This article presents a comprehensive analysis and strategic framework for enhancing social welfare in Kazakhstan through the adoption of international social security standards. This article aims to formulate scientific and practical recommendations for enhancing the legal framework governing Kazakhstan’s social security system. It posits that integrating international social protection standards is pivotal for refining national legislation and charting future developmental courses. Employing a novel methodology, this study analyzes key documents from the International Labour Organization (ILO), the United Nations, the Commonwealth of Independent States (CIS), and the Eurasian Economic Union (EAEU). It also examines efforts to assimilate these international norms into Kazakhstan’s social security laws. The investigation reveals a stagnation in the evolution of the nation’s social sector, marked by a dearth of innovative ideas and initiatives to elevate the subpar social security standards. The adoption of international social standards emerges as a catalyst for rejuvenating the national social sphere, aiming to elevate the Kazakhstani social protection system to meet global benchmarks. This research outlines the pathways for Kazakhstan’s ratification of and accession to key social protection instruments and offers expert recommendations to support this endeavor. The conclusions and recommendations developed are poised for application in legislative reforms, aiming to amend and enhance existing laws to foster a more robust and inclusive social security framework. The findings suggest that the adoption of international social security standards not only contributes to the improvement of individual lives but also fosters social cohesion and economic stability. The article concludes with tailored recommendations for Kazakhstan, highlighting the role of stakeholder engagement, phased implementation, and continuous evaluation in the successful integration of global social security norms. This research contributes to the ongoing discourse on social security reform, offering a valuable perspective for scholars, policymakers, and practitioners involved in social welfare enhancement efforts in Kazakhstan and similar contexts.

In the process of forest recreation value development, there are some characteristics, such as large amount of investment capital, long financing recovery cycle and high potential risks, which lead to limited capital source and prominent financing risks. To achieve sustainable development, forest recreational value development enterprises must solve the financing dilemma, therefore, it is very urgent to identify the financing risk factors. The research constructed financing risk evaluation index system through WSR (Wuli-Shili-Renli) methodology (from affair law, matter principle and human art dimensions), taking S National Forest Park at Fujian Province as a case study, the analytic hierarchy process (AHP) and fuzzy comprehensive evaluation method were used for empirical analysis. The results showed that for the first level indicators, operational risk should be paid close attention to, followed by political risk and environmental risk. Among the secondary level indicators, policy changes, financing availability and market demand need attention, which are consistent with the result of field survey. Based on that, countermeasures were put forward such as the multiple collaborative linkage and effective internal control; reduction on operating costs and broaden financing channels; encouragement diversification of investment entities and improvement of financial and credit support; strengthening government credit supervision, optimizing financing risk evaluation, and building a smart tourism financing information platform, to reduce and control financing risks, then promote the development of forest recreation value projects.

The Government of Indonesia has modernized the toll road transaction system by implementing the multi-lane free-flow (MLFF) project, set to operate commercially by the end of 2024. This project leverages Global Navigation Satellite System (GNSS) technology to identify vehicles using toll roads and establish a transaction mechanism that allows the MLFF Project Company to charge road users according to distance, vehicle category, and tariff levels. The project has result in a complex business arrangement between the Indonesia National Toll Road Authority (INTRA), Toll Road Companies (TRCs), and the MLFF Project Company. The aim of this paper is to review the regulatory and institutional framework of the MLFF project and analyze its challenges. The methodology employed is a qualitative framework for legal research, utilizing international literature reviews and current regulatory frameworks. The study assesses the proposed transaction architecture of the project and identifies commercial, political, and other risks associated with its implementation. Based on the analysis, the research identifies opportunities for regulatory improvements and better contracting arrangements. This research provides valuable insights into the regulatory landscape and offers policy recommendations for the Government to mitigate the identified risks. This contribution is significant to the academic field as it enhances understanding regulatory and institutional challenges in implementing advanced toll road systems.

 Public-private partnerships (PPPs) are vital for infrastructure development in developing countries, integrating private efficiency with public oversight. However, PPP models often face risks, particularly in Indonesia’s water sector, due to its unique geographical and regulatory challenges. This study aims to identify and evaluate risk factors specific to drinking water PPP projects in Indonesia. Using a quantitative approach, structured questionnaires were distributed to experts in the sector, and the data was analyzed using a fuzzy evaluation method. Risks were categorized into location, design and construction, financial, operational, revenue, and political. The study emphasizes that effective risk management, including identification, analysis, and mitigation, is essential for project success. It highlights the importance of stakeholder involvement and flexible risk management strategies. Comprehensive and proactive risk management is key to the success of drinking water infrastructure projects. The research suggests that an integrated and collaborative approach among stakeholders can enhance risk management effectiveness. These findings provide valuable insights for policymakers, project managers, investors, and other stakeholders, underscoring the necessity for adaptable regulatory frameworks and robust policy guidelines to improve the sustainability and efficacy of future water-related PPPs.

Resisting the adoption of medical artificial intelligence (AI), it is suggested that this opposition can be overcome by combining AI awareness, AI risks, and responsibility displacement. Through effective integration of public AI dangers and displacement of responsibility, some of these major concerns can be alleviated. The United Kingdom’s National Health Service has adopted the use of chatbots to provide medical advice, whereas heart disease diagnoses can be made by IBM’s Watson. This has the ability to improve healthcare by increasing accuracy, efficiency, and patient outcomes. The resistance may be due to concerns about losing jobs, anxieties about misdiagnosis or medical mistakes, and the consciousness of AI systems drifting more responsibility away from medical professionals. There is hesitancy among healthcare professionals and the general public about the deployment of AI, despite the fact that healthcare is being revolutionised by AI, its uses are pervasive. Participants’ awareness of AI in healthcare, AI risk, resistance to AI, responsibility displacement and ethical considerations were gathered through questionnaires. Descriptive statistics, chi-square tests and correlation analyses were used to establish the relationship between resistance and medical AI. The study’s objective seeks to collect data on primary and public AI awareness, perceptions of risk and feelings of displacement that the professionals have regarding medical AI. Some of these concerns can be resolved when AI awareness is effectively integrated and patients, healthcare providers, as well as the general public are well informed about AI’s potential advantages. Trust is built when, AI related issues such as bias, transparency, and data privacy are critically addressed. Another objective is to develop a seamless integration of risk management, communication and awareness of AI. Lastly to assess how this comprehensive approach has affected hospital settings’ ambitions to use medical AI. Fusing AI awareness, risk management, and effective communication can be used as a comprehensive strategy to address and promote the application of medical AI in hospital settings. An argument made by Chen et al. is that providing training in AI can improve adoption intentions while lowering complexity through the awareness of AI.

The COVID-19 crisis, which occurred in 2020, brought crisis events back to the attention of scholars. With the increasing frequency of crisis events, the influence of crisis events on stock markets has become more obvious. This paper focuses on the impact of the subprime crisis, the Chinese stock market crash crisis and the COVID-19 crisis on the volatility and risk of the world’s major stock markets. In this paper, we first fit the volatility using EGARCH model and detect asymmetry of volatility. After that, a VaR model is calculated on the basis of EGARCH to measure the impact of the crisis event on the risk of stock markets. This paper finds that the subprime crisis has a significant influence on the risk of the stock market in China, US, South Korea, and Japan. During the COVID-19 crisis, there was little change in the average risk of each country. But at the beginning of the COVID-19 crisis, there was a significant increase in the risk of each country’s stock market. The Chinese stock market crash crisis had a more pronounced effect on the Chinese and Japanese stock markets and a lesser effect on the US and Korean stock markets.