Exploring the Relationship Between Organizational Culture Types and Knowledge Management Processes: A Meta-Analytic Path Analysis.

This study investigated the relationship between organizational culture types according to Competing Values Framework (Clan, Adhocracy, Market, Hierarchy) and Knowledge Management Processes (Creation, Dissemination, Storage, Application) using meta-analytic path analysis. To produce the necessary pooled correlation matrix for model testing, we used the univariate (r) approach to carry out two additional meta-analyzes. Based on data collected from several research databases, we extracted the paired correlation coefficients (r) among knowledge management processes (k = 32, N = 6835) then the inter-correlations between knowledge management processes and culture types (k = 7, N = 865). The findings revealed that no particular culture type has a stronger effect on all KM processes. Clan, Adhocracy and Market have significant but varying effects on Knowledge Management processes. Notably, the clan is more associated with knowledge creation, while Adhocracy has a greater effect on knowledge application, and market has a stronger effect on knowledge dissemination and storage. However, hierarchical culture has an insignificant effect on knowledge creation and the lowest effects on the rest of Knowledge Management processes. Therefore, the study concluded that knowledge management success is determined by developing a balanced portfolio of cultural traits from clan, adhocracy and market cultures.

The Impact of e-Learning Systems on Motivating Students and Enhancing Their Outcomes During COVID-19: A Mixed-Method Approach.

e-Learning is a key strategy in the course of higher education to improve the results of the educational process and stimulate student motivation. The COVID-19 pandemic imposed on Algerian universities to adopt e-Learning systems to search for effectiveness and efficiency of academic approaches. This paper seeks to remedy these problems by analyzing the impact of e-Learning systems on student motivation and outcomes. A mixed-method approach was used in the data analysis. We conducted the study as a survey, with data being gathered via questionnaires distributed to 398 students. The questionnaire includes open questions that were qualitatively analyzed using content analysis with Nvivo, besides Likert scale questions were quantitatively analyzed and modeled using Structural equation modeling (SEM) with Amos to accomplish the path analysis of the research model. The results of the study showed that student motivation (Attention, Relevance, Confidence, and Satisfaction) and student outcomes (knowledge, skills, and attitudes) are significantly affected by e-Learning systems (Technical and electronic requirements, personal requirements, perceived value, and credibility of e-Learning). The key findings are discussed, and they provide recommendations for future research.

The impacts of total quality management practices in Algerian higher education institutions.

Algerian universities rely on total quality management. TQM is one of the most successful strategic options for improving the quality of higher education. In addition, achieving academic accreditation and progress in international rankings. The study aims to address relevant contemporary issues by examining the impact of total quality management on the quality of higher education. The data were analyzed using a mixed-method approach; the study was done as a survey, with data collected via questionnaires issued to 610 students. The questionnaire included Likert scale items that were quantitatively evaluated and modeled using structural equation modeling (SEM) using Amos to accomplish the path analysis of the research model. Furthermore, qualitative data were acquired through interviews with 24 professors who are members of the Quality Cells, and qualitative data were evaluated using content analysis with NVivo. The study findings revealed that TQM has a direct and significant impact on the quality of graduates, scientific research, and community service in Algerian universities. The main results have been presented, and recommendations for future research are made.

Key Sectors in the Economy of Saudi Arabia.

This study shows the key sector for the economy of Saudi Arabia based on input-output model analyses. They derived the analyses from the economy of the Kingdom of Saudi Arabia (KSA) using 35 economic sectors. We found that four leading sectors exceeded the values of the linkage coefficients with a value of 1, represented by both chemicals and pharmaceutical products, namely, manufacturing basic metals (S13), transportation and storage (S24), and other business sector services (S31). According to the unbalanced growth theory, more attention is paid to these sectors that are the primary engine for the rest of the sectors and their growth. The results obtained are beneficial for success of the economic policy of Saudi Arabia. By observing the different influences, it is possible to identify the policies expected to have more significant indirect impacts on other sectors in Saudi Arabia and are likely to develop a prudent economic policy. Given the economic dependence on oil, it is also essential to be acquainted with the different sectors that are probable to have an overall effect on the economy for strategic and operationally effective analysis that can help.

COVID-19 Deaths Cases Impact on Oil Prices: Probable Scenarios on Saudi Arabia Economy.

The purpose of this paper is to discuss death cases on the World, exacerbated investor fears, uncertainties, and increased volatility of crude oil prices in financial markets. The reaction absorbed the epidemic gradually until January 22. Still, the market situation changed soon with a sharp drop in prices, and prices slowly recovered after that until June 14. The data of this research using an econometric model, the ARDL (Autoregressive Distributed Lag), according to the Gets methodology, using daily data, January 22 -June 14, 2020. Our ARDL shows, the death ratio has a significant negative effect on oil price dynamics. However, the death ratio has an indirect impact on volatility in Crude Oil prices. The findings show that the death toll of COVID-19 has a significant impact on oil prices in Saudi Arabia (KSA). However, the preliminary results mainly influence by the situation reported in the USA. When we assess the case outside the USA, and we see the positive effect of the COVID-19 death figures on oil prices, therefore, stress the amplification of death-related risks to the financial market and the real economy, caused by increased, policy-induced economic uncertainty in the United States.

E-Learning Research Trends in Higher Education in Light of COVID-19: A Bibliometric Analysis.

This paper provides a broad bibliometric overview of the important conceptual advances that have been published during COVID-19 within "e-learning in higher education." E-learning as a concept has been widely used in the academic and professional communities and has been approved as an educational approach during COVID-19. This article starts with a literature review of e-learning. Diverse subjects have appeared on the topic of e-learning, which is indicative of the dynamic and multidisciplinary nature of the field. These include analyses of the most influential authors, of models and networks for bibliometric analysis, and progress towards the current research within the most critical areas. A bibliometric review analyzes data of 602 studies published (2020-2021) in the Web of Science (WoS) database to fully understand this field. The data were examined using VOSviewer, CiteSpace, and KnowledgeMatrix Plus to extract networks and bibliometric indicators about keywords, authors, organizations, and countries. The study concluded with several results within higher education. Many converging words or sub-fields of e-learning in higher education included distance learning, distance learning, interactive learning, online learning, virtual learning, computer-based learning, digital learning, and blended learning (hybrid learning). This research is mainly focused on pedagogical techniques, particularly e-learning and collaborative learning, but these are not the only trends developing in this area. The sub-fields of artificial intelligence, machine learning, and deep learning constitute new research directions for e-learning in light of COVID-19 and are suggestive of new approaches for further analysis.