This study examines the issue of understanding management accounting practices in Romanian financial and accounting service firms, a subject of significant relevance due to the influence of accounting on organizational decision-making and strategic planning. The research examines 21 distinct management accounting practices, utilizing hierarchical clustering analysis refined by the Bayesian Information Criterion (BIC) to discern patterns and classifications within these practices. The findings indicate eight unique clusters, distinguished by differences in cluster size, withincluster heterogeneity, total within-cluster sum of squares, and Silhouette scores, which explain the diversity of practices and their organizational implications. The research enhances the literature by delineating the present state of management accounting practices in Romania and providing a more refined comprehension of the interrelationships among these practices, as guided by institutional theory. This method surpasses other attempts by emphasizing the diversity within clusters, uncovering distinct traits and strategic consequences. The findings indicate that various groupings of practices demonstrate particular patterns of adoption and utilization, which might affect firms’ strategic decision-making processes. These insights facilitate future research focused on examining the drivers and effects of accounting methods across various institutional contexts.

Research and Development Station for Cattle Arad is a public institution of national interest and its main activity is research and development in biotechnology and livestock breeding. The purpose of this paper is to analyze and improve through recommendations, the management applied on the livestock-breeding farm from the station. We are showing at first glance, the following important aspects: methods and techniques used by senior management and livestock at the farm are not up-to-date both morally and technology, which are also partly used. The station has a hierarchical - functional organizational, but nevertheless, the information system is underdeveloped. Also using such authoritarian management style promotes cooperation resort management, consulting and delegation between the chambers, but in a way inefficient. The role and the performance of the management system of the breeding farm is a decisional component with a privileged role. No other element of the resort management has a specificity so obvious and so great of an impact on all plans and performance results. The strengths and weaknesses of an institution of this kind are described in the literature that we use to test, draw and make recommendations for the future growth potential of the station, both in terms of managerial, economic -financial and in terms of the quality of work processes and finished products. To achieve a practical study, we present the relevant results after applying the latest technology management, reporting and decision-making for some time on senior management, livestock breeding management and on cooperation between these compartments.

The purpose of this paper is to analyze and improve through recommendations the revenue management, in this case the turnover, applied by changing the method of feeding calves with age ranging from 0 to 6 months from the zootechnical farm at the Development and Research Center for Cattle Breeding from Arad. This will be achieved by using an approved and certified feed substitute (milk powder) to feed the calves instead of the cow’s milk so that the milk produced by the dairy cows can be delivered to customers. The differences between the cost of buying and feeding calves with this substitute and the income from selling milk are substantial. By this method, the income of the resort and that of any zootechnical farm will be maximized without endangering the health of the calves or the end-users. At the same time, we will disseminate the results obtained by applying this method in 2016, the results being conclusive.

Artificial intelligence (AI) has emerged as a transformative force within the digital economy, reshaping how organizations create value, compete, and innovate. For small and medium-sized enterprises (SMEs), AI represents not only a technological advancement but also a strategic resource capable of generating sustainable competitive advantages. This study explores the role of artificial intelligence as a driver of competitiveness for SMEs operating in increasingly digitalized markets. It examines the mechanisms through which AI technologies enhance operational efficiency, support data-driven decisionmaking, improve customer experiences, and foster innovation. The research highlights both the opportunities and challenges associated with AI adoption in SMEs, including resource constraints, skill gaps, organizational readiness, and ethical considerations. By integrating theoretical perspectives with practical implications, the paper emphasizes that AI is not merely a tool for automation but a catalyst for business model transformation and strategic differentiation. The findings suggest that SMEs leveraging AI effectively can achieve greater adaptability, productivity, and market responsiveness, thereby strengthening their position within the digital economy. The study contributes to a deeper understanding of how emerging technologies influence competitive dynamics and provides insights for managers, policymakers, and researchers interested in digital transformation and SME development.