The primary objective of this paper is to explore the impact of household policies in both Saudi Arabia and Nigeria towards achieving efficient and sustainable economic growth in the 21st century. Fundamentally, the objective of the study was sparked by the basic factors of comparison the importance of culture in international relations, challenges related to terrorism which impede adequate implementations of economic policies, trade facilitation and logistics to enhance economic growth and cross-border movement of goods and services. Systematic literature review (SLR) and content analysis (CA) were used as methodological approaches of the paper. The articles explored for review were accessed using visualization of similarities (VOS) by exploring different database such as: journals, core collection of Web of Science (WOS), peer review sources and library sources. The findings demonstrated that Saudi Arabia and Nigeria have different policies regarding households in achieving sustainable economic growth. On one hand, in Saudi Arabia, the focus is on the economic burden associated with chronic non-communicable diseases (NCDs) and the out-of-pocket spending among individuals diagnosed with these diseases. In addition, the study found that households with older and more educated members, an employed head of household, higher socioeconomic status, health insurance coverage, and urban residency had significantly higher out-of-pocket expenditure in achieving sustainable economic development. On the other hand, Nigeria’s policy is centered around trade liberalization and its impact on household welfare as an integral part of sustainable economic development. The policies implemented in Saudi Arabia and Nigeria have implications for the well-being of their citizens. In Saudi Arabia, the household policies have significantly impacted the quality of life (QoL) of households, particularly those with low income, large size, male-led, urban, and with elderly heads. In Nigeria, trade liberalization policies have mixed welfare implications for households in the aspects of real income, they also induce unemployment in key sectors, such as agriculture and industry. To mitigate negative effects, it is suggested that Saudi Arabia should effectively address chronic non-communicable diseases (NCDs) among the households while Nigeria should efficiently pursue trade liberalization on a sectorial basis, focusing on sectors that do not severely undermine household welfare.

With the outbreak of the COVID-19 pandemic in 2019, educational activities have faced significant disruptions, leading to a widespread adoption of online teaching and a transformation in the evaluation of teaching quality. Using CiteSpace visualization software, the study examines 1485 papers from the Chinese database of China Knowledge Network and 1656 papers from the English database of Web of Science (WoS) spanning the period from January 2013 to June 2023 as research samples. The findings reveal heightened activity in China and other countries research on teaching quality evaluation, moreover, research in both contexts predominantly comprises independent studies, supplemented by collaborative efforts. Notably, there is an increased focus on the exploration of online teaching quality evaluation, specifically delving into methodologies and systems. The emphasis has shifted towards students’ learning initiatives and a comprehensive evaluation of teachers’ work before, during and after class. While research in other countries has also identified new hotspots related to online teaching, the number of studies is comparatively limited. The study proposes the imperative need to update the evaluation criteria for online teaching and enhance the infrastructure of online teaching platforms. Additionally, it advocates for reforms in the evaluation systems of educational institutions and innovations of teachers’ instructional methods.

This study analyzes in a comparative way the psychological meanings that social science and basic science researchers assign to the term “research”. Using the Natural Semantic Networks technique with 127 participants from a Colombian public university, we sought to unravel the distinctive epistemological and methodological positions between these disciplines. The findings reveal that, although both groups closely associate research with knowledge, they differ in the lexical network and associated terms, reflecting their different epistemological approaches. Basic science researchers emphasize terms such as “innovation” and “experimentation,” while social science researchers lean toward “solving” and “learning.” Despite the variability in the associated words, “knowledge” remains the common core, suggesting a shared basis in the perception of research. These results show the importance of considering disciplinary differences in research training and knowledge generation. The study concludes that research contributes significantly to both the advancement of individual disciplines and social welfare, urging future research to explore these dynamics in broader contexts to enrich interdisciplinary understanding and foster cooperation in knowledge generation.

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.