This paper analyzes the characteristics and influence mechanisms of financial support for China’s strategic emerging industries. Using a sample of 356 listed companies across nine major industries, we conduct an in-depth analysis of the efficiency of financial support and its influencing factors. In addition, this paper analyzes the influence mechanism of financial support for strategic emerging industries based on the relevant theory of financial support for industry development. It clarifies the internal and external influencing factors. Based on the theoretical analysis, a two-stage empirical investigation was conducted: The data of 356 listed companies in strategic emerging industries from 2010 to 2022 were selected as a sample, and the data envelopment analysis (DEA) method was applied to measure efficiency. The influencing factors were then analyzed using a Tobit regression and an intermediate effects test.

Illegal, unreported, and unregulated fishing (IUU fishing) crimes by rogue fisheries companies are rife in the sea waters of Riau Province. However, this issue is rarely reported by those provincial journalists in the online media where they work. In fact, in Riau, there are 163 online media companies and 600 competent journalists; 200 of them live in capture fisheries center areas. Apart from the journalist competency factor, the decision to make IUU fishing news can also be influenced by the fisheries company intervention that committed the crime. Besides, the policy role of media leaders—editors, editors-in-chief, and media owners—also determines journalists’ decisions to make those news stories. This research aims to analyze the influence of journalist competence and fishing company intervention on the decision to make IUU fishing news, as well as the role of media leader policy as mediators in these influences. This survey involved 100 competent journalists as respondents. Data collection was carried out through a questionnaire containing a number of closed statements measured on a 5-point Likert scale, which was distributed to respondents. The data were analyzed using the Structural Equation Modeling (SEM) method. The research results show that the fishing company intervention has a negative and significant influence on the decision to make IUU fishing news in Riau, while journalist competence does not. Additionally, media leader policy was found to play a significant role in mediating the influence of fisheries company intervention and journalist competence on the decision to make IUU fishing news. The leader policy could prevent journalists from making IUU fishing news if fisheries companies, who are responsible for those crimes, intervene and request it. Those actions of media leaders need to be questioned because they can hamper the media’s function as a means of disseminating information, educating the public, and implementing social control, especially those related to combating IUU fishing crimes.

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.

This paper explores the integration of digital technologies and tools in English as a Foreign Language (EFL) learning in Jordanian Higher Education through a qualitative open-ended online survey. It highlights the perceptions of 100 Jordanian EFL instructors, each with a minimum of five years of experience, on the digital transformation in the EFL learning process. The survey, consisting of ten open-ended questions, gathered in-depth insights on the benefits, challenges, and implications of this transformation. Thematic analysis was employed to analyze the qualitative data, revealing varied levels of experience, the use of diverse digital tools, and both technical and pedagogical challenges. Key findings include the positive impact of digital tools on teaching and learning experiences, enhanced student engagement, and opportunities for personalized learning and collaboration. The study concludes that leveraging digital resources can enhance EFL learner engagement and learning outcomes, inform future pedagogical practices, and shape the landscape of digital transformation in EFL Higher Education for years to come.

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.