The extent to which businesses incorporate Naga worship into their strategies and operations and its effect on their success remains ignored. This study employed a multidisciplinary approach to examine the diverse practices of Naga worship in business contexts across different regions. This study utilized a mixed-methods research design to provide insights into the strategic integration of Naga worship into business practices and its impact on business performance. It employed a questionnaire to gather insights from respondents about their demographic data, awareness of Naga worship, its integration into business practices, consumer perceptions and behaviors, and overall business performance. Follow-up, in-depth interviews were developed to probe deeper into respondents’ experiences, motivations, and perceptions regarding the integration of Naga worship into their business practices. Most respondents agreed to integrate Naga worship into their company practices or marketing plans by using Naga symbols in branding, doing rituals for success, providing Naga-themed products and services, and scheduling activities on auspicious Naga-related dates. Respondents perceived companies that venerate Naga as culturally genuine and focused on the community. Worshipping the Naga deity improved the brand’s and corporation’s image and reputation. People patronized these enterprises by buying products and services associated with Naga culture. A substantial portion of respondents believe that worshiping Naga enhances commercial prosperity. Yet, a few participants from different regions mentioned difficulties regarding the integration of Naga religious customs.

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.

Access to affordable and quality medicines plays a vital role for achieving Universal Health Coverage and in reducing out-of-pocket expenditures (OOPE) for households especially in developing nations such as India. Pradhan Mantri Bhartiya Janaushadhi Pariyojana (PMBJP), a Government of India initiative, aims to make low-cost and quality generic drugs and surgical equipment accessible to all segments of the population through its dedicated store outlets known as Pradhan Mantri Bhartiya Janaushadhi Kendra (PMBJK). In this study, a pilot survey comprising 20 stores/PMBJKs and 150 citizens was undertaken in the Bengaluru Urban District, India to understand various aspects of the PMBJKs including availability of drugs, stock-outs, accessibility to stores, perception and awareness levels along with challenges faced by store owners and citizens/beneficiaries. Based on the survey results, we capture the availability of drugs for 35 medicines and consumables belonging to 12 therapeutic categories across 20 store outlets. We also provide valuable insights and interdisciplinary recommendations on several facets including adopting technology-based measures for day-to-day functioning of stores, need for in-depth supply chain analysis for ensuring availability of drugs, encouraging prescription of generic medicines, increasing awareness levels in addition to promoting grassroot-level research, surveys and feedback mechanisms. These suggestions are expected to find their utility in policy-making, strengthen the implementation of the PMBJP scheme across Bengaluru and India as well as contribute towards achieving related Sustainable Development Goals.

The Malaysian dilemma presents a complex challenge in the wake of the COVID-19 pandemic, requiring a comprehensive statistical analysis for the formulation of a sustainable economic framework. This study delves into the multifaceted aspects of reconstructing Malaysia’s economy post-COVID-19, employing a data-driven approach to navigate the intricacies of the nation’s economic landscape. The research focuses on key statistical indicators, including GDP growth, unemployment rates, and inflation, to assess the immediate and long-term impacts of the pandemic. Additionally, it examines the effectiveness of government interventions and stimulus packages in mitigating economic downturns and fostering recovery. A comparative analysis with pre-pandemic data provides valuable insights into the extent of economic resilience and identifies sectors that require targeted support for sustained growth. Furthermore, the study explores the role of technology and digital transformation in building a resilient economy, considering the accelerated shift towards remote work and digital transactions during the pandemic. The analysis incorporates data on technological adoption rates, digital infrastructure development, and innovation ecosystems to gauge their contributions to economic sustainability. Addressing the Malaysian Dilemma also involves an examination of social and environmental dimensions. The study investigates the impact of economic policies on income distribution, social equity, and environmental sustainability, aiming to achieve sustainable economic growth. The study contributes a nuanced analysis to guide policymakers and stakeholders in constructing a sustainable post-COVID-19 economy in Malaysia.

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.