions of an Emerging Economy

This research paper aims to investigate the interdependent influences of barriers to implementing reverse logistics in the broad spectrum of processing activities in the conditions of an emerging economy. An effort was made to approach these barriers (i.e., organizational and management barriers, technical and technological barriers, and economic, financial, and market barriers) based on the relevant literature, predominant attitudes, and experts’ opinions, thus contributing to the body of knowledge in this domain. Determining the intensity of interdependent influences and the importance of barriers for implementing reverse logistics was performed to determine the most important (key) barriers that can be practically applied as guidelines for decision making. The Fuzzy DEMATEL method was used to determine the intensity of these influences on a sample of manufacturing companies in the Republic of Serbia. The results indicate that the most critical barriers to the successful implementation of reverse logistics are a lack of management support and cooperation with scientific institutions and professional associations to acquire knowledge and follow trends in the field.