The advent of Artificial Intelligence (AI) has transformed Learning Management Systems (LMSs), enabled personalized adaptation and facilitated distance education. This study employs a bibliometric analysis based on PRISMA-2020 to examine the integration of AI in LMSs from an educational perspective. Despite the rapid progress observed in this field, the literature reveals gaps in the effectiveness and acceptance of virtual assistants in educational contexts. Therefore, the objective of this study is to examine research trends on the use of AI in LMSs. The results indicate a quadratic polynomial growth of 99.42%, with the years 2021 and 2015 representing the most significant growth. Thematic references include authors such as Li J and Cavus N, the journal Lecture Notes in Computer Science, and countries such as China and India. The thematic evolution can be observed from topics such as regression analysis to LMS and e-learning. The terms e-learning, ontology, and ant colony optimization are highlighted in the thematic clusters. A temporal analysis reveals that suggestions such as a Cartesian plane and a league table offer a detailed view of the evolution of key terms. This analysis reveals that emerging and growing words such as Learning Style and Learning Management Systems are worthy of further investigation. The development of a future research agenda emerges as a key need to address gaps.
Background: Digital transformation in the sports industry has become increasingly crucial for sustainable development, yet comprehensive empirical evidence on policy effectiveness and risk management remains limited. Purpose: This study investigates the impact of policy support and risk factors on digital transformation in sports companies, examining heterogeneous effects across different firm characteristics and regional contexts. Methods: Using panel data from 168 sports companies listed on China’s A-shares markets and the New Third Board from 2019 to 2023, this study employs multiple regression analyses, including baseline models, instrumental variables estimation, and robustness tests. The digital transformation level is measured through a composite index incorporating digital infrastructure, capability, and innovation dimensions. Results: The findings reveal that policy support significantly enhances digital transformation levels (coefficient = 0.238, p < 0.01), while financial risks demonstrate the strongest negative impact (−0.162, p < 0.01). Large firms and state-owned enterprises show stronger responses to policy support (0.312 and 0.278, respectively, p < 0.01). Regional development levels significantly moderate the effectiveness of policy implementation. Conclusions: The study provides empirical evidence for the differential effects of policy support and risk factors on digital transformation across various firm characteristics. The findings suggest the need for differentiated policy approaches considering firm size, ownership structure, and regional development levels. Implications: Policy makers should develop targeted support mechanisms addressing specific challenges faced by different types of firms, while considering regional disparities in digital transformation capabilities.
The Yangjiabu Kite Festival, originating over 2000 years ago in Shandong Province, China, stands as a testament to the enduring cultural heritage and artistic traditions of kite flying. This research explores the historical origins, cultural symbolism, festival format, community engagement, and international exposure of the Yangjiabu Kite Festival, shedding light on its evolution and impact over time. Findings reveal the festival’s deep roots in ancient Chinese traditions, its role as a platform for showcasing cultural diversity and craftsmanship, and its significance in promoting tourism, cultural exchange, and soft power projection for Shandong Province. Lessons learned from the Yangjiabu Kite Festival offer valuable insights for cross-cultural application, event management, cultural diplomacy, and community development. Suggestions for future research include comparative studies, longitudinal assessments, audience research, and policy analysis to further explore the dynamics and implications of cultural festivals in a global context. Overall, the research underscores the importance of cultural festivals as vehicles for cultural preservation, tourism promotion, and intercultural dialogue, fostering mutual understanding and appreciation across borders.
The aim of this study is to examine the contributions of the components of employee engagement on knowledge-sharing behavior alongside possible mediating effect of management support. This study collected data from 395 respondents purposively selected from pharmaceutical organizations in Bangladesh. For input and incorporation of sample data, SPSS version 26 was used, whereas the PLS-SEM (version-4) tool was used to test the hypotheses relationships. The findings reveal significant positive effects of adaptation, devotion, and vitality on both knowledge sharing behavior and management support. Adaptation to new technologies and processes enhances employees’ ability and intention to share knowledge, facilitated by robust management support. Similarly, devotion and vitality among employees fosters a supportive environment that is conducive for knowledge exchange. Management support emerges as a critical mediator, amplifying the positive impacts of adaptation, devotion, and vitality on organizational outcomes. These findings address a critical gap in understanding the conditions that enhance knowledge-sharing behaviors in highly regulated industries and provides a valuable framework for organizations to nurture knowledge-sharing cultures that will drive innovation and resilience within emerging markets.
This study focuses on the use of the Soil and Water Assessment Tool (SWAT) model for water budgeting and resource planning in Oued Cherraa basin. The combination of hydrological models such as SWAT with reliable meteorological data makes it possible to simulate water availability and manage water resources. In this study, the SWAT model was employed to estimate hydrological parameters in the Oued Cherra basin, utilizing meteorological data (2012–2020) sourced from the Moulouya Hydraulic Basin Agency (ABHM). The hydrology of the basin is therefore represented by point data from the Tazarhine hydrological station for the 2009–2020 period. In order to optimize the accuracy of a specific model, namely SWAT-CUP, a calibration and validation process was carried out on the aforementioned model using observed flow data. The SUFI-2 algorithm was utilized in this process, with the aim of enhancing its precision. The performance of the model was then evaluated using statistical parameters, with particular attention being given to Nash-Sutcliffe efficiency (NSE) and coefficient of determination (R2). The NSE values for the study were 0.58 for calibration and 0.60 for validation, while the corresponding R2 values were 0.66 and 0.63. The study examined 16 hydrological parameters for Oued Cherra, determining that evapotranspiration accounted for 89% of the annual rainfall, while surface runoff constituted only 6%. It also showed that groundwater recharge was pretty much negligible. This emphasized how important it is to manage water resources effectively. The calibrated SWAT model replicated flow patterns pretty well, which gave us some valuable insights into the water balance and availability. The study’s primary conclusions were that surface water is limited and that shallow aquifers are a really important source of water storage, especially for irrigation during droughts.
Managing business development related to the innovation of intelligent supply chains is an important task for many companies in the modern world. The study of management mechanisms, their content and interrelations of elements contributes to the optimization of business processes and improvement of efficiency. This article examines the experience of China in the context of the implementation of intelligent supply chains. The study uses the methods of thematic search and systematic literature review. The purpose of the article is to analyze current views on intelligent supply chain management and identify effective business management practices in this area. The analysis included publications devoted to various aspects of supply chain management, innovation, and the implementation of digital technologies. The main findings of the article are as follows: Firstly, the key elements of intelligent supply chain management mechanisms are identified, secondly, successful experiences are summarized and the main challenges that companies face in their implementation are identified. In addition, the article focuses on the gaps in research related to the analysis of successful experiences and the reasons for achieving them.
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