The present study aimed to determine the dynamic relationship between good governance, fiscal policy, and economic growth in Oman. In the context of the current study, researchers chose a quantitative approach to answer the research questions, utilizing the latest 2023 data from the World Bank and The Global Economy databases. The data for the current study was carefully selected using variables that represent aspects of governance, fiscal policies, and economic performance. Our analysis uses Ordinary Least Squares (OLS) regression and the Autoregressive Distributed Lag (ARDL) Model. These methods help us understand these factors’ immediate and long-term impacts on Oman’s economy. The results we obtained offer fascinating insights into the country’s economic dynamics. We observe bidirectional causal relationships between the Good Governance Index (GGI) and the Regulatory Quality Index (RQI) and economic growth, while Fiscal Policy Effectiveness (FPE), Government Efficiency Index (GEI), and the Rule of Law Index (RLI) exhibit unidirectional causality towards GDP. Budget Balance (BB) shows no causal relationship with GDP, implying external factors influence it. Additionally, moderation analysis underscores the significance of digital financial inclusion in amplifying the effects of governance and fiscal policies on economic growth. These findings hold practical implications for policymakers and stakeholders in Oman. Specifically, they highlight the importance of governance, regulatory quality, and effective fiscal policies in shaping the economic landscape. To foster sustainable economic development, efforts should improve governance, enhance fiscal policy effectiveness, and promote digital financial inclusion.

The study aims to investigate the impact of digital leadership on sustainable competitive advantage, digital talent, and knowledge workers. Additionally, it explores the mediating role of digital talent (DT) and knowledge workers (KW) in the relationship between digital leadership (DL) and sustainable competitive advantage (SC), using the Technology Acceptance Model (TAM) as its theoretical foundation. The researchers employed Partial Least Squares Structural Equation Modeling (PLS-SEM) to examine survey data from 784 employees working in Egyptian travel agencies and tour operators. The results demonstrate that DL significantly enhances SC, DT, and KW. Moreover, DT and KW were shown to positively contribute to SC and serve as partial mediators in the relationship between DL and SC. The findings highlight the crucial role of developing DT and creating an environment that embraces technological acceptance and innovation. This approach amplifies the strategic effectiveness of DL, ultimately contributing to long-term organizational success.

The purpose of the article is to present the results of analysis of newly industrialized countries in the context of sustainable development. The study took place within the framework of the Kaldor’s structural-economic model of the gross domestic product and the energy flow model, using the socio-economic systems power changes analyzing method. Within the context of the approach, an invariant coordinate system in energy units is considered, the necessary conditions for sustainable development are formulated, and the main parameters for assessing the potential for growth and development are determined. The article focuses on key issues regarding new concepts of sustainable development and methodology for assessing sustainable development using the concept of socioeconomics useful power for the countries of the newly industrialized economy a group of emerging countries that have made in short time period a qualitative transition in socio-economic development. Based on a new definition of sustainable development in energy units, development trends are formulated for the selected countries during 20 years for the period 2000–2019. Results of the study can be used to planning for the transition to sustainable development. The data of the Central Statistical Office of European Union, the World Bank and the United Nations Organization were used for calculations. Initial interpretation of the calculated data has been done for the largest newly industrialized countries Brazil, India and China in terms of the gross domestic product in the period 1990–2019. For comparison, data on USA are presented as countries with advanced economy.

In Ecuador, although regulations on curricular adaptations are clearly defined, Physical Education teachers face challenges at the micro-curricular level in adapting their classes to meet the needs of students with disabilities, specific learning difficulties, and vulnerable situations. The objective of this study was to analyze the presence and characteristics of specific curricular adaptations for Physical Education on a global scale. A scoping review was conducted following the PRISMA-ScR guidelines, covering studies from the Scopus database. A total of 112 articles were identified, and 16 that met the inclusion criteria were selected. These studies addressed curricular adaptations in Physical Education across five dimensions: teaching methodology, inclusive assessment, access to resources, accessible environments, and learning content, with a focus on students with disabilities. It was concluded that the combination of access adaptations, methodological strategies, and curricular content modifications enhances the inclusion and participation of students with disabilities. Interventions with these simultaneous adaptations achieved levels of satisfaction, self-efficacy, and holistic development, influenced by the geographical and cultural context.

This paper presents an overview of the policies and efforts of the Provincial Government of Bali, Indonesia, to tackle the development of HIV/AIDS. This study considers the socio-cultural context and analyzes the factors that are most likely to influence its spread, the response of the community, and the local government’s efforts to form Provincial AIDS commission whose movement is supported by the village government and the community to suppress the spread of HIV/AIDS. The authors observe the micro factors that most determine this program, such as attitudes, behaviors, and desires of policy-making actors, stakeholders, implementing organizations, adequacy of human resources, financial funds, information, education, communication, advocacy, regional languages, the role of students, and field workers, and local culture in preventing the spread of HIV/AIDS. Therefore, this research does not focus on just one dimension in efforts to deal with this outbreak. Following the application of the public policy theory, all potential contributing elements must be addressed simultaneously. This requires a truly interdisciplinary and multisectoral approach that requires to be comprehended by policymakers in other provinces where the prevalence of HIV/AIDS is quite high. This effort also requires commitment and strong political will from levels of government.

The paper considers an important problem of the successful development of social qualities in an individual using machine learning methods. Social qualities play an important role in forming personal and professional lives, and their development is becoming relevant in modern society. The paper presents an overview of modern research in social psychology and machine learning; besides, it describes the data analysis method to identify factors influencing success in the development of social qualities. By analyzing large amounts of data collected from various sources, the authors of the paper use machine learning algorithms, such as Kohonen maps, decision tree and neural networks, to identify relationships between different variables, including education, environment, personal characteristics, and the development of social skills. Experiments were conducted to analyze the considered datasets, which included the introduction of methods to find dependencies between the input and output parameters. Machine learning introduction to find factors influencing the development of individual social qualities has varying dependence accuracy. The study results could be useful for both practical purposes and further scientific research in social psychology and machine learning. The paper represents an important contribution to understanding the factors that contribute to the successful development of individual social skills and could be useful in the development of programs and interventions in this area. The main objective of the research was to study the functionalities of the machine learning algorithms and various models to predict the students’s success in learning.