To evaluate the efficiency of decision-making units, researchers continually develop models simulating the production process of organizations. This study formulates a network model integrating undesirable outputs to measure the efficiency of Vietnam’s banking industry. Employing methodologies from the data envelopment analysis (DEA) approach, the efficiency scores for these banks are subsequently computed and comparatively analyzed. The empirical results indicate that the incorporation of undesirable output variables in the efficiency evaluation model leads to significantly lower efficiency scores compared to the conventional DEA model. In practical terms, the study unveils a deterioration in the efficiency of banking operations in Vietnam during the post-Covid era, primarily attributed to deficiencies in credit risk management. These findings contribute to heightening awareness among bank managers regarding the pivotal importance of credit management activities.

Fiscal spending for road construction to link Kalabakan, Sabah, Malaysia with North Kalimantan, Indonesia is an idea that have been proposed for over 20 years. The announcement for the relocation of Indonesia’s capital city from Jakarta to East Kalimantan give a strong justification for the construction of the Serudong-Simanggaris road. The fact that population size is big in Kalimantan and strong purchasing power is estimated in North and East Kaliamantan provide a strong argument for the need to have a road link. Having said that, the effect of road construction on output growth is not clear. The purpose of this study is to estimate the impact of road construction and the business activities across two sectors being assumed on output Sabah’s output growth. Based on the input-output analysis conducted using the output multiplier, the one-off road construction would lead to 1.8% growth in Sabah’s overall output.

This paper uses existing studies to explore how Artificial Intelligence (AI) advancements enhance recruitment, retention, and the effective management of a diverse workforce in South Africa. The extensive literature review revealed key themes used to contextualize the study. This study uses a meta-narrative approach to literature to review, critique and express what the literature says about the role of AI in talent recruitment, retention and diversity mapping within South Africa. An unobtrusive research technique, documentary analysis, is used to analyze literature. The findings reveal that South Africa’s Human Resource Management (HRM) landscape, marked by a combination of approaches, provides an opportunity to cultivate alternative methods attuned to contextual conditions in the global South. Consequently, adopting AI in recruiting, retaining, and managing a diverse workforce demands a critical examination of the colonial/apartheid past, integrating contemporary realities to explore the potential infusion of contextually relevant AI innovations in managing South Africa’s workforce.

This study investigates how digital transformation influences visitor satisfaction at 12 World Heritage Sites (WHS) across eight coastal provinces in Eastern and Southern China. Utilizing 402 valid survey responses, it explores the impact of demographic factors—education, age, and income—on visitors’ perceptions of digital services, particularly focusing on usability, quality, and overall experience. The findings reveal that younger, higher-income, and STEM-educated visitors express significantly higher satisfaction with digital services, while older, lower-income visitors report lower levels of engagement and satisfaction. This research highlights the need for tailored digital strategies that cater to diverse demographic groups, ensuring the balance between technological innovation and the preservation of cultural authenticity at heritage sites. The originality of this study lies in its focus on non-Western contexts, particularly China’s rapidly developing coastal regions, which have been largely overlooked in the global discourse on digital tourism. By applying established theoretical frameworks—such as the Technology Acceptance Model (TAM) and Expectation-Confirmation Theory (ECT)—to a non-Western setting, this research fills a crucial gap in the literature. The insights provided offer actionable recommendations for heritage site managers to enhance visitor engagement, adapt digital services to demographic variations, and promote sustainable tourism development.

High-risk pregnancies are a global concern, with maternal and fetal well-being at the forefront of clinical care. Pregnancy’s three trimesters bring distinct changes to mothers and fetal development, impacting maternal health through hormonal, physical, and emotional shifts. Fetal well-being is influenced by organ development, nutrition, oxygenation, and environmental exposures. Effective management of high-risk pregnancies necessitates a specialized, multidisciplinary approach. To comprehend this integrated approach, a comparative literature analysis using Atlas.ti software is essential. Findings reveal key aspects vital to high-risk pregnancy care, including intervention effectiveness, case characteristics, regional variations, economic implications, psychosocial impacts, holistic care, longitudinal studies, cultural factors, technological influences, and educational strategies. These findings inform current clinical practices and drive further research. Integration of knowledge across multidisciplinary care teams is pivotal for enhancing care for high-risk pregnancies, promoting maternal and fetal well-being worldwide.