This research investigates how accountants in Thailand are adapting to changes driven by advances in digital technology, environmental issues, and professional accounting organizations. The study identifies key factors influencing these shifts and assesses their impact on the accounting field. A survey of accountants from large manufacturing firms in Thailand was conducted, examining internal, external, and personal factors affecting their roles and responsibilities. The study uses Structural Equation Modeling (SEM) to analyze data from 174 respondents, identifying leadership and digital technology readiness as internal factors; sustainability force, professional entity, and digital technology force as external factors; and competency skills and attitude as personal factors. The fit indices collectively suggest that the model has a good fit to the data, demonstrated by Comparative Fit Index (CFI) value (0.91), Tucker-Lewis Index (TLI) (0.891), Root Mean Squared Error of Approximation (RMSEA) (0.067), and chi-square/degree of freedom model (1.776). The combination of the indices supports the conclusion that the model is robust and well-aligned with the observed data, and importantly capturing the relationships between the constructs under the study. Results reveal a significant transformation in the professional identity of Thai accountants, primarily driven by their positive attitude towards changes. Notably, professional accounting bodies and educational institutions appear to hinder this evolution. The findings emphasize the need for professional organizations to realign their strategies to better support the evolving roles of accountants.

The rapid advancement of information and communication technology has greatly facilitated access to information across various sectors, including healthcare services. This digital transformation demands enhanced knowledge and skills among healthcare providers, particularly in comprehensive midwifery care. However, midwives in rural areas face numerous challenges such as limited resources, cultural factors, knowledge disparities, geographic conditions, and technological adoption. This research aims to evaluate the impact of AI utilization on midwives’ knowledge and behavior to optimize the implementation of healthcare services in accordance with Delima Midwife Service standards in rural settings. The analysis encompasses competencies, characteristics, information systems, learning processes, and health examinations conducted by midwives in adopting AI. The research methodology employs a cross-sectional approach involving 413 rural midwives selected proportionally. Results from Partial Least Squares Structural Equation Modeling indicate that all reflective evaluation variables meet the required criteria. Fornell-Larcker criterion demonstrates that the square root of AVE is greater than other variables. The primary findings reveal that information systems (0.029) and midwives’ competencies (0.033) significantly influence AI utilization. Furthermore, midwives’ competencies (0.002), characteristics (0.031), and AI utilization (0.011) also significantly impact midwives’ knowledge and behavior. Midwives’ characteristics also significantly affect their competencies (0.000), while midwives’ learning influences health examinations (0.000). Midwives’ knowledge and behavior affect the transformation of healthcare services in rural midwifery (0.022). The model fit results in a value of 0.097, empirically supporting the explanation of relationships among variables in the model and meeting the established linearity test.

This paper delves into the intricate dynamics of suburban transportation transformation within the Jakarta Metropolitan Area, with a specific focus on the evolution of the Commuter Line and Bus Rapid Transit (BRT) systems. Utilizing spatial analysis, qualitative descriptions, and stakeholder insights, the paper unveils self-organizing dynamics. It critically examines the role of transportation infrastructure in shaping the broader landscape of urban development. Unlike a traditional approach, the paper seeks to unravel the self-organization processes embedded in transportation planning, unveiling adaptive strategies crafted to tackle the distinct challenges of suburban transportation. By using autonomy, flexibility, adaptability, and collaboration frameworks, the paper contributes to a nuanced understanding of suburban transportation dynamics, with implications for policymakers, planners, and researchers grappling with similar challenges in diverse metropolitan regions.

The research aimed to: 1) analyze components and indicators of digital transformation leadership among school administrators, 2) assess their leadership needs, and 3) develop mechanism models to promote this leadership. A mixed-method approach was applied, involving three sample groups: 8 experts, 406 administrators, and 7 experts. Data collection tools included semi-structured interviews, leadership scales, needs assessments, and focus group discussions, with analysis performed through construct validity testing, needs assessment, and content analysis. The findings revealed: 1) The components and indicators of digital transformation leadership showed structural validity, as confirmed by the model's alignment with empirical data (Chi-Square = 82.3, df = 65, p = 0.072, CFI = 0.998, TLI = 0.997, RMR = 0.00965, RMSEA = 0.0256). 2) Among the leadership components, "innovative knowledge" ranked highest in need (PNImodified = 0.075), followed by "ideological influence" (0.066), "consideration of individuality" (0.055), "intellectual stimulation" (0.052), and "inspiration" (0.053). 3) Mechanism models for promoting leadership emphasized enhancing these five components to strengthen administrators' skills in applying technology, managing teaching and development plans, and fostering innovation. Administrators were encouraged to tailor strategies to individual needs, inspire personnel, and create a commitment to organizational change and development. These mechanisms aim to equip administrators to effectively lead transformations, motivate staff, and drive educational institutions to adapt and thrive in evolving environments.

The artificial intelligence (AI)-based architect's profile's selection (simply iSelection) uses a polymathic mathematical model and AI-subdomains' integration for enabling automated and optimized human resources (HR) processes and activities. HR-related processes and activities in the selection, support, problem-solving, and just-in-time evaluation of a transformation manager's or key team members' polymathic profile (TPProfile). Where a TPProfile can be a classical business manager, transformation manager, project manager, or an enterprise architect. iSelection-related selection processes use many types of artifacts, like critical success factors (CSF), AI-subdomain' integration environments, and an enterprise-wide decision-making system (DMS). iSelection focuses on TPProfiles for various kinds of transformation projects, like the case of the transformation of enterprises' HRs (EHR) processes, activities, and related fields, like enterprise resources planning (ERP) environments, financial systems, human factors (HF) evolution, and AI-subdomains. The iSelection tries to offer a well-defined (or specific) TPProfile, which includes HF's original-authentic capabilities, education, affinities, and possible polymathical characteristics. Such a profile can also be influenced by educational or training curriculum (ETC), which also takes into account transformation projects’ acquired experiences. Knowing that selected TPProfiles are supported by an internal (or external) transformation framework (TF), which can support standard transformation activities, and solving various types of iSelection’s problems. Enterprise transformation projects (simply projects) face extremely high failure rates (XHFR) of about 95%, which makes EHR selection processes very complex.

This study delves into the nuanced impact of leadership styles on state-owned enterprises (SOEs) performance in Northeast China. It aims to discern how transformational, transactional, and authoritative leadership approaches influence organizational outcomes, framed within the context of sustainable leadership theory. Employing a quantitative methodology, the research analyzes survey data from employees across various SOEs to assess the relationship between leadership styles and company performance, including aspects such as job satisfaction, employee motivation, and operational efficiency. The findings reveal a clear dichotomy: transformational and transactional leadership styles positively correlate with improved performance metrics, fostering an environment of innovation, motivation, and job satisfaction. Conversely, authoritative leadership is shown to detrimentally affect these same metrics, potentially hindering organizational growth and employee morale. This research contributes to the broader discourse on leadership and organizational performance by highlighting the critical role of leadership style in enhancing the sustainable development of SOEs, particularly within China’s socio-political and economic fabric. Practical implications suggest a shift towards more adaptive, employee-centered leadership approaches to spur performance and sustainability in SOEs. The originality of this study lies in its specific focus on the Chinese context, offering insights into the leadership dynamics within SOEs and proposing actionable strategies for fostering leadership that align with sustainability and organizational excellence principles.