In this paper, we assess the results of experiment with different machine learning algorithms for the data classification on the basis of accuracy, precision, recall and F1-Score metrics. We collected metrics like Accuracy, F1-Score, Precision, and Recall: From the Neural Network model, it produced the highest Accuracy of 0.129526 also highest F1-Score of 0.118785, showing that it has the correct balance of precision and recall ratio that can pick up important patterns from the dataset. Random Forest was not much behind with an accuracy of 0.128119 and highest precision score of 0.118553 knit a great ability for handling relations in large dataset but with slightly lower recall in comparison with Neural Network. This ranked the Decision Tree model at number three with a 0.111792, Accuracy Score while its Recall score showed it can predict true positives better than Support Vector Machine (SVM), although it predicts more of the positives than it actually is a majority of the times. SVM ranked fourth, with accuracy of 0.095465 and F1-Score of 0.067861, the figure showing difficulty in classification of associated classes. Finally, the K-Neighbors model took the 6th place, with the predetermined accuracy of 0.065531 and the unsatisfactory results with the precision and recall indicating the problems of this algorithm in classification. We found out that Neural Networks and Random Forests are the best algorithms for this classification task, while K-Neighbors is far much inferior than the other classifiers.

The performance of Public Enterprises (PEs) in Namibia has been a long and contentious issue, clamored by continuous bailouts in the face of constant poor performance. The trend of financial bailouts to PEs in Namibia over the years has attracted increased attention into the dynamics of poor PE performance and their fiscal burden on the state. The Namibian government has taken active steps in cutting on PE bailouts and demanding improved performance or face closure. By looking at recent developments in the governance of PEs in Namibia, the purpose and objective of the current study is to analyze whether the current stance and trajectory of government decisions spells a post-honeymoon period in which poor performing PEs will ‘wither and survive or die’ if they do not improve their sustainability index by not relying on financial bailouts. This analysis is aided by the insights provided by the stakeholder, institutional and principal-agent theories. Through the qualitative research method, this study finds that the Namibian government has taken a new attitude and approach in which it will no longer blindly accept and tolerate the poor performance of PEs through continuous bailouts as seen in the past. PEs that are withering will now either survive (through reforms) or die (through liquidation or dissolution).

As the aging trend intensifies, the Chinese government prioritizes technological innovation in smart elderly care services to enhance quality and efficiency, catering to the diverse needs of the elderly. This study examines the acceptance and usage behavior of smart elderly care services among elderly individuals in Xi’an, using a modified Unified Theory of Acceptance and Use of Technology (UTAUT) model that includes digital literacy as a moderating variable. Data were collected via a survey of 299 elderly individuals aged 60 and above in Xi’an. The study aims to identify factors influencing the acceptance and usage behavior of smart elderly care services and to understand how digital literacy moderates the relationship between these factors and usage behavior. Regression analysis assessed the direct effects of Performance Expectancy (PE), Effort Expectancy (EE), Social Influence (SI), and Facilitating Conditions (FC) on usage behavior. These dimensions were then integrated into a comprehensive index Service Acceptance to evaluate their overall impact on usage behavior, with behavioral intention examined as a potential mediating variable. Results indicate that EE and SI significantly impact the adoption of smart elderly care services, whereas PE and FC do not. Behavioral intention mediates the relationship between these variables and usage behavior. Additionally, gender, age, and digital literacy significantly moderate the impact of service acceptance on usage behavior. This study provides valuable theoretical and practical insights for designing and promoting smart elderly care services, emphasizing the importance of usability and social promotion to enhance the quality of life for the elderly.

This study presents a comprehensive bibliometric analysis of the literature on public financial management (PFM), aiming to identify key trends, influential publications, and emerging themes. Using data from Web of Science and Scopus, the study examines the evolution of PFM research from 1977 to 2024. The findings reveal a significant increase in PFM research output, particularly after 2010, with countries like the United States, the United Kingdom, and China contributing the most publications. Central themes such as financial management, transparency, and accountability remain prominent while emerging topics like gender budgeting, health insurance, and blockchain technology reflect shifting priorities in the field. The study employed performance analysis and science mapping techniques to assess the structure and dynamics of PFM research. The analysis highlights key focus areas, including fiscal decentralization and sector-specific management, and identifies gaps in the existing literature, particularly regarding interdisciplinary and international collaboration. The results suggest that while PFM remains rooted in traditional governance and financial control, there is a growing emphasis on modern, innovative solutions to address contemporary challenges. This study’s insights provide a roadmap for future research, emphasizing the importance of transparency, technological integration, and inclusive financial policies. In conclusion, this bibliometric analysis contributes to understanding PFM’s evolving landscape, offering scholars and policymakers a clearer perspective on current trends and future directions in the field. Future research should focus on expanding interdisciplinary approaches and exploring the practical impacts of emerging PFM trends across different regions.

Urban facilities and services are essential to human life. Access to them varies according to the geographical location of the population, whether urban, peri-urban or rural, and according to the modes of transport available. In view of the rapid development of peri-urban areas in developing countries, questions are being asked about the ability of the inhabitants of these areas to access these facilities and services. This study examines the ability of the inhabitants of Hêvié, Ouèdo and Togba, three peri-urban districts of Abomey-Calavi in the Republic of Benin, to access commercial, educational, school and health facilities. To this end, we have adopted a GIS-based methodology. It is a combination of isochronal method and accessibility utility measurement. The isochrones were produced according to the main modes of travel recorded on the study area and over a time t ≤ 20 min divided into intervals of 05 min. Analysis of the data enabled us to understand that the main modes of travel adopted by residents are walking, motorcycle and car. Access to educational and health facilities is conditioned by the mode of travel used. Access to commercial and entertainment facilities in t ≤ 20 min is not correlated with the modes of transport used.

In the context of digital transformation, Chinese small and medium sized enterprises (SMEs) face significant challenges and opportunities in adapting to market dynamics and technological advancements. This study investigates the impact of coopetition strategy on the core competencies of SMEs, with a particular focus on marketing, technological, and integrative competencies. Data were collected from a sample of 300 SMEs in Anhui Province through an online survey, and reliability and validity were tested using SPSS and AMOS. The results indicate that dependency and trust significantly enhance the effectiveness of coopetition strategy from an external perspective, while managerial ambidexterity and strategic intent are critical internal factors driving the successful implementation of coopetition strategies. Both external and internal factors positively impact the core competencies of SMEs. Additionally, environmental uncertainty moderates the relationship between coopetition strategy and core competencies, underscoring the need for flexibility and adaptability in dynamic market environments. The findings suggest that SMEs can better integrate internal and external resources, optimize resource allocation, and improve operational efficiency through coopetition strategy, thereby enhancing their core competencies. This study provides valuable insights and practical guidance for policymakers and business practitioners aiming to support the digital transformation of SMEs.