This study aims to guide future research by examining trends and structures in scholarly publications about digital transformation in healthcare. We analyzed English-language, open-access journal articles related to this topic from the Scopus database, irrespective of publication year. Using tools like Microsoft Excel, VOSviewer, and Scopus Analyzer, we found a growing research interest in this area. The most influential article, despite being recent, has been cited 836 times, indicating its impact. Notably, both Western and Eastern countries contribute significantly to this field, with research spanning multiple disciplines, including computer science, medicine, engineering, business, social sciences, and health professions. Our findings can help policymakers allocate resources to impactful research areas, prioritize multidisciplinary collaboration, and promote international partnerships. They also offer insights for technology investment, implementation, and policy decisions. However, this study has limitations. It relied solely on Scopus data and didn’t consider factors like author affiliations. Future research should explore specific collaboration types and the ethical, social, policy, and governance implications of digital transformation in healthcare.

In the process of China's industrial modernization development, intelligent manufacturing is one of the very important links, in the promotion of social development and economic development plays an important significance, therefore, it is necessary to maximize the level of intelligent manufacturing. As an important technical means in intelligent manufacturing, mechatronics technology has very great application advantages, which can not only promote the production efficiency and product quality, but also effectively reduce the cost of expenditure. This paper will study the application of mechatronics technology in intelligent manufacturing.

This study examines the relationship between macroeconomic determinants and education levels in eight selected African oil-exporting countries (AOECs) over the period 2000–2022. Drawing on human capital theory, the paper scrutinizes the impact of factors such as income inequality, health outcome, economic growth, human development, unemployment, education expenditure, institutional quality, and energy consumption on education levels. Employing robust estimation techniques such as fixed effects (FE), random effects (RE), pooled mean group (PMG) and cross-section autoregressive distributed lag model (CS-ARDL), the study unveils vital static and dynamic interactions among these determinants and education levels. Findings reveal notable positive and significant connections between education levels and some of the variables—human capital development, institutional quality, government expenditure on education, and energy consumption, while income inequality demonstrates a consistent negative relationship. Unexpectedly, health outcomes exhibit a negative impact on education levels, warranting further investigation. Furthermore, the analysis deepens understanding of long-run and short-run relationships, highlighting, for example, the contradictory impact of gross domestic product (GDP) and unemployment on education levels in AOECs. Finally, the study recommends targeted human development programs, enhanced public investment in education, institutional reforms for good governance, and sustainable energy infrastructure development.

This study aims to assess the efficacy of speech-to-text (STT) technology in improving the writing abilities of special education pupils in Saudi Arabia. A deliberate sample of 150 special education college students was selected, with participants randomly allocated to either an experimental group employing STT technology or a control group using traditional writing methods. The study utilized a comprehensive approach, which included standardized writing assessments, questionnaires, and statistical analyses such as t-tests, correlation, regression, ANOVA, and ANCOVA. The results demonstrate a substantial enhancement in writing skills among the experimental group utilizing Speech-to-Text (STT) technology. The findings contribute to the discussion on assistive technology in special education and offer practical recommendations for educators and policymakers.

The complex interactions of industrial Policy, structural transformation, economic growth, and competitive strategy within regional industries are examined in this research. Using a dynamic capabilities framework, the study examines the mediating roles of organizational innovation and adaptability in the link between competitiveness and macroeconomic variables. A two-way fixed effects model is used in this study to examine the influence of structural transformation (ST) on Industrial Policy (IP). Using regional data covering the years 2010 to 2022, the research undertaken in this paper explores the dynamics of the Indonesian economy by empirically assessing the consequences of structural change on industrial Policy. In order to establish a comprehensive model that clarifies the mechanisms through which industrial policies and structural shifts impact the development of dynamic capabilities, ultimately influencing competitiveness strategies, this research draws on a large amount of empirical data and integrates insights from seminal works. Our research adds to our knowledge of strategic management in regional industries by providing detailed information on how economic development and policy interventions influence businesses’ ability to adapt and gain a competitive edge. In addition to advancing scholarly discourse, this study offers business executives and politicians valuable insights for managing the intricacies of global economic processes.

This study investigates the relationship between the disclosure of historical tourism information by local governments and tourism performance in Indonesia. Employing a quantitative research design, data were collected from 152 respondents, including local government officials, tourism stakeholders, and community members, using a purposive sampling method. This approach ensured the inclusion of participants with direct knowledge and involvement in historical tourism activities. Data analysis was conducted using IBM SPSS software, utilizing descriptive statistics, correlation, and multiple regression analysis to examine the relationships between variables. The results indicate that effective disclosure practices positively impact tourism performance, with key factors including the involvement of regional heads, legislative councils, mass media, tourism business actors, investment value, tourism budgets, and grant expenditures. The study highlights the importance of transparency and comprehensive information dissemination in enhancing tourism performance. Future research should explore the role of digitalization and innovative technologies in improving historical tourism disclosure and performance. These findings have significant implications for policymakers and practitioners in the tourism sector, emphasizing the need for robust disclosure practices to foster tourism development and economic growth.