Recently, as it is known, the evaluation of the efficiency of agricultural enterprises is being more and more performed on the basis of multi-criteria analysis. With this in mind, this paper analyzes the efficiency of agricultural enterprises in Serbia based on the WASPAS method. The goal and purpose of this is to address this issue as thoroughly as possible and propose adequate measures to improve the efficiency of agricultural enterprises in Serbia in the future. The obtained results of empirical research using the given method show that the efficiency of agricultural enterprises in Serbia has recently significantly improved. It was the best in 2018. It was positively influenced by numerous macro and micro factors.

As our country has been opening itself more to foreign capital, foreign banks have brought their paradigm of efficient business methods in the banking system of the Republic of Serbia. This paper shows the seven-year analysis of the time series based on the ratio indicators of liquidity and profitability of the 10 largest banks doing business in the Republic of Serbia for the period between 2010 and 2017. In this research we used data from quarterly reports issued by the National Bank of Serbia and the selection criteria for banks was the amount of total net assets. As the percentage of participating banks' share is 77.1% of the total net assets of all banks operating in the Republic of Serbia, the values obtained approximate the performance of the entire banking system to a very good extent. The objective of this paper is to interpret these indicators in the aim of supporting the decision-making process concerning the credit-based and other finance-based relationships with clients so as to demonstrate whether monitoring of monetary authorities needs to be raised to a higher level, assuming that in the observed period the banking system of the Republic of Serbia was stable.

Under the influence of different factors, the dynamics of the size of the operating profit margin of food trading companies in Serbia varies from comparable global food retailers in various countries. Based on the obtained results of empirical research, we can also conclude that the operating profit margin of the leading food trading companies in Serbia is lower than the in analyzed comparable food retail trade companies from the developed market economies. It points to the conclusion that it is necessary to efficiently manage revenues, costs, profit, assets, and financial structure in order to improve the performance of food trading companies in Serbia in the future. In order to increase the operating profit margin, as a measure of long-term performance, it is necessary to manage the financial structure of the food trading companies in Serbia as effectively as possible. The main objective of this paper is to apply dynamics of size and structure of operating margin of global retailers in Serbia by applying accounting methodology based on data from annual financial statements. It is an increasingly significant non-standard indicator of their performance. Therefore, this indicator will receive increasing attention in the future.

This paper analyses the business operation of trade companies in the Republic of Serbia during the Covid-19 pandemic and the impact of the crisis caused by this virus on the work of these companies. Namely, this crisis has caused serious problems in a short period in most sectors and altered the way they do business. It can be said that to a certain extent it caused damage to trade companies, with the effect of the pandemic differing by trade segments. For example, trade companies selling food products even achieved positive results in 2020, when compared to 2019. Accordingly, this paper aims to perceive the manner of business operation and achieved economic results of trade companies that operate in the territory of the Republic of Serbia during the period of existence of the Covid-19 virus.

Modern trends operating from the environment require a different shaping of the organizational structure of the company. Accordingly, instead of traditional forms, more flexible organizational structures appear that are based on the characteristics of organic design. The emphasis is primarily on accepting change, decentralization of decision-making, a wider range of control, teamwork, adequate organizational culture, good interpersonal relationships, continuous learning and innovation development. Technological progress, scientific achievements, and thus the even greater need for continuous learning and acquiring new knowledge, as important characteristics of the modern business environment, have had the greatest impact on shaping the organizational structure of the company. The fact that information technology and knowledge are the basis of new organizational forms speaks in favor of that. Globalization has also played a role in creating the conditions for changing the organizational structure of companies, as well as the time of the COVID 19 pandemic. Organisations have been forced to do business differently and business processes have had to change rapidly in order for organisations to survive. The aim of this work is to indicate the fundamental trends that operate from the business environment and condition the need for the application of more flexible organizational forms. In addition, the aim of the paper is to point out the characteristics of organizational models that have emerged under the influence of these trends.

This paper examines the profound impact of Artificial Intelligence (AI) on the global economy, exploring its transformative effects across various sectors, the job market, and overall economic growth. The study begins by tracing the evolution of AI technology and its current state, providing context for its economic implications. It then delves into AI's influence on key industries such as manufacturing, finance, healthcare, and retail, highlighting how AI is driving innovation and efficiency. The research addresses the complex dynamics of AI in the job market, discussing both job displacement and creation, and the changing skill requirements in an AI-driven economy. The paper also analyzes the potential economic benefits of AI, including increased productivity, new business models, and projections for economic growth. However, it also confronts the challenges and concerns associated with widespread AI adoption, such as income inequality, data privacy issues, and regulatory hurdles. Furthermore, the study explores AI's role in global economic competition, examining how nations are positioning themselves in the AI race and the potential for shifts in economic power. The paper concludes by outlining strategies for preparing for an AI-driven economy, including education and workforce training initiatives, government policies, and business adaptation strategies. It also provides a future outlook, considering various scenarios for AI's long-term economic impact. This comprehensive analysis aims to provide a balanced view of AI's economic implications, offering insights for policymakers, business leaders, and individuals navigating the AI-driven economic landscape. The paper underscores the importance of harnessing AI's potential while addressing its challenges to ensure a prosperous and equitable economic future.