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.
With the rapid development of artificial intelligence (AI) technology, its application in the field of auditing has gained increasing attention. This paper explores the application of AI technology in audit risk assessment and control (ARAC), aiming to improve audit efficiency and effectiveness. First, the paper introduces the basic concepts of AI technology and its application background in the auditing field. Then, it provides a detailed analysis of the specific applications of AI technology in audit risk assessment and control, including data analysis, risk prediction, automated auditing, continuous monitoring, intelligent decision support, and compliance checks. Finally, the paper discusses the challenges and opportunities of AI technology in audit risk assessment and control, as well as future research directions.
In the face of growing competition, industrial and commercial firms need more effective strategies to gain competitive advantages. This study investigates the role of enterprise risk management (ERM) as a mediator in highlighting the significance of innovation capability on profitability in industrial and commercial firms listed on the Amman Stock Exchange (ASE). Data were collected from 244 respondents using a standardized questionnaire and analyzed with SPSS software. The results indicate that the innovation capability has an impact on profitability in industrial and commercial firms, as well as their ERM practices. Additionally, ERM mediates the relationship between innovation capability and profitability. Firms that adopt distinctive innovation strategies tend to maintain formal ERM strategies, which in turn enhance market superiority and profitability. This research offers some significant managerial ramifications that may be essential for business owners, executives, and decision-makers involved in the development of firms.
Ticket revenues are crucial for the financial success of sports teams. To maximize these revenues, teams continuously explore effective ticket promotional strategies. One such strategy includes partial season plans, which mirror bundle offers common across various industries. Another widespread promotional strategy across industries is offering discounted credit (i.e., store credit purchased at a lower price than its face value). However, its application in sports (e.g., providing a $500 credit for tickets at $450) remains limited. Therefore, this study explores critical questions such as: “How effective is offering discounted credit compared to partial season plans?” and “What factors influence ticket promotion preferences?” Consequently, the study employed a 2 × 2 × 2 experimental designs, considering three independent variables: promotion type (discounted credit vs. partial season plans), promotion flexibility (predefined vs. customizable), and the consumer’s distance to the venue (near vs. distant). Results indicated that partial season plans generated significantly higher perceived value and purchase intentions while presenting lower perceived risks than discounted credit . Promotion flexibility did not significantly influence the three dependent variables , but the distance to the venue did . Both practical and theoretical implications of these findings are discussed.
Noise pollution in construction sites is a significant concern, impacting worker health, safety, communication, and productivity. The current study aims to assess the paramount consequences of ambient noise pollution on construction activities and workers’ productivity in Peshawar, Pakistan. Noise measurements have been recorded at four different construction sites in Peshawar at different times of the day. Statistical analysis and Relative Importance Index (RII) are employed to evaluate the data Risk variables, such as equipment maintenance, noise control, increased workload, material handling challenges, quality control issues, and client satisfaction. The results indicated that noise levels often exceeded permissible limits, particularly in the afternoon, posing significant worker risks. In addition, RII analysis identified communication difficulties, safety hazards, and decreased productivity as significant issues. The results show that noise pollution is directly linked with safety risks, decreased performance, and client dissatisfaction and needs immediate attention by authorities. This paper proposes a strategic policy framework, recommending uniform hand signals and visual communication methods without noise for workers, worker training about safety, and using wearable devices in noisy settings. Communication training for teams and crane operators, proactive quality control, and customer-oriented project schedules are also proposed. These recommendations aim to mitigate the adverse effects of noise pollution, enhance construction industry resilience, and improve overall operational efficiency, worker safety, and client satisfaction in the construction sector of Peshawar, aligning with policy and sustainable development objectives.
Background: Digital transformation in the sports industry has become increasingly crucial for sustainable development, yet comprehensive empirical evidence on policy effectiveness and risk management remains limited. Purpose: This study investigates the impact of policy support and risk factors on digital transformation in sports companies, examining heterogeneous effects across different firm characteristics and regional contexts. Methods: Using panel data from 168 sports companies listed on China’s A-shares markets and the New Third Board from 2019 to 2023, this study employs multiple regression analyses, including baseline models, instrumental variables estimation, and robustness tests. The digital transformation level is measured through a composite index incorporating digital infrastructure, capability, and innovation dimensions. Results: The findings reveal that policy support significantly enhances digital transformation levels (coefficient = 0.238, p < 0.01), while financial risks demonstrate the strongest negative impact (−0.162, p < 0.01). Large firms and state-owned enterprises show stronger responses to policy support (0.312 and 0.278, respectively, p < 0.01). Regional development levels significantly moderate the effectiveness of policy implementation. Conclusions: The study provides empirical evidence for the differential effects of policy support and risk factors on digital transformation across various firm characteristics. The findings suggest the need for differentiated policy approaches considering firm size, ownership structure, and regional development levels. Implications: Policy makers should develop targeted support mechanisms addressing specific challenges faced by different types of firms, while considering regional disparities in digital transformation capabilities.
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