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.

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.

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.

Low-cost housing homeownership funding for junior staffers is challenging in private sector organisations, especially in developing countries. Motivating private sector investment in junior staffers’ homeownership via a developed expanded corporate social responsibility (ECSR) may promote achieving Sustainable Development Goal 11 (SDG 11). Therefore, the study investigates the role of the ECSR framework in improving Nigeria’s private sector junior staffers’ homeownership and achieving SDG 11. Data were collected via face-to-face interviews with selected participants in six of Nigeria’s geo-political zones. The study adopted thematic analysis to analyse the collected data. Six variables emerged from the 18 re-clustered sub-variables. This includes institutionalising ECSR in low-income homeownership, housing finance for junior staffers’ homeownership, and housing incentives and stakeholders’ participation for low-income earners. The research employed six variables and 18 sub-variables to develop the improved private sector’s junior staffers’ homeownership via ECSR and achieving SDG 11 (sustainable cities and communities) and their targets. The research presents a novel approach by attempting to integrate SDG 11 with Corporate Social Housing, an extension of corporate social responsibility, especially to align the SDGs with evolving perspectives on Expanded Corporate Social Responsibility in Nigeria.

“Global South” is undoubtedly a broad term that typically refers to developing countries with varying degrees of economic, cultural and political influence. The rise of the Global South signifies the importance of reassessing the existing international order. In terms of international relations theory, this should be an innovative, progressive and reflective field of study. However, this research is predominantly led by the Western mainstream international relations theories. This often neglects the internal and external factors in the development processes of other countries, the formation of relationship frameworks, foreign policy formulation, and the need of foreign relations. Despite the ongoing and intense debate over the innovation of international relations theory, it is difficult to see it keeping pace with contemporary developments. Various schools and thoughts frequently innovate only within their foundational frameworks. Therefore, for Global South countries, there is the need for international relations theories that can reflect their specific needs and actual conditions. This does not only require breaking away from the westcentric theoretical framework, but ensuring that the innovation process is aligned with practical realities that recognize mutual interests and encompass both local and global perspectives. This approach should involve a comprehensive reflection on international relations, allowing innovation of international relations theories to genuinely “enter” the Global South countries.