Veljko Dmitrović

The rapid convergence of artificial intelligence (AI) and green energy (GE) is transforming sustainable business practices, energy management, and economic development. Although research in this interdisciplinary field has expanded considerably, its intellectual structure, thematic evolution, and business implications remain insufficiently understood. This study presents a comprehensive bibliometric analysis of AI and GE research from a business and economics perspective. Publications were retrieved from the Scopus and Web of Science databases using an expanded, transparent, and reproducible search strategy. Following PRISMA guidelines and predefined inclusion criteria, a final dataset of 7,301 publications was analyzed using Bibliometrix and VOSviewer to examine publication trends, influential authors, institutions, countries, journals, collaboration networks, and thematic structures. The results reveal a marked increase in scientific production after 2022, reflecting the growing integration of AI into renewable energy systems and sustainable development research. Scientific output is concentrated in countries with strong research capacity, sustained investment in digital innovation, and ambitious sustainability agendas. Keyword co-occurrence analysis identifies four dominant research themes: sustainability and energy policy, AI-driven forecasting and optimization, smart energy systems, and digital transformation for energy efficiency. The findings demonstrate that the field has evolved from predominantly technical applications toward a multidisciplinary research domain integrating business strategy, innovation management, sustainability, and energy economics. Unlike previous bibliometric studies based on narrower search strategies or smaller datasets, this study provides a transparent, large-scale mapping of the field and offers a more comprehensive understanding of its intellectual structure and emerging research directions. The findings provide valuable insights for researchers, policymakers, managers, and investors seeking to accelerate sustainable energy transitions and support long-term economic resilience.

This paper examines the determinants of financialdistress in the agro-industrial sector of the Republicof Serbia. The empirical analysis is based on paneldata for 20 large companies from the food productionsector in the period 2019–2024. Financial distress wasoperationalized using the revised Altman Z′ indicator,with an extended classification threshold (Z′ < 1.8). Binarylogistic regression was applied to assess the impact ofselected variables. The findings have shown that thecapital structure is the dominant determinant of financialdistress, while indicators of profitability and operatingcash flows do not show a statistically significant influence.At the same time, company size stood out as a significantfactor, with larger companies more likely to face financialdifficulties. The findings indicate that financial distressis not primarily conditioned by operational performance,but primarily by the structural characteristics of financingindicating the need for the development of integrative andmultidimensional analytical approaches in this area.

China’s export-oriented economic expansion has substantially influenced transport-sector CO₂ emissions, raising critical concerns about the environmental impacts of sustained industrial growth and global trade integration. Understanding the interplay between macroeconomic dynamics, trade composition, and industrial structure is essential for aligning economic development with climate mitigation objectives. This study examines transport-related CO₂ emissions in China over the period 1990–2023, employing a hybrid methodological framework that combines econometric modeling—including Autoregressive Distributed Lag (ARDL) bounds testing, Fully Modified Ordinary Least Squares (FMOLS), and Dynamic Ordinary Least Squares (DOLS)—with machine-learning techniques using Extreme Gradient Boosting (XGBoost) interpreted through SHapley Additive exPlanations (SHAP). The analysis confirms a long-run cointegration relationship between transport emissions and the selected macroeconomic variables. Short-run dynamics indicate a strong sensitivity of emissions to GDP growth, while long-run estimates reveal that higher export-to-GDP ratios and industrial value added contribute to reducing transport emissions, reflecting the efficiency gains from industrial upgrading and cleaner trade practices. By contrast, the expansion of medium- and high-technology exports increases emissions due to the energy- and logistics-intensive nature of high-value goods. The XGBoost model achieves high predictive performance, with an out-of-sample R² of 0.9975 and a Root Mean Square Error (RMSE) of 87.16, confirming the dominant contribution of medium- and high-technology exports to transport-sector emissions. The results underscore the critical role of aligning trade structure, industrial productivity, and low-carbon logistics within China’s policy agenda. Implementing strategies that enhance industrial energy efficiency and develop sustainable transport infrastructure can substantially reduce the environmental impacts associated with export-driven economic expansion.

Uopšteno posmatrajući, brojna odeljenja interne revizije, često mogu da manifestuju sklonost prema izbegavanju realizacije angažmana na poslovima revizije strateških planova organizacije čiji su deo. Deo internih revizora, takvu vrstu zadataka doživljava sa naglašenom dozom egzocentrizma, gubeći fokus sa suštinski važne tematike, sve pod uticajem spoljašnjih faktora koji su često neosnovani, neutemeljeni i bezrazložno nametnuti kao dominantno određujući. Imajući to na umu, predmet ovog rada je razmatranje revizije strateških planova organizacije, sagledavanjem šireg konteksta, kroz uvid u prednosti i nedostatke koji određuju karakteristike i rezultate takvog poduhvata. Glavni zaključak u radu je da revizija strateških planova organizacije treba da pronađe svoje mesto u godišnjim planovima odeljenja za internu reviziju i da i pored izraženih specifičnosti koje su naglašene od organizacije do organizacije, sve prednosti koje ona donosi, kako za organizaciju, tako i za pojedinca koji je deo organizacije i sve druge zainteresovane strane su višestruke i predstavljaju korist koja se nameće kao svrsishodna i rezidualno vredna za dugoročno poslovanje organizacije.

U današnjem sve složenijem i međusobno povezanijem svetu, organizacije i sistemi u različitim sektorima suočavaju se sa nivoima rizika bez presedana, u rasponu od finansijske nestabilnosti do ekoloških katastrofa i pretnji po sajber bezbednost. Kako učestalost i intenzitet ovih rizika rastu, postaje ključno ne samo da se identifikuju potencijalne ranjivosti, već i da se testira i izmeri otpornost sistema suočenih sa ovim izazovima. Otpornost na rizik se odnosi na sposobnost Sistema, bilo da se radi o organizaciji, infrastrukturi ili zajednici, da predvidi, apsorbuje, prilagodi se i oporavi od ometajućih događaja dok nastavi da efikasnofunkcioniše. Predmet rada je analiza koncepta otpornosti na rizik, naglašavajući važnost testiranja okvira i metodologija za procenu robusnosti sistema u različitim scenarijima rizika. Kroz sveobuhvatno testiranje rizika, zainteresovane strane mogu bolje razumeti snage i slabosti svojih trenutnih strategija, omogućavajući im da donesu informisane odluke o upravljanju rizikom, ublažavanju i prilagođavanju. Glavni zaključak u radu je da interna revizija može u znacajnoj meri da doprinese da se poboljšaju sposobnosti organizacija za testiranje otpornosti na rizik tako što jesnije definisati dizajn i implementaciju internih procedura i internih kontrola, kao i tako sto ce da generise pravovremene i jasne rezultate testova otpornosti.

This study conducts a comprehensive bibliometric analysis of research applying data envelopment analysis (DEA) to the evaluation of sustainability and performance in complex socioeconomic systems between 2010 and mid-2025. DEA has become an increasingly valuable tool for measuring efficiency, benchmarking practices, and supporting decision-making in contexts where sustainability challenges intersect with economic, environmental, and governance dimensions. To capture global research dynamics, we extracted and merged bibliographic data from Web of Science and Scopus, analyzing publication trends, thematic clusters, co-authorship networks, citation structures, and keyword co-occurrences using bibliometric tools such as VOSviewer and Bibliometrix. Our findings reveal a consistent growth trajectory of the field, with research outputs peaking in 2020 and subsequently diversifying across multiple thematic areas. Conceptual mapping highlights two dominant domains: (i) policy, governance, and planning and (ii) environmental, ecological, and management applications, both linked through the overarching theme of sustainable development. The analysis further underscores the geographic diversity of contributions, the concentration of knowledge in key publication outlets, and the increasing connectivity of international collaboration networks. By identifying thematic gaps and underexplored intersections, this study emphasizes the need for more interdisciplinary approaches that integrate bibliometric insights with practical sustainability outcomes. The results provide a structured overview of the field’s evolution, offering researchers and policymakers a valuable reference point for advancing DEA applications in sustainability research.

Research Question: This study examines the relationship between corporate debt and profitability, with a particular focus on the moderating effect of firm size. Motivation: The relationship between corporate debt and profitability has long been a subject of interest in both economic theory and empirical research. However, existing findings are often contradictory, particularly within the context of developing economies such as Serbia, where institutional, financial, and market structures may diverge significantly from those in more advanced economies. Understanding this relationship is crucial, as it directly impacts firms’ financial stability, investment decisions, and long-term competitiveness. In economies in transition, where access to capital is often limited and financial risks are elevated, identifying how leverage affects profitability—and under what conditions—can provide valuable insights for both corporate managers and policymakers. This study seeks to address this gap by examining the extent to which firm size influences the debt–profitability nexus, with a focus on whether larger firms possess higher capacity to absorb the risks and costs associated with leverage. Conceptual Framework: Profitability is the dependent variable and is measured by return on assets (ROA), defined as the ratio of net income to total assets. The main independent variable is corporate debt, measured as the ratio of total debt to total assets. Firm size (SIZE) is represented by the natural logarithm of total assets, while firm age and sales growth are included as control variables. Data: The research was conducted on a sample of companies operating within the territory of the Republic of Serbia, selected from the list of the most successful companies in 2023. The analysis covers the period from 2019 to 2023. After excluding certain firms from the sample, the final analysis was performed on 97 companies. Methods: Following descriptive statistics, correlation analysis was applied to determine relationships between variables. Two models were specified: one without interaction terms and one with interaction terms. For both models, panel regression analysis and fixed effects model (FEM) analysis were performed. Findings: Results from the model without interaction terms indicate that corporate debt has a significant negative impact on profitability within the examined sample. Although companies with higher asset values generally achieve higher ROA, an increase in firm size can have an adverse effect on profitability. The interaction model shows that firm size acts as a moderating factor in the relationship between debt and profitability. Contribution: The key contribution of this research lies in the introduction of firm size as a moderating variable in a panel regression framework—an approach that provides a more nuanced understanding of the interdependencies among financial indicators. By shedding light on these dynamics, the study offers practical implications for optimizing capital structure decisions and enhancing financial performance in developing economies.