Table of Contents
In this paper advanced Sentiment Analysis techniques were applied to evaluate public opinions reported by rail users with respect to four major European railway companies, i.e., Trenitalia and Italo in Italy, SNCF in France and Renfe in Spain. Two powerful language models were used, RoBERTa and BERT, to analyze big amount of text data collected from a social platform dedicated to customers reviews, i.e., TrustPilot. Data concerning the four European railway companies were first collected and classified into subcategories related to different aspects of the railway sector, such as train punctuality, quality of on-board services, safety, etc. Then, the RoBERTa and BERT models were developed to understand context and nuances of natural language. This study provides a useful support for railways companies to promote strategies for improving their service.
This study aims to explore the research on Chinese higher education policy from 2005 to 2024 through a bibliometric analysis. It is revealed that a continuous growth trend and sustained academic interest in this field. Mainland China leads in publication quantity, showcasing the active involvement of Chinese scholars in higher education policy research. Institutions like Peking University, the University of Hong Kong, and Beijing Normal University play significant roles in this research domain. The focus of research has shifted from student attitudes to international students, teachers, innovation models, changing demands, and urban education development, reflecting a growing emphasis on sustainability and internationalization. The study highlights the positive development trajectory of Chinese higher education policy research, with expanding research focuses and deepening concerns for sustainability and internationalization.
Modernizing the Internet of Things in Islamic boarding schools is essential to eliminate backwardness and skills gaps. Santri must have cognitive, affective, psychomotor, and creative intelligence to be ready to enter the industrial and business world. The students’ need for information transparency can be resolved using technology. This is because the empowerment of the Internet of Things has become a separate part of Islamic boarding school activities with students who can connect in real-time. This research aims to analyze current conditions and stakeholder involvement regarding the application of the Internet of Things in innovative Islamic boarding school services in the era of disruption. The Descriptive Method and Individual Interest Matrix Analysis were used by involving 130 respondents from the internal environment of the Daarul Rahman Islamic boarding school and completing the questionnaire through FGD (Focus Group Discussion) with the leaders of the Daarul Rahman Islamic boarding school. The results show that the current condition of Islamic boarding schools is that most need to learn or understand IoT, even though they are enthusiastic about learning new things and flexible in accepting change. The challenges required in implementing IoT are financial investment, increasing human resources through training, and synergy between Islamic boarding school policy makers. Mutually supportive and solid conditions are required between foundations, school principals, and school committees to implement IoT at Daarul Rahman Islamic Boarding School. Collaboration with various parties is needed because the implementation of IoT cannot be done alone by Islamic boarding schools but with the support of various related parties.
Objectives: The unprecedented COVID-19 pandemic has intensified the stress on blood banks and deprived the blood sources due to the containment measures that restrict the movement and travel limitations among blood donors. During this time, Malaysia had a significant 40% reduction in blood supply. Blood centers and hospitals faced a huge challenge balancing blood demand and collection. The health care systems need a proactive plan to withstand the uncertain situation such as the COVID-19 pandemic. This study investigates the psychosocial factors that affect blood donation behavior during a pandemic and aims to propose evidence-based strategies for a sustainable blood supply. Study design: Qualitative design using focus group discussion (FGD) was employed. Methods: Data were acquired from the two FGDs that group from transfusion medicine specialists (N = 8) and donors (N = 10). The FGD interview protocol was developed based on the UTM Research Ethics Committee’s approval. Then, the data was analyzed using Nvivo based on the General Inductive Approach (GIA). Results: Analysis of the text data found that the psychology of blood donation during the pandemic in Malaysia can be classified into four main themes: (i) reduced donation; (ii) motivation of donating blood; (iii) trends of donation; and (iv) challenges faced by the one-off, occasional, and non-donors. Conclusions: Based on the emerging themes from the FGDs, this study proposes four psycho-contextual strategies for relevant authorities to manage sustainable blood accumulation during the pandemic: (1) develop standard operating procedure for blood donors; (2) organize awareness campaigns; (3) create a centralized integrated blood donors database; and (4) provide innovative Blood Donation Facilities.
The growth of mobile Internet has facilitated access to information by minimizing geographical barriers. For this reason, this paper forecasts the number of users, incomes, and traffic for operators with the most significant penetration in the mobile internet market in Colombia to analyze their market growth. For the forecast, the convolutional neural network (CNN) technique is used, combined with the recurrent neural network (RNN), long short-term memory network (LSTM), and gated recurrent unit (GRU) techniques. The CNN training data corresponds to the last twelve years. The results currently show a high concentration in the market since a company has a large part of the market; however, the forecasts show a decrease in its users and revenues and the growth of part of the competition. It is also concluded that the technique with the most precision in the forecasts is CNN-GRU.
This research aims to test the effect that the implementation of green practices at a major sport tourism event, the Badminton World Championships in Huelva (Spain), has on the future intention of spectators to return to similar sport events. A total of 523 spectators who attended the event were randomly selected and self-administered in the presence of the interviewer. A confirmatory factor analysis of the model and a multi-group analysis were carried out. Sporting events have a great impact on the environment in which they are organised, mainly when they are linked to tourism, whether at an economic, social or environmental level. The results indicated that green practices indirectly influence spectators’ future intentions through emotions and satisfaction, direct antecedents. In addition, green practices directly affect both image and trust, and indirectly affect satisfaction. In conclusion, green practices are a variable to be taken into account when planning the organisation of a sporting event that aims to consolidate itself in the tourism and sports services market.
Physical sampling of water on site is necessary for various applications like drinking water quality checking in lakes and checking for contaminants in freshwater systems. The use of water surface vehicles is a promising technology for monitoring and sampling water bodies, and they offer several advantages over traditional monitoring methods. This project involved designing and integrating a drone controller, water collection sampling contraption unit, and a surveillance camera system into a water surface vehicle (WSV). The drone controller unit is used to operate the boat from the starting location until the location of interest and then back to the starting location. The drone controller has an autopilot system where the operator can set a course and be able to travel following the path set, whereas the WSV will fight the external forces to keep itself in the right position. The water collection sampling unit is mounted onto WSV so when it travels to the location, it can start collecting and holding water samples until it returns to the start location. The field of view (FOV) surveillance camera helps the operator to observe the surrounding location during the operation. Experiments were conducted to determine the operational capabilities of the robot boat at the Ayer Keroh Lake. The water collection sampling contraption unit collected samples from 44 targeted areas of the lake. The comprehensive examination of 14 different water quality parameters were tested from the collected water samples provides insights into the factors influencing the pollution and observation of water bodies. The successful design and development of a water surface surveillance and pollution tracking vehicle marks the key achievements of this study. The developed collection and surveillance unit holds the potential for further refinement and integration onto various other platforms. They are offering valuable assistance in water body management, coastal surveillance, and pollution tracking. This system opens up new possibilities for comprehensive water body assessments, contributing to the advancement of sustainable and efficient water testing. Through careful sampling efforts, a thorough overview of the substances presents in the water collected from Ayer Keroh Lake has been compiled. This in-depth analysis provides important insights into the lake’s current condition, offering valuable information about its ecological health.
This study investigates the impact of generative AI on social media marketers’ job attitudes and performance, examining the roles of person-organization fit (PO-fit) and person-job fit (PJ-fit). As generative AI transforms marketing practices, understanding its effects on employees is crucial. A survey of 340 social media marketers using generative AI tools was conducted. Structural equation modeling revealed that both PO-fit and PJ-fit positively influence job involvement, with PJ-fit showing a stronger effect. Job involvement, in turn, significantly enhances job satisfaction, which positively impacts job performance. These findings suggest that aligning employees’ values and skills with organizational AI strategies and job requirements is critical in fostering positive work outcomes in AI-driven marketing environments. The study contributes to the literature on AI’s impact on human resource management and provides practical insights for organizations implementing AI technologies. This research highlights the importance of ensuring compatibility between employees and AI-enhanced work environments, as well as the need for continuous skill development and organizational culture adaptation. Future research could explore the long-term effects of AI integration on employee attitudes and investigate potential moderating factors in these relationships.
Many financial crises have occurred in recent decades, such as the International Debt Crisis of 1982, the East Asian Economic Crisis of 1997–2001, the Russian economic crisis of 1992–1997, the Latin American debt Crisis of 1994–2002, the Global Economic Recession of 2007–2009, which had a strong impact on international relations. The aim of this article is to create an econometric model of the indicator for identifying crisis situations arising in stock markets. The approach under consideration includes data for preprocessing and assessing the stability of the trend of time series using higher-order moments. The results obtained are compared with specific practical situations. To test the proposed indicator, real data of the stock indices of the USA, Germany and Hong Kong in the period World Financial Crisis are used. The scientific novelty of the results of the article consists in the analysis of the initial and given initial moments of high order, as well as the central and reduced central moments of high order. The econometric model of the indicator for identifying crisis situations arising considered in the work, based on high-order moments plays a pivotal role in crisis detection in stock markets, influencing financial innovations in managing the national economy. The findings contribute to the resilience and adaptability of the financial system, ultimately shaping the trajectory of the national economy. By facilitating timely crisis detection, the model supports efforts to maintain economic stability, thereby fostering sustainable growth and resilience in the face of financial disruptions. The model’s insights can shape the national innovation ecosystem by guiding the development and adoption of monetary and financial innovations that are aligned with the economy’s specific needs and challenges.
The Hungarian tourism and hospitality industry has faced serious challenges in recent years. The tourism and hospitality sector has been confronted with severe challenges in recent years. Even after the end of the pandemic, the industry has not seen the expected recovery, as rising inflation, declining discretionary income and a lack of foreign tourists have further hampered the industry. The hotel market in Budapest in particular has been significantly affected by these developments. Despite the difficulties, investors continue to see opportunities in the market. One example is the purchase by a group of real estate investors of an under-utilised leisure centre in District VII, which they intend to convert into a hotel. Our study is part of this project and its primary objective is to define the parameters of the future hotel and analyse the market opportunities and challenges. Our research focuses on the hotel market in Budapest and uses methods such as benchmarking, STEEP and SWOT analyses, as well as four in-depth interviews with key players in the market. The benchmarking examined the operations of hotels in the capital, while the in-depth interviews provided practical experience and insider perspectives. On the basis of the interviews and analyses, the study identifies possible directions for improvement and factors for competitive advantage.
Cultural heritage tourism requires effective digital solutions to meet evolving tourist needs and balance site preservation with sustainable development. Existing research predominantly focuses on technical feasibility and functionality, with limited attention to diverse tourist demands. This study addresses this gap by investigating tourists’ multi-dimensional needs for cultural heritage tourism applications using the Kano model. Through a case study of Sancai Town, a renowned cultural heritage site in China, 22 demand items were initially identified through semi-structured interviews. A questionnaire survey of 422 tourists was then conducted to categorize these demand items into must-be, one-dimensional, attractive, and indifferent needs. The results indicate that must-be needs, such as navigation and attraction information, form the foundation of tourist expectations. One-dimensional needs, including multimedia presentations and experience sharing, directly influence satisfaction. Attractive needs, such as immersive experiences and personalized services, enhance emotional engagement. Based on this classification, differentiation design strategies are proposed to guide the development of tourism applications that effectively address these needs and enhance the travel experience. The findings contribute to the theoretical understanding of demand-driven digital innovation in cultural heritage tourism and provide practical insights for innovative tourism development in Sancai Town and similar heritage sites. This research advances a tourist-centric perspective to balance cultural preservation and tourism growth, fostering the sustainable integration of heritage and tourism.
This study investigates pedagogical content knowledge (PCK) among teachers teaching mathematics at the preschool level in Colombia, highlighting the importance of integrating mathematical knowledge with innovative and effective pedagogical strategies. Using a mixed exploratory and transactional methodology, the perceptions and practices of 82 teachers were examined, focusing on their understanding of mathematical content, pedagogical skills, and knowledge of children’s cognitive development. The findings reveal a significant gap in teachers’ understanding of these concepts, indicating a critical need to strengthen PCK among teachers. To this end, training should be provided to enable teachers to foster meaningful and contextualized mathematical learning in preschool students. The study suggests reviewing teacher training curricula and fostering the development of pedagogical strategies that prioritize conceptual understanding and mathematical reasoning. Additionally, it identifies critical areas for improvement and offers concrete recommendations for transforming mathematics teaching in preschool education. To enhance the quality of mathematics education, several measures are proposed: ensuring continued availability of training programs for teachers, encouraging collaboration between educators, adopting constructivist approaches, and helping teachers understand the value of mathematics learning outside the school.
This study empirically examines the complex relationship between materialism and economic motivation, proposing an inverted U-shaped relationship. The research analyzes three dimensions of materialism: happiness pursuit, social recognition, and uniqueness, and their impact on economic motivation. The findings suggest that materialism, when balanced, positively influences economic motivation without causing adverse effects. This relationship remains consistent across demographic characteristics and life satisfaction levels, challenging the traditional negative view of materialism. The implications of these findings extend to marketing strategies, policy design, and infrastructure development, offering actionable insights for real-world contexts. This research underscores the importance of balancing materialistic values to foster sustainable economic growth and well-being.
The ongoing dissemination of globalization and digitalization may suggest that personal relationships are becoming less crucial in the context of retail banking and financial services. In Hungary, in addition to private banking, which is associated with high income levels, personal banking also plays an important role. The objective of this study is to develop a model that can identify the factors that determine customer satisfaction and their relative importance. Furthermore, the aim is to incorporate gender and age as moderator variables to identify demographic differences in satisfaction. The analysis was conducted via a questionnaire survey in October to November 2023 employing a purposive sampling approach in a university environment, as the respondents are likely to possess the highest level of existing financial knowledge within this population. The 214 valid responses were analyzed using the Partial Least Squares Structural Equation Modeling (PLS-SEM) approach, with the objective of contributing to the development of theory in this field of study. The results demonstrate that perception (β = 0.519) and reliability (β = 0.253) collectively explained 51.8% of the variance in satisfaction. Moreover, the results indicate that perception accounts for 49.2% of the variance in reliability, suggesting the existence of an indirect effect on satisfaction. Therefore, the findings suggest that, despite the advent of digital banking, face to face service remains a pertinent concern in Hungary, and financial institutions should prioritize the factors that shape customer satisfaction. The study contributes to the literature and to the development of customer loyalty strategies for banks based on these findings.
The tourism sector in the Aseer region of Saudi Arabia is experiencing significant growth and development, aligning with the country’s Vision 2030 strategic framework. However, rapid growth can lead to strategic drift if not managed with vigilance. This study aims to examine the role of strategic vigilance in reducing strategic drift in the tourism sector. The study employs a quantitative approach, utilizing a questionnaire distributed to a sample of 220 staff and directors from the tourism sector. The questionnaire measures the level of strategic vigilance and the level of strategic drift. The study hypothesizes a statistically significant positive relationship between strategic vigilance and reducing strategic drift. Data analysis involves exploratory factor analysis, confirmatory factor analysis, and structural equation modeling. The findings are expected to provide insights into the effectiveness of strategic vigilance in mitigating strategic drift and offer recommendations for enhancing the tourism sector’s resilience and adaptability to accelerated environmental changes.
With its inherent characteristics of decentralization, immutability, and transparency, blockchain technology presents a promising opportunity to revolutionize the South African food supply chains. Blockchain technology, with its decentralized, immutable, and secure nature, offers solutions to these challenges by improving traceability and accountability across the supply chain. This study investigates the role of blockchain technology in enhancing transparency in the food supply chain among small and medium enterprises in South Africa. SMEs form a critical part of the country’s agri-food sector but face challenges such as food fraud, inefficient inventory management, and lack of transparency, which impact food safety and trust. The research adopts a mixed-method approach, utilizing the Technology-Organization-Environment framework and Institutional Theory to explain blockchain adoption among SMEs. The results demonstrate that blockchain-enabled practices, such as smart contracts, records traceability, production tracking, and distribution monitoring, significantly enhance supply chain transparency. The findings highlight blockchain’s potential to increase operational efficiency, regulatory compliance, and stakeholder trust. This research provides valuable insights for policymakers and practitioners, emphasizing the need for regulatory support and strategic investment in blockchain solutions to promote sustainability and competitiveness in the agri-food sector.
The golden visa is a regulation designed to facilitate foreign nationals through a residence permit scheme with an emphasis on investment and citizenship. This research aims to look at the development of the golden visa as an innovation policy, and find out how its implications for the flow of foreign investment into Indonesia. This research uses online research methods (ORM) to discover new facts, information and conditions through technology and internet searches. The aspects used to conduct analysis in this descriptive qualitative research are using innovation policy instruments which include regulatory, economic, financial, and soft instruments. The research findings show that the golden visa as an innovation policy has great potential to support national development through investment in priority sectors. However, its implementation needs to be done carefully with strict supervision and inclusive regulations so as to mitigate risks such as money laundering and property price inflation. That way, golden visas can encourage sustainable and inclusive economic growth through the smooth flow of incoming foreign investment.
Social Prescribing (SP) is an approach which aims of improving health and well-being and connecting patients to community services. Examples of these services include physical activity and cultural activities. Despite its benefits, SP has still not been fully implemented in Portugal. This case study is part of a larger study on Social Prescribing Local System (SPLS) implementation, which comprised a quantitative approach, a pilot study and a qualitative approach, and aims at exploring patients’ and healthcare workers’ perspectives on SP. The study was carried out to understand the motivations of different stakeholders for participating in the pilot project, the anticipated benefits for patients, healthcare professionals, and the health unit, as well as their perceptions and experiences within the scope of the SP project. Data collection was carried out in December 2020 through semi-structured individual interviews and a focus group. A total of seven participants were included, of which one patient, one museum representative and five healthcare professionals. Different common dimensions related to SP emerge, including health and well-being, social interaction and community engagement, accessibility and inclusivity, motivation and adherence, collaboration and coordination, and education and awareness. The patient considered the adequacy of the activity to the patient’s state of health and capabilities, adoption of a phased approach, with a focus on progress, in order to promote long-term adherence as facilitators. For the museum, disseminating its activities to healthcare professionals and patients through different channels such as posters at the health center, social media pages, and training sessions can significantly enhance visibility and engagement, while direct phone contact and digital publications can further promote adherence, ensuring a comprehensive and coordinated approach to patient participation and institutional benefit. Healthcare professionals identified several benefits, including reduction of social isolation and sedentarism, as well as a means of strengthening the therapeutic relationship with patients. The design and implementation of SP programs should be participative and involve all stakeholders participating in the process. Barriers to adherence included time for activity and the associated costs or prerequisites, availability of activities and lack of perceived interest in health.
This study meticulously explores the crucial elements precipitating corporate failures in Taiwan during the decade from 1999 to 2009. It proposes a new methodology, combining ANOVA and tuning the parameters of the classification so that its functional form describes the data best. Our analysis reveals the ten paramount factors, including Return on Capital ROA(C) before interest and depreciation, debt ratio percentage, consistent EPS across the last four seasons, Retained Earnings to Total Assets, Working Capital to Total Assets, dependency on borrowing, ratio of Current Liability to Assets, Net Value Per Share (B), the ratio of Working Capital to Equity, and the Liability-Assets Flag. This dual approach enables a more precise identification of the most instrumental variables in leading Taiwanese firms to bankruptcy based only on financial rather than including corporate governance variable. By employing a classification methodology adept at addressing class imbalance, we substantiate the significant influence these factors had on the incidence of bankruptcy among Taiwanese companies that rely solely on financial parameters. Thus, our methodology streamlines variable selection from 95 to 10 critical factors, improving bankruptcy prediction accuracy and outperforming Liang’s 2016 results.
Formation of the latest scientific and methodological principles and the determination of the most important directions of the paradigm of the analysis of artistic creativity and text have been represented as actual problems of the theory of modern Kazakh literary criticism. The purpose of the work is to consider and analyze the modern concepts of Kazakh literary criticism, to evaluate the contribution of scientists from the period of independence of Kazakhstan in the development of theoretical analysis and interpretation of the artistic originality of national literature. The article discusses new trends in the theory of Kazakh literary criticism, changes in methodology, which are due to the leading positions of world literary criticism. In this regard, the article offers an analytical review of the main scientific and theoretical studies in the field of literary criticism, defines the evolution of the concepts of scientific and theoretical thought, identifies the principles and main aspects of the study of literature in a new way, shows certain achievements in close relationship with historical stages, as well as tasks future research; literary-theoretical and philosophical-aesthetic searches in modern Kazakh literary criticism are evaluated, the prospects for its development are determined.
Autism is often referred to as autism spectrum disorder that constitutes a diverse group of conditions related to brain development (which is a neurodevelopmental disorder). Autism spectrum disorder patients often have difficulty communicating and interacting socially, and are characterized by restricted and repetitive patterns of behavior and interests that have been shown to be the same in cultures of countries around the world. However, the interpretation of symptoms and recognition in terms of policies and laws in countries are not the same. Accordingly, some countries recognize autism spectrum disorder as one of the types of disability and some countries do not, including Vietnam. Currently, Vietnam’s Law on Persons with Disabilities 2010 does not recognize the term “autism” in the Law. At the same time, there is a lack of legal issues related to the “autism spectrum” from the time of diagnosis such as policies on practical support appropriate to each individual’s needs and interests so that they can develop and be integrated in the medical field, education and enjoyment of other benefits such as persons with disabilities. This is an overlooked term that leads to the community having a misperception of “autism” when they are not aware that autism is a disease or a disability, what causes autism and why, etc. The article points out the current situation of adjustment by policies and laws on autistic people in Vietnam. On that basis, the article focuses on analyzing the contents that need to reform those policies and laws to ensure human rights of autistic people and their families.
Food safety in supply chains remains a critical concern due to the complexity of global distribution networks. This study develops a conceptual framework to evaluate how food safety risks influence supply chain performance through predictive analytics. The framework identifies and minimizes food safety risks before they cause serious problems. The study examines the impact of food safety practices, supply chain transparency, and technological integration on adopting predictive analytics. To illustrate the complex dynamics of food safety and supply chain performance, the study presents supply chain transparency, technological integration, and food safety practices and procedures as independent variables and predictive analytics as a mediator. The results show that supply chain managers’ capacity to anticipate and control risks related to food safety can be improved by predictive analytics, leading to safer food production and distribution methods. The research recommends that businesses create scalable cloud-based predictive model solutions, combine data sources, and employ cutting-edge AI and machine learning tools. Companies should also note that strong, data-driven approaches to food safety require cooperative data sharing, regulatory compliance, training initiatives and ongoing improvement.
The proportion of elderly people is growing steadily in many countries, and this trend is expected to continue. As a result, ageism—negative discrimination often tied to perceptions of the elderly—becomes especially harmful. Ageism prevents older generations from being fully accepted by society and, in turn, hinders their ability to adapt to today’s technological changes. In this article, we present the results of our survey mapping the extent of ageism among youth in Uzbekistan, known for its cultural tolerance in Central Asia, and in Hungary, a more individualistic society in Central Europe. To interpret the survey results accurately, we included specific questions to measure social desirability bias, enabling a realistic comparison of ageism levels between the two countries. Data was collected through a survey translated into multiple languages, with a final sample of nearly 400 respondents, each either currently pursuing or already holding a college-level diploma. Our methodological approach was twofold. First, we conducted simple chi-square tests to compare levels of negative and positive ageism between the two countries under study. Upon finding significant differences, we used multivariable OLS regression to explain the variance in types of ageism in Uzbekistan and Hungary, accounting for the possible effects of social desirability bias. Uzbek youth demonstrated higher levels of positive ageism and lower levels of negative ageism compared to Hungarian youth. This finding confirms that the cultural tolerance in Uzbek society remains strong and, in many ways, could serve as a model for Hungary. Additionally, our literature review highlights that adequate infrastructure is essential for a society to treat older adults equitably alongside other citizens.
This study addresses the rising concerns of technostress experienced by teachers due to the increased reliance on educational technology in both classroom and online settings. Technostress, defined as the adverse psychological effects arising from the use of information communication technologies, has been documented to impact teacher performance and overall well-being. Despite the importance of educational technology in enhancing teaching and learning experiences, many educators report elevated levels of anxiety, stress, and pressures associated with their use of these tools. This study presents practical strategies to help teachers alleviate or prevent technostress while using educational technology. This study used a quantitative approach with a survey conducted among 113 university and schoolteachers. The data analysis included frequency and percentage distribution of categorical variables, Cronbach’s alpha for reliability, chi-square test, and exploratory factor analysis to identify strategies for symptom prevention. The results indicated that while many teachers experienced symptoms of technostress due to several factors, some did not. The study concluded with specific strategies, and many teachers agreed highly. The implications of this study are profound for educational institutions, policymakers, and teacher training programs as they underscore the necessity of providing comprehensive training, support, and resources to help educators manage technostress effectively. By integrating these strategies into professional developmental programs and fostering a supportive teaching environment, schools and universities can promote better mental health for teachers, improving students’ educational outcomes.
The present study focuses on improving Cognitive Radio Networks (CRNs) based on applying machine learning to spectrum sensing in remote learning scenarios. Remote education requires connection dependability and continuity that can be affected by the scarcity of the amount of usable spectrum and suboptimal spectrum usage. The solution for the proposed problem utilizes deep learning approaches, namely CNN and LSTM networks, to enhance the spectrum detection probability (92% detection accuracy) and consequently reduce the number of false alarms (5% false alarm rate) to maximize spectrum utilization efficiency. By developing the cooperative spectrum sensing where many users share their data, the system makes detection more reliable and energy-saving (achieving 92% energy efficiency) which is crucial for sustaining stable connections in educational scenarios. This approach addresses critical challenges in remote education by ensuring scalability across diverse network conditions and maintaining performance on resource-constrained devices like tablets and IoT sensors. Combining CRNs with new technologies like IoT and 5G improves their capabilities and allows these networks to meet the constantly changing loads of distant educational systems. This approach presents another prospect to spectrum management dilemmas in that education delivery needs are met optimally from any STI irrespective of the availability of resources in the locale. The results show that together with machine learning, CRNs can be considered a viable path to improving the networks’ performance in the context of remote learning and advancing the future of education in the digital environment. This work also focuses on how machine learning has enabled the enhancement of CRNs for education and provides robust solutions that can meet the increasing needs of online learning.
This study investigates the role of Chat-GPT with augmented reality applications in enhancing tourism experiences in Thailand, focusing on behavioral intentions and innovation adoption to reduce stress in the tourism industry. The research addresses two key objectives: identifying factors driving consumers’ behavioral intentions to adopt AR apps and evaluating the robustness of a modified innovation framework for analyzing these intentions. A conceptual model integrating innovativeness, attitudes, perceived enjoyment, and revisit intentions was developed and tested using Structural Equation Modeling with data from 430 Thai tourists who have one to three years of mobile application experience. The findings highlight that service and technology innovation significantly influence perceived enjoyment and attitude, which in turn mediate the impact on behavioral intention to adopt augmented reality applications. At a significance level of p < 0.001, perceived enjoyment and attitude were identified as critical determinants of BI, underscoring the importance of intrinsic user experiences. Tourists are more likely to adopt augmented reality technologies based on personal perceptions and enjoyment rather than external recommendations. This research provides actionable insights for stakeholders in the tourism technology ecosystem, including technology providers, marketers, and policymakers. By emphasizing the interplay of social, emotional, and hedonic factors in shaping user attitudes, the study introduces a robust framework for advancing augmented reality applications in tourism. The findings underscore the importance of user-centric design to drive technology adoption and offer strategic guidance for developers and entrepreneurs aiming to enhance tourism experiences through innovative augmented reality solutions.
This paper investigates the factors influencing credit growth in Kosovo, focusing on the relationship between credit activity and key economic variables, including GDP, FDI, CPI, and interest rates. Its analysis targets loans issued to businesses and households in Kosovo, employing a VAR model integrated into a VEC model to investigate the determinants of credit growth. The findings were validated using OLS regression. Additionally, the study includes a normality test, a model stability test (Inverse Roots AR Characteristic Polynomial), a Granger causality test for short-term relationships, and variance decomposition to analyze variable shocks over time. This research demonstrates that loan growth is primarily driven by its historical values. The VEC model shows that, in the long run, economic growth in Kosovo leads to less credit growth, showing a negative link between it and GDP. Higher interest rates also reduce credit growth, showing another negative link. On the other hand, more foreign direct investment (FDI) increases credit demand, showing a positive link between credit growth and FDI. The results show that loans and inflation (CPI) are positively linked, meaning higher inflation leads to more credit growth. Similarly, more foreign direct investment (FDI) increases credit demand, showing a positive link between FDI and credit growth. In the long term, higher inflation is connected to greater credit growth. In the short term, the VAR model suggests that GDP has a small to moderate effect on loans, while FDI has a slightly negative effect. In the VAR model, interest rates have a mixed effect: one coefficient is positive and the other negative, showing a delayed negative impact on loan growth. CPI has a small and negative effect, indicating little short-term influence on credit growth. The OLS regression supports the VAR results, finding no effect of GDP on loans, a small negative effect from FDI, a strong negative effect from interest rates, and no effect from CPI. This study provides a detailed analysis and adds to the research by showing how macroeconomic factors affect credit growth in Kosovo. The findings offer useful insights for policymakers and researchers about the relationship between these factors and credit activity.
This study investigates the integration of sustainability principles into educational curricula, focusing on the gap between theoretical knowledge and practical application. Through a mixed-methods approach, the research identifies key institutional barriers, including outdated policies, insufficient teacher training, and limited resources. These barriers hinder the effective incorporation of sustainable development principles into education. The study reveals that while some educational systems struggle to adopt sustainability, examples from progressive institutions show that integrating these principles enhances student awareness and equips them with skills essential for sustainable development. The findings suggest that substantial changes are needed in existing educational frameworks to better support sustainability in curricula. Recommendations for future research include conducting longitudinal studies to assess the long-term impact of curriculum changes on sustainability outcomes and exploring the role of technology in advancing sustainable education. Policy recommendations emphasize the need for advocacy and the implementation of actionable strategies, such as industry collaborations for pilot projects and real-world applications. Furthermore, institutional support for teacher professional development is crucial, with structured programs that combine theoretical knowledge and practical skills in sustainability. Enhancing partnerships between educational institutions and industries, including co-designed curriculum modules and internship opportunities, is also essential for aligning education with the Sustainable Development Goals. This study highlights the importance of transforming educational practices to better address the challenges of sustainable infrastructure development, ultimately preparing students to contribute to a more sustainable future.
This longitudinal study is dedicated to the evaluation of the comprehensive impact of educational reforms through a mixed research methodology which is a combination of the quantitative- and qualitative-oriented research methods to check the students’ outcomes. Data was collected in the span of [mention the time frame] from various data sources for instance standardized test scores, school performance statistics, and through open-ended qualitative evaluation from both students and teachers. Data analysis carried on after the reforms had been put in place revealed that there was a considerable rise in mean test scores and success graduation rates. Therefore, formative evaluation demonstrates the need for implementing reforms that will eventually help the students in boosting academic performance. Besides, there is no difference among investor opinions on teachers, administrators, and students who are involved with the implementation of the reforms. Stakeholders manifest this new assistance as an outcome of lasting improvements in curriculum quality, methods of teaching, and student participation. The study approaches two main challenges that are confronted with education reform that is resourcelessness and to society the change of the educational system can be more suitable for the students to excel academically and it can have an impact on the whole community. Even though this study makes important advancements toward the realization of the complex education implementation process and its effect on student academics, there are elements in which it can be criticized. Both quantitative and qualitative performance improvement is important as well as all the important stakeholder participation. This way the transformation process becomes layered. In other words, these results point to the necessity of planning interventions for longer periods that target the challenges and the forces that maintain the low levels of education performance by the counties.
This study aims to discover the relationship between growth sales, capital structure, and corporate governance on financial performance of energy and basic material sector public companies in Indonesia. Financial performance is observed from 2 aspects: market performance (Tobin’s Q) and profitability performance (ROA). The population in this study is firms in the energy and basic material sector on Indonesia Stock Exchange. The total population is 248 firms. 39 firms were selected as samples. The data is obtained from the annual report which starts from the period 2018 to 2022. A total of the population was determined as samples by purposive sampling method. Data analysis using panel data regression. The result shows: 1) Growth Sales have a significant influence on market performance; however, it does not have a significant effect on profitability performance. 2) Capital Structure significantly influences market and profitability performance 3) Corporate governance significantly influences market and profitability performance. Suggestions for companies that must strive to increase sales, maintain good corporate governance and pay attention to the company’s capital structure in a balanced manner.
While the International Civil Aviation Organization (ICAO) Council is sometimes criticized for the potential influence of political agendas on its decisions, while the International Court of Justice (ICJ) is criticized for its limited jurisdiction and dependence on the party’s willingness to accept the ICJ’s jurisdiction, a crucial concern is raised over the efficiency of the current Dispute Resolution Mechanisms (DRM) for aviation industry related disputes. Unravelling the compelling inquiry that hangs in the air: Just how efficient is the current aviation arbitration legal system? Is the efficiency of this system available to ad hoc arbitration1 or arbitral tribunals2? The authors aim to analyze the existing legal guidance to navigate the complex arbitration system. This article sheds light on precedent cases by the ICAO Council and the ICJ studying challenges, such as the lack of efficiency of the ICAO Council and the criticism of the Council’s ineffectiveness for being hampered by the political interests of Member States. As well as the ICJ as it may be a more powerful authority in resolving such disputes, it also faces multiple challenges including the lack of enforcement, jurisdiction issues, and political influence, which in return makes it unlikely for dispute parties to seek the ICAO or the ICJ for resolution of their disputes, instead parties have now mostly adopted arbitration clauses as their primary dispute resolution method under Air Services Agreements (ASAs) and other aviation related agreements. While ad hoc arbitration has shown effectiveness and success, its secrecy and confidentiality might result in inconsistency and the inability to develop a case law system. The authors note the urgent need for an arbitration institution3 under the United Nations (UN) umbrella specialized in air law and aviation technology disputes, with the power to issue an enforceable, legally binding ruling. The article also examines the realm of arbitration in the aerospace industry, analyzing legal resources, current aviation arbitration systems, centres, and platforms, and further analyzing case studies to assess the results of the efficiency of each Dispute Resolution Mechanism.
The reduction of biodiversity and the decline in wildlife populations are urgent environmental issues with devasting consequences for ecosystems and human health. As a result, the protection of wildlife and biodiversity has emerged as one of humanity’s greatest goals, not only for protecting and maintaining human health but also for environmental, economic, and social well-being. In recent years, people have become increasingly aware of the importance and effectiveness of wildlife conservation efforts alongside environmental protection measures, sustainable agricultural practices and non-harmful production procedures and services. This study describes the development and implementation of a labeling scheme for wildlife and biodiversity protection for products or services. The label is designed to encourage the adoption of sustainable and environmentally friendly production methods and services that will contribute to biodiversity conservation and the harmonic coexistence of human-wildlife. Moreover, using a case study approach, the research presents an innovative information system designed to streamline the label-awarding process, ensuring transparency and efficiency. The established system evaluates the sustainability practices and measures implemented by businesses, with a focus on honey production in this case. Additionally, the study explores the broader social implications of the label, particularly its potential to engage consumers and promote awareness of biodiversity conservation.