In the era of artificial intelligence, smart clothing, as a product of the interaction between fashion clothing and intelligent technology, has increasingly attracted the attention and affection of enterprises and consumers. However, to date, there is a lack of focus on the demand of silver-haired population’s consumers for smart clothing. To adapt to the rapidly aging modern society, this paper explores the influencing factors of silver-haired population’s demand for smart clothing and proposes a corresponding consumer-consumption-need theoretical model (CCNTM) to further promote the development of the smart clothing industry. Based on literature and theoretical research, using the technology acceptance model (TAM) and functional-expressive-aesthetic consumer needs model (FEAM) as the foundation, and introducing interactivity and risk perception as new external variables, a consumer-consumption-need theoretical model containing nine variables including perceived usefulness, perceived ease of use, functionality, expressiveness, aesthetics, interactivity, risk perception, purchase attitude, and purchase intention was constructed. A questionnaire survey was conducted among the Chinese silver-haired population aged 55–65 using the Questionnaire Star platform, with a total of 560 questionnaires issued. The results show that the functionality, expressiveness, interactivity, and perceived ease of use of smart clothing significantly positively affect perceived usefulness (P < 0.01); perceived usefulness, perceived ease of use, aesthetics, and interactivity significantly positively affect the purchase attitude of the silver-haired population (P < 0.01); perceived usefulness, aesthetics, interactivity, and purchase attitude significantly positively affect the purchase intention of the silver-haired population (P < 0.01); functionality and expressiveness significantly positively affect perceived ease of use (P < 0.01); risk perception significantly negatively affects purchase attitude (P < 0.01). Through the construction and empirical study of the smart clothing consumer-consumption-need theoretical model, this paper hopes to stimulate the purchasing behavior of silver-haired population’s consumers towards smart clothing and enable them to enjoy the benefits brought by scientific and technological advancements, which to live out their golden years in comfort, also, promote the rapid development of the smart clothing industry.

Assessment of water resources carrying capacity (WRCC) is of great significance for understanding the status of regional water resources, promoting the coordinated development of water resources with environmental, social and economic development, and promoting sustainable development. This study focuses on the Longdong Loess Plateau region and utilized panel data spanning from 2010 to 2020, established a three-dimensional evaluation index system encompassing water resources, economic, and ecological dimensions, uses the entropy-weighted TOPSIS model coupled with global spatial autocorrelation analysis (Global Moran’s I) and the hot spot analysis (Getis-Ord Gi* index) method to comprehensively evaluate the spatial distribution of the WRCC in the study region. It can provide scientific basis and theoretical support for decision-making on sustainable development strategies in the Longdong Loess Plateau region and other regions of the world.From 2010 to 2020, the overall WRCC of the Longdong Loess Plateau area show some fluctuations but maintained overall growth. The WRCC in each county and district predominantly fell within level III (normal) and level IV (good). The spatial distribution of the WRCC in each county and district is featured by clustering pattern, with neighboring counties displaying similar values, resulting in a spatial distribution pattern characterized by high carrying capacity in the south and low carrying capacity in the north. Based on these findings, our study puts forth several recommendations for enhancing the WRCC in the Longdong Loess Plateau area.

The service quality of a logistics operation is a key research factor. According to Parasuraman in 1988, there are 5 dimensions about the service quality. In this paper will detective the affecting factors by collecting data from 1560 customers who experienced the service of Beibu Gulf Port Group, Guangxi, China. We used structural equation modeling (SEM) to test whether the service quality factors would affect the logistics operation or not from tangible, responsiveness, reliable and empathy to assurance. Moreover, with the Regional Comprehensive Economic Partnership (RCEP) has been signed, whether this free trade agreement’s effect would affect this Group’s service quality or not would be a consideration of this research. And the traditional service quality factors will affect the RCEP implementation or not will be tested, too. The results in the paper show the significance positive in co-relationship and supporting evidences for the Group’s future development.

The aim of the research is to elucidate the features of the modern model of bioecomedicine and its components as a social determinant of sustainable societal development. The theoretical-methodological basis of the work was the complex use of scientific principles and a systematic approach, which determined the choice of research methods: general scientific and interdisciplinary. The concept generalized content is substantiated and the main lines of building the bioecomedicine model are characterized from the standpoint of information-structural modeling and sustainable development. Based on the structural-logical imperative, the object, subject, basic method and main concepts of this science sphere are characterized. The bioecomedicine principal idea as a social determinant of the sustainable development within a single information space is the unification of the knowledge information field of biology, ecology and medicine based on the use of the latest achievements in information technologies. It is proven that the algorithm for achieving the bioecomedicine global goal in the form of a set of principles reflects the essence of a systemic approach to solving the tasks of sustainable societal development by ensuring the system-environmental homeostasis of humans and the ecosystems that surround them.

Using time series data covering the years 1980 to 2020, this study examines the effects of government spending, population growth, and economic expansion on unemployment in the context of South Africa. The study’s variables include government spending, population growth, and economic growth as independent factors, and unemployment as the dependent variable. To ascertain the study’s outcomes, basic descriptive statistics, the Vector Error Correction Model (VECM), the Johansen Cointegration Procedures, the Augmented Dicky-Fuller Test (ADF), and diagnostic tests were used. Since all the variables are stationary at the first difference, the ADF results show that there isn’t a unit root issue. According to the Johansen cointegration estimation, there is a long-term relationship amongst the variables. Hence the choice of VECM to estimate the outcomes. Our results suggests that a rise in government spending will result in a rise in South Africa’s unemployment rate. The findings also suggest that there is a negative correlation between unemployment and population growth. This implies that as the overall population grows, unemployment will decline. Additionally, the findings suggest that unemployment and economic growth in South Africa are positively correlated. This contradicts a number of economic theories, including Keynesian and Okuns Law, which hold that unemployment and economic growth are inversely correlated.