Ljubomir Obradović

This paper investigates the relationship between monetary policy and consumer price inflation in nine Southeast European (SEE) economies, with the aim of identifying the key channels through which monetary policy influences inflation dynamics. The analysis is based on an annual panel dataset covering the period 2007–2022. Static panel econometric techniques are applied, combining fixed-effects and random-effects estimators with robust standard errors. Model validity is assessed through cross-sectional dependence tests, panel unit-root tests and the Hausman specification test. The model includes lending interest rates, exchange rates and broad money (M3), alongside control variables such as producer price inflation, unemployment, adjusted net income per capita, domestic credit and foreign direct investment. The results indicate that lending interest rates exert a strong positive and statistically significant effect on inflation, consistent with Neo-Fisherian dynamics under uncertainty. Producer price inflation, domestic credit and foreign direct investment also show positive and significant effects, while broad money (M3) displays a negative coefficient, reflecting structural characteristics and high collinearity with credit aggregates in SEE financial systems. By providing a harmonized multi-country dataset and a comprehensive panel diagnostic framework, the study contributes new empirical evidence on the non-standard transmission of monetary policy in transition economies and offers policy-relevant insights for countries aligning their monetary frameworks with European Central Bank practices.

With its rapid development, artificial intelligence (AI) has become a significant factor influencing contemporary business, with important implications across various organizational domains. By mapping the literature on the impact of AI on modern business, this article seeks to identify relevant studies and classify them according to key areas of application, including business efficiency and innovation, user experience, data analysis and decision-making, as well as issues related to ethics, security, and the risks of AI adoption. The study is based on a systematic approach to reviewing existing literature, applying established scoping review methodologies to identify and select relevant studies and research. We have highlighted certain limitations and gaps in the existing body of research, which could serve as a foundation and starting point for further investigation. Finally, the article presents a set of conclusions and proposes potential directions for future research.