This research analyzes disaster risk financing within the framework of the disaster management policy in Indonesia as the implementation of the Disaster Management Law, Number 24 of 2007, by examining recent issues, challenges, and opportunities in disaster financing. Utilizing a qualitative approach, the research systematically reviews various studies, reports, and existing regulations and policies to understand the current landscape comprehensively. Recent developments in disaster risk financing in Indonesia highlight the need for a nuanced exploration of the existing policy framework. Fiscal constraints, evolving risk landscapes, and the increasing frequency of disasters underscore the urgency of effective disaster risk financing strategies. Through a qualitative examination, this study identifies challenges while illuminating opportunities for innovation and improvement within the current policy framework. The contribution of this research extends to both theoretical and practical levels. Theoretically, it enriches the academic discourse on disaster risk financing by offering a nuanced understanding of the complexities involved. On a practical level, the findings derived from the examination provide actionable recommendations for policymakers and practitioners engaged in disaster management in Indonesia. The insights aim to inform the refinement of disaster management policies and practices, fostering resilience and adaptability in the face of evolving disaster scenarios.

Family violence is the act that causes harm, suffering, or death to members of the family group, especially if they are in a situation of vulnerability due to characteristics associated to age or physical condition. Objective: The social characteristics of aggressors were associate in the risk level of victims of family violence in the city of Arequipa, Peru. Method: The study was descriptive, quantitative, and non-experimental. A total of 205 randomly selected judicial files of aggressors reported for domestic violence were evaluated. The data were secondary, and the chi-square test (association of categorical variables) was used for statistical analysis. Results: A moderate risk level (31.2%) was found, with a tendency to be severe and very severe (49.5%). Likewise, the most observed types of violence are physical and psychological violence (89.3%) and sexual abuse (10.7%). The female aggressor exerts mild violence, while the male aggressor exerts moderate to extreme severe violence, causing more harm to the victim. The profile of the aggressor with low or high education, with high or low incomes, and who occupies a house or only one room can be associated the level of violence that occurs. Conclusion: Men are more likely to attack women, and similarly, female aggressors tend to target men more frequently. Moreover, men exhibit a higher tendency to attack their partners, including wives, cohabitants, and ex-partners, whereas women tend to target a broader range of family members, including parents, children, grandparents, nephews, cousins, as well as in-laws such, brothers-in-law and other relatives.

The goal of this work was to create and assess machine-learning models for estimating the risk of budget overruns in developed projects. Finding the best model for risk forecasting required evaluating the performance of several models. Using a dataset of 177 projects took into account variables like environmental risks employee skill level safety incidents and project complexity. In our experiments, we analyzed the application of different machine learning models to analyze the risk for the management decision policies of developed organizations. The performance of the chosen model Neural Network (MLP) was improved after applying the tuning process which increased the Test R² from −0.37686 before tuning to 0.195637 after tuning. The Support Vector Machine (SVM), Ridge Regression, Lasso Regression, and Random Forest (Tuned) models did not improve, as seen when Test R² is compared to the experiments. No changes in Test R²’s were observed on GBM and XGBoost, which retained same Test R² across different tuning attempts. Stacking Regressor was used only during the hyperparameter tuning phase and brought a Test R² of 0. 022219.Decision Tree was again the worst model among all throughout the experiments, with no signs of improvement in its Test R²; it was −1.4669 for Decision Tree in all experiments arranged on the basis of Gender. These results indicate that although, models such as the Neural Network (MLP) sees improvements due to hyperparameter tuning, there are minimal improvements for most models. This works does highlight some of the weaknesses in specific types of models, as well as identifies areas where additional work can be expected to deliver incremental benefits to the structured applied process of risk assessment in organizational policies.

Integrated risk value response is designed to reduce threats and increase opportunities, especially in terms of running the spun pile method innovation process in accordance with the ISO 56002:2019 standard. Implementing innovation can reduce risks and increase the competitiveness of the company. The method of making or producing spun piles is the research area examined in this study. Questionnaires were distributed to workers in precast concrete companies and most of them were involved in each spun pile production line in the company in order to identify the risk factors that existed in the production line for the spun pile manufacturing method. 30 respondents were workers from organizations in the positions of Director, Manager and Staff. The risk values and impacts are mapped for each dimension to the activity details and it is found that there are 5 high risks as dominant ones, mainly risks with codes R41, R10, R4, R37, and R36. Based on a survey, the highest risk of 30% was found in the stressing & spinning dimension, which is recommended for the innovation process. Innovation is conducted with 5 innovation processes, mainly identifying opportunities, creating concepts, validating concepts, developing solutions, and deploying solutions. Recommendations for improvements are made with preventive and corrective actions that must be taken from every aspect of the spun pile production method activities. Innovation recommendations are also proposed to monitor production activities in real-time utilizing existing information and communication technology. Handling of spun pile waste material must also be implemented with certain methods and produce products that add value for the company. Ultimately, to increase the company’s competitiveness by increasing assets, it is recommended to increase the company’s intangible assets. The company’s intangible assets encompass IPR ownership in the form of Patents and Copyrights.

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.

 This paper empirically analyzes the relationship between corporate governance and capital market risk using A-share listed companies in China’s Shanghai and Shenzhen markets from 2008 to 2022 as a research sample. The study finds that corporate governance decreases capital market risk using new risk measurement at the firm level. Further analysis shows that such an effect is more pronounced in the sample of private companies, companies with a higher degree of indebtedness, and companies with a lower concentration of power. This paper’s findings help us better understand corporate governance’s role in stock risk and provide theoretical support and empirical evidence to improve the stability of the financial market in emerging markets.