The rapid advancement of Big Data and artificial intelligence (AI) has significantly transformed management accounting practices, necessitating a reevaluation of job profiles and skill-sets required for professionals in this field. This study explores managerial accounting practices in Romanian contexts, examining how digital technology aligns with competitive strategy, managerial efficiency, human resources constraints, and limited resources constraints. Grounded in technology determinism and the resource-based view theory, this research identifies factors influencing the successful implementation of and challenges associated with managerial accounting practices. A sequential mediation analysis investigates pathways wherein investments in human resources and constraints related to limited resources influence managerial advancement through digital technology and competitive strategy. This study emphasizes digital technologies’ role in optimizing costs, enhancing operational processes, and facilitating strategic decision-making. This study’s conclusions show that, even in situations with limited resources, digital transformation projects greatly improve managerial effectiveness and competitive strategy. The participants included 406 professional accountants from the Romanian accounting community. Practical implications for companies include the necessity for strategic planning in digital implementations to mitigate constraints and capitalize on opportunities for sustainable growth and competitive advantage. This report provides a path to optimize the potential of digital technology and gives practical recommendations for researchers and business leaders.

A bean counter is defined as an accountant or economist who makes financial decisions for a company or government, especially someone who wants to severely limit the amount of money spent. The rise of the bean counter in both public and private companies has motivated us to develop a Bean Counter Profiling Scale in order to further depict this personality typology in real organizational contexts. Since there are no scales to measure such traits in personnel, we have followed the methodological steps for elaborating the scale’s items from the available qualitative literature and further employed a cognitive systems engineering approach based on statistical architecture, employing cluster, factor and items network analysis to statistically depict the best mathematical design of the scale. The statistical architecture will further employ a hierarchical clustering analysis using the unsupervised fuzzy c-means technique, an exploratory factor analysis and items network analysis technique. The network analysis which employs the use of networks and graph theory is used to depict relations among items and to analyze the structures that emerge from the recurrence of these relations. During this preliminary investigation, all statistical techniques employed yielded a six-element structural architecture of the 68 items of the Bean Counter Profiling Scale. This research represents one of the first scale validation studies employing the fuzzy c-means technique along with a factor analysis comparative design.

The purpose of this study is to examine the factors that influence vaccination options, including vaccination against COVID-19, in order to develop a management algorithm for decision-makers to reduce vaccination reluctance. This paper’s primary objective is to empirically determine the relationships between different variables that correlate to non-vaccination behavior of the target population, as well as the implications for public health and situational management strategies for future vaccination intentions. We created a questionnaire to investigate the personal approach to disease prevention measures in general and vaccination in particular. Using SmartPLS, load factors for developing an algorithm to manage vaccination reluctance were calculated. The results shows that the vaccination status of an individual is determined by their vaccine knowledge. The evaluation of the vaccine itself influences the choice not to vaccinate. There is a connection between external factors influencing the decision not to vaccinate and the clients’ motives. This plays a substantial part in the decision of individuals not to protect themselves by vaccination. External variables on the decision not to vaccinate correlate with agreement/disagreement on COVID-19 immunization, but there is no correlation between online activity and outside influences on vaccination refusal or on vaccine opinion in general.

This paper examines the impact of social stratification on trust in recommender systems. Recommender systems have become an essential tool for users to navigate vast amounts of information online, but trust in these systems has become a concern. The focus of this study is to investigate whether social stratification, defined by socioeconomic status, affects trust in recommender systems. We first review the literature on trust in recommender systems and social stratification, highlighting gaps in the current research. We then describe the methodology used in our study, which involves the analysis of valid and consented responses received from 487 participants from different socioeconomic backgrounds, registered in an online survey. This study aimed to investigate the influence of social stratification, specifically income, on trust in recommender systems. Results showed a curvilinear relationship between income and trust in recommender systems, such that moderate income levels were associated with higher levels of trust, while both low- and high-income levels were associated with lower levels of trust. These findings suggest that income plays an important role in shaping users’ trust in recommender systems and highlight the need for future research to examine the complex interplay between social stratification and trust in technology.

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.

In this article we present aspects regarding the objective of the treasury budget, the stages of its preparation and the elaboration of the provisional financial statements. The purpose of the treasury budget consists of translating the expenses and income generated by various activities in collections and payments monetary terms. Its elaboration is the result of an exhaustive budgetary approach, completed by preparing the provisional financial statements, that must be coherent with the long-term planning activities existing in the enterprise. In other words, the treasury budget transforms the expenses and income of all previous budgets in collections and payments, notion which favours that of the monetary fluxes due date.