Low enrollment intention threatens the funding pools of rural insurance schemes in developing countries. The purpose of this study is to investigate how social capital enhances the enrollment of health insurance among rural middle-aged and elderly. We propose that social capital directly increases health insurance enrollment, while indirectly influences health insurance through health risk avoidance. We used data from the China Health and Retirement Longitudinal Study (wave 4) dating the year of 2018, instrumental variable estimation was introduced to deal with the endogeneity problem, and the mediation analysis was used to examine the mechanism of social capital on insurance enrollment. The results show that social capital is positively related to social health insurance enrollment, and the relationship between social capital and social health insurance enrollment is mediated by health risk avoidance.

Accurate demand forecasting is key for companies to optimize inventory management and satisfy customer demand efficiently. This paper aims to Investigate on the application of generative AI models in demand forecasting. Two models were used: Long Short-Term Memory (LSTM) networks and Variational Autoencoder (VAE), and results were compared to select the optimal model in terms of performance and forecasting accuracy. The difference of actual and predicted demand values also ascertain LSTM’s ability to identify latent features and basic trends in the data. Further, some of the research works were focused on computational efficiency and scalability of the proposed methods for providing the guidelines to the companies for the implementation of the complicated techniques in demand forecasting. Based on these results, LSTM networks have a promising application in enhancing the demand forecasting and consequently helpful for the decision-making process regarding inventory control and other resource allocation.

In the rapidly evolving landscape of technological innovation, the safeguarding of Intellectual Property Rights (IPR) emerges as a critical factor influencing economic growth and technological advancement. This study, conducted in the context of organizations operating in the United Arab Emirates (UAE), meticulously explores the intricate dynamics between IPR awareness, enforcement, and their implications for information security practices. The research undertakes a thorough investigation with three primary objectives: a comprehensive examination of IPR awareness, an exploration of the relationship between IPR enforcement and information security practices, and an assessment of the impact of information sensitivity. To achieve these objectives, a sample population of 150 respondents from various sectors was engaged, employing a combination of survey instruments and robust statistical analyses. The findings of the study illuminate a strong positive correlation between IPR awareness and information security practices, underscoring the pivotal role of cultivating IPR awareness among organizations. Furthermore, the enforcement of IPR, intricately connected with a resilient legal framework, regulatory authorities, international agreements, and effective customs and border control measures, is identified as a significant influencer of information security practices. The study employs a statistical model that exhibits a high explanatory power, elucidating approximately 85.9% of the variance in information security practices. In conclusion, the research offers profound implications for organizations, policymakers, and stakeholders in the UAE, advocating for strategies such as education, legal and regulatory support, international collaboration, and robust access control mechanisms to fortify IPR awareness, enforcement, and information security practices. The integration of advanced tools such as the smart PLS software adds depth and reliability to the study’s analytical framework, contributing to its comprehensive insights.

Every sector must possess the ability to identify potential dangers, assess associated risks, and mitigate them to a controllable extent. The mining industry inherently faces significant hazards due to the intricate nature of its systems, processes, and procedures. Effective risk control management and hazard assessment are essential to identify potential adverse events that might lead to hazards, analyze the processes by which these occurrences may transpire, and estimate the extent, importance, and likelihood of negative consequences. (1) The stage of industrial hazard analysis assesses the capability of a risk assessment process by acknowledging that hidden hazards have the potential to generate dangers that are both unknown and beyond control. (2) To mitigate hazards in mines, it is imperative to identify and assess all potentially dangerous circumstances. (3) Upon conducting an analysis and evaluation of the safety risks associated with identified hazards, the acquired knowledge has the potential to assist mine management in making more informed and effective decisions. (4) Frequently employed methods of data collection include interrogation of victims/witnesses and collection of information directly from the accident site. (5) After conducting a thorough analysis and evaluation of the safety hazards associated with hazard identification, the dataset has the potential to assist mine management in making more informed decisions. The study highlights the critical role of management in promoting a strong safety culture and the need for active participation in health and safety systems. By addressing both feared and unknown risks, educating workers, and utilizing safety-related data more effectively, mining companies can significantly improve their risk management strategies and ensure a safer working environment.

This study investigates the relationship between corporate social responsibility (CSR), capital structure, and financial distress in Jordan’s financial services sector. It tests the mediating effect of capital structure on the CSR-distress linkage. Utilizing a panel data regression approach, the analysis examines a sample of 35 Jordanian banks and insurance firms from 2015–2020. CSR is evaluated through content analysis of sustainability disclosures. Financial distress is measured using Altman’s Z-score model. The findings reveal an insignificant association between aggregated CSR engagement and bankruptcy risk. However, capital structure significantly mediates the impact of CSR on financial distress. Specifically, enhanced CSR enables higher leverage capacity, subsequently escalating distress risk. The results advance academic literature on the nuanced pathways linking CSR to financial vulnerability. For practitioners, optimally balancing CSR and financial sustainability is recommended to strengthen resilience. This study provides novel empirical evidence on the contingent nature of CSR financial impacts within Jordan’s understudied financial services sector. The conclusions offer timely insights to inform policies aimed at achieving sustainable and stable financial sector development.

Although the problems created by exceeding Earth’s carrying capacity are real, a too-small population also creates problems. The convergence of a nation’s population into small areas (i.e., cities) via processes such as urbanization can accelerate the evolution of a more advanced economy by promoting new divisions of labor and the evolution of new industries. The degree to which population density contributes to this evolution remains unclear. To provide insights into whether an optimal “threshold” population exists, we quantified the relationships between population density and economic development using threshold regression model based on the panel data for 295 Chinese cities from 2007 to 2019. We found that when the population density of the whole city (urban and rural areas combined) exceeded 866 km⁻², the impact of industrial upgrading on the economy decreased; however, when the population density exceeded 15,131 km⁻² in the urban part of the cities, the impact of industrial upgrading increased. Moreover, it appears that different regions in China may have different population density thresholds. Our results provide important insights into urban economic evolution, while also supporting the development of more effective population policies.