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.
I summarize the current regulatory decisions aimed at combating the debt load of the population in Russia. Further, I show that the level of delinquency of the population on loans is growing despite the regulatory measures taken. In my opinion, the basis of regulatory policy should move from de facto pushing personal bankruptcies to preventing them. I put forward a hypothesis and statistically prove the expediency of quantitative restrictions on one borrower. It is necessary to introduce reports to the credit bureaus of some types of overdue debts, which are not actually reported now. It is also necessary to change the order of debt repayment established by law, allowing the principal and current interest to be paid first, which will prevent the expansion of the debt.
Intellectual capital is one of the most crucial determinants of long-term economic development. The countries compete for highly skilled labor and talented youth. State regulatory interventions aim to, on the one hand, facilitate the retention of foreign high-productivity intellectual capital in the host country, transforming ‘educational’ and ‘scientific’ migrants into residents, and on the other hand, prevent the outflow of their own qualified workforce. The paper aims to outline the role of the nation’s higher education system in the influx and outflow of labor resources. A two-stage approach is applied: 1) maximum likelihood—to cluster the EU countries and the potential candidates to become members of EU countries based on the integrated competitiveness of their higher education systems, considering quantitative, qualitative, and internationalization aspects; 2) logit and probit models—to estimate the likelihood of net migration flow surpassing baseline cluster levels and the probability of migration intensity changes for each cluster. Empirical findings allow the identification of four country clusters. Forecasts indicate the highest likelihood of increased net migration flow in the second cluster (66.7%) and a significant likelihood in the third cluster (23.4%). However, the likelihood of such an increase is statistically insignificant for countries in the first and fourth clusters. The conclusions emphasize the need for regulatory interventions that enhance higher education quality, ensure equal access for migrants, foster population literacy, and facilitate lifelong learning. Such measures are imperative to safeguard the nation’s intellectual potential and deter labor emigration.
The rapid progress of information technology has made public online participation in policy formulation an inevitable product of modern government reshaping and reconstruction. However, compared with developed countries, citizens’ online participation in policy formulation in China started relatively late. Thus, in order to explore an effective and efficient method for Chinese citizens’ participation in policy formulation, this research made a brief review of the experiences from the typical developed country of United States of America at first, followed by some other developed countries such as Singapore, South Korea, and Japan in Asia with similar situations. Still, combined with the current situation of the China itself into consideration, this research further proposes targeted recommendations. It is expected that the findings in this research could provide some references for the Chinese government to form more effective and efficient theoretical frameworks targeted at the future development trends of the Chinese society and accordingly, to improve the construction of democracy in China.
The rapid expansion of smart cities has led to the widespread deployment of Internet of Things (IoT) devices for real-time data collection and urban optimization. However, these interconnected systems face critical cybersecurity risks, including data tampering, unauthorized access, and privacy breaches. This paper proposes a blockchain-based framework designed to enhance the security, integrity, and resilience of IoT data in smart city environments. Leveraging a private blockchain, the system ensures decentralized, tamper-proof data storage, and transaction verification through digital signatures and a lightweight Proof of Work consensus mechanism. Smart contracts are employed to automate access control and respond to anomalies in real time. A Python-based simulation demonstrates the framework’s effectiveness in securing IoT communications. The system supports rapid transaction validation with minimal latency and enables timely detection of anomalous patterns through integrated machine learning. Evaluations show that the framework maintains consistent performance across diverse smart city components such as transportation, healthcare, and building security. These results highlight the potential of the proposed solution to enable secure, scalable, and real-time IoT ecosystems for modern urban infrastructures.
The tourism sector in the Aseer region of Saudi Arabia is experiencing significant growth and development, aligning with the country’s Vision 2030 strategic framework. However, rapid growth can lead to strategic drift if not managed with vigilance. This study aims to examine the role of strategic vigilance in reducing strategic drift in the tourism sector. The study employs a quantitative approach, utilizing a questionnaire distributed to a sample of 220 staff and directors from the tourism sector. The questionnaire measures the level of strategic vigilance and the level of strategic drift. The study hypothesizes a statistically significant positive relationship between strategic vigilance and reducing strategic drift. Data analysis involves exploratory factor analysis, confirmatory factor analysis, and structural equation modeling. The findings are expected to provide insights into the effectiveness of strategic vigilance in mitigating strategic drift and offer recommendations for enhancing the tourism sector’s resilience and adaptability to accelerated environmental changes.
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