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.

This study examines the key drivers behind the adoption of artificial intelligence (AI) in the accounting profession, emphasizing the influence of AI-related knowledge, personality traits, and professional roles. By applying Decision Tree Regression analysis to survey data from accounting professionals, our research identifies AI knowledge as the strongest determinant of AI adoption, underscoring the importance of expertise in technology acceptance. While personality traits play a secondary role, extraversion and openness emerge as significant factors influencing adoption intentions. The study further explores AI applications in financial auditing, tax compliance, and fraud detection, clarifying the specific accounting domains impacted by AI integration. These findings offer valuable guidance for policymakers, educators, and business leaders aiming to equip the accounting workforce with the necessary skills and mindset to navigate the AI-driven transformation of the profession.

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 acceptance of artificial intelligence (AI) among professionals in accounting and auditing by applying the Technology Acceptance Model (TAM). The research addresses the broader question of how AI technologies are integrated into professional decision-making in financial services, with a focus on the determinants that shape user acceptance. A standardized survey, consisting of 21 items designed to measure TAM components, was distributed to accounting and auditing professionals. Data were analyzed through confirmatory factor analysis to validate the construct structure, and Pearson’s correlation and network analyses were used to identify relationships among variables. The results confirmed a robust seven-factor model with significant interrelations, highlighting AI knowledge as a central variable influencing perceived usefulness (PU), self-efficacy, and intention to use AI. These findings demonstrate that professional familiarity and confidence in AI tools are key drivers of technology acceptance. The study concludes that enhancing AI literacy can strengthen organizational readiness for digital transformation. Additionally, the research underscores the contribution of women-led scholarship in promoting responsible and inclusive approaches to AI adoption within the accounting and auditing sectors.

Recent global events have slowed progress toward achieving the Sustainable Development Goals (SDGs), making robust sustainability reporting (SR) systems critical for monitoring and corrective actions. While research on the link between corporate sustainability performance (CSP) and corporate financial performance (CFP) is extensive, the specific role of sustainability reporting as a communication channel remains insufficiently explored. Therefore, the objective of this paper is to address this gap in the literature by assessing the relevance of sustainability reporting for modeling the relationship between CSP and CFP. In this study, a univariate meta-analysis based on a PRISMA screening framework was performed to assess the unidirectional relationship between SR and CFP, specifically investigating whether SR acts as a moderating or mediating factor in the CSP-CFP nexus. The analysis is limited to 19 high-quality articles published in top-tier accounting journals between 2014 and 2024 to minimize publication bias and ensure reliability. The meta-analysis reveals no statistically significant moderating effect of SR on CFP. Instead, the results confirm a significant mediating effect, particularly when considering the presence of sustainability reports rather than just their specific content. These findings suggest that SR serves as a vital catalyst for corporate communication, providing more positive effects in voluntary compared to mandatory disclosure settings. This paper has both theoretical and practical implications, which are mainly relevant to standard-setters for assessing the efforts of SR disclosure regulation, and is of fundamental importance to managers as it indicates that SR does not relate solely to the practice of conformity, but rather to essential channels of communication and value creation.