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.

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.