The aim of this study is to investigate the effect of tourist resources, conditions and opportunities of sacral tourism in Kazakhstan using panel data (time series and cross-sectional) regression analysis for a sample of 14 regions of Kazakhstan observed over the period from 2004 to 2022. The article presents an overview of modern methods of assessment of the tourist and recreational potential of sacral tourism, as used by national and foreign scientific works. The main focus is on the method of estimating the size and effectiveness of the tourist potential, which reflects the realization and volume of tourist resources and their potential. The overall results show a significant positive effect in that the strongest impact on the increase in the number of tourist residents is the proposed infrastructure and the readiness of regions to receive tourists qualitatively. This study is expected to be of value to firm managers, investors, researchers, and regulators in decision- making at different levels of government.

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.

This study investigates the impact of tourism and institutional quality on environmental preservation, utilizing principal component analysis to generate three composite indices of environmental sustainability for 134 countries from 2002 to 2020. The results reveal that environmental sustainability indices have generally improved in lower- and middle-income nations but have declined in certain high-income countries. The findings also underscore the critical role of institutional quality—particularly regulatory standards, government effectiveness, anti-corruption efforts, and adherence to legal frameworks—in promoting environmental sustainability. However, the study shows that both domestic and international tourism expenditures can have adverse effects on environmental sustainability. Notably, these negative effects are exacerbated in countries with well-developed institutions, which is an unexpected outcome. This highlights the need for careful, thoughtful policymaking to ensure that the tourism sector supports sustainable development, rather than undermining environmental objectives.

This study analyzes the importance of strengthening the design of Indonesia’s maritime axis policy. This research uses a qualitative approach to systematically explain the dynamics and importance of strengthening world maritime policy, where the Nvivo 12 Plus tool is used to analyze data and answer the research questions posed. This research shows that Indonesia still has complex bureaucratic and institutional problems and aspects of political identity and leadership attitudes that require systematic and comprehensive improvement. Then, the draft for strengthening the maritime axis policy in Indonesia includes three policy recommendations: reformulating the focus of the maritime axis policy, comprehensive and coherent governance, and an integrated administrative framework, as well as improving the political identity and attitudes of leaders in public policy. Substantially, the relative failure of the Global Maritime Axis (GMA) policy, known as Joko Widodo’s concept of regulating the Indonesian government based on geographical location, was caused by the dominance of political factors and domestic bureaucratic problems. Apart from that, the lack of priority narratives in the maritime and development sectors means that the Indonesian government’s priorities are more oriented towards GMA infrastructure aspects and at the expense of other fundamental elements. This study encourages the Indonesian government to accelerate a more substantive GMA. However, this research needs to be expanded because the analysis results were only carried out through secondary data and focused on two important aspects of GMA. Therefore, further research is needed that explains the prospects for GMA policy in Indonesia in more detail.

This research aimed to 1) evaluate the demographic characteristics, economic, social, and environmental conditions, and characteristics of the senior people in Ranong province, 2) discover the most relevant work characteristic factors for the older persons, and 3) propose appropriate work characteristics model for older people to improve quality of life. This mixed-methods research, for the quantitative part, utilizes the techniques of MRA & CFA with a sample size of 378 individuals, and for the qualitative part, utilizes a documentary study, in-depth interviews with 19 key informants, and a focus group of 17 individuals. The quantitative data were analyzed using a statistical package for the social sciences (SPSS), and content and categorization analysis with a triangulation verification were used for qualitative data. The results showed that: 1) Ranong province is blessed with rich resources, having minerals that can generate income for the province, life-long learning is given priority in senior school to enhance knowledge and necessary life skills, 2) from the regression analysis, the six predicted work characteristic factors; physical, emotional, autonomous, resistant, low-technology and safety were found relevant with statistically significant at 0.05, and the CFA consistency indices also withstood with the six dimensions above, 3) the appropriate work characteristics is articulated in the form of PEARLS model where physical, emotional, autonomous, resistant, low-technology and safety dimensions are the key.

Since 2013, the state has introduced a number of policies to strictly control the number and scale of public hospitals and to control the rapid expansion of public hospitals. After the introduction of this series of policies, the number of public hospitals in China did not continue to grow, but the number of beds in public hospitals continued to grow. This paper uses difference-in-difference (DID) method to analyze the number of public hospitals with the corresponding data of the development of private hospitals after the introduction of the policy, and the results proves that the introduction of relevant policies has an impact on the number of public hospitals, but has a limited impact on the expansion of the scale of public hospitals. At the end of the article, positive policy suggestions are given to the development of hospitals in China, such as controlling the expansion of public hospitals, strictly controlling the number of beds in public hospitals, and vigorously developing private hospitals. Promoting the development of private hospitals is an important economic supplement to China's health care.