This research focuses on patients’ perceptions regarding the accessibility of dental services in Slovenia across four dimensions: financial accessibility, time accessibility, geographical accessibility, and service quality. We observed how specific factors impact accessibility dimensions of dental services in Slovenia, that patients perceive important. A cross-sectional quantitative survey was conducted using proportionate stratified sampling. Data was collected through an online questionnaire, and 599 completed responses were received from patients regarding their experiences and perceptions of accessibility to dental care. A SEM (structural equation model) approach was used to examine the data. The analysis revealed that patients perceive all four dimensions of accessibility: financial, time, geographical, and service quality important and they all constitute the perception of dental accessibility. The findings of this study can assist policymakers in developing a more accessible dental health system by considering the results proposed in our model.

As the second most polluting industry in the world, the fashion industry has a critical impact on the environment. The development of sustainable fashion is conducive to reducing the environmental pollution caused by the fashion industry. China has the largest consumer market in the world, and the Chinese government and major companies have made considerable contributions to the sustainable development of the fashion industry. However, research regarding young women’s attitudes towards this topic remains under-explored. This study interviewed 30 young women of different ages from different places in China. Based on the theory of planned behavior (TPB), a semi-structured interview was used as a data collection method, and thematic analysis was adopted for data analysis. This paper discusses young Chinese female consumers’ attitudes towards sustainable fashion and analyzes the motivating factors and hindrance factors affecting the consumption intentions of young Chinese female consumers towards sustainable fashion. The research found that young Chinese female consumers generally hold a positive and supportive attitude towards sustainable fashion. Consumers’ perceptions of sustainable fashion, their self-perceptions, and their level of green awareness all significantly impact their attitudes and purchase intentions toward sustainable fashion. Consumers feel low social pressure, and Chinese society demonstrates a high level of acceptance and praise for sustainable concepts. However, the lack of purchasing channels and choices for sustainable fashion in China and the high cost of sustainable fashion products discourage consumers from making purchases. This study will be beneficial as a reference when the Chinese government makes sustainable policies to guide consumers toward sustainable fashion consumption. This study helps enterprises select target markets in China and formulate sustainable fashion marketing strategies and targeted advertising. This study contributes to increasing consumer awareness of sustainable fashion, as well as providing reference and reflective value when consumers purchase sustainable fashion products. Finally, this study will help promote the development process of sustainable fashion in Chinese society, make contributions to reducing the waste of social resources, promoting the recycling of resources, and improving social conditions, and put forward specific solutions and feasible suggestions for the development of sustainable fashion in Chinese society.

The progress of a country can be directly related to the education level of its countrymen. Over a time period, the internet has become a game changer for the world of disseminating education. From 2000 onwards, the scale of online courses has increased manyfold. The main reason for this growth in online learning can be attributed to the flexibility in course delivery and scheduling. Through this study, the authors analyzed the challenges in adopting Online degree programs in higher education in management in India. The authors used Focus Group discussions, semi-structured interviews, and in-depth interviews to collect the data from the various stakeholders. Thematic analysis was used to analyze the responses. Considering the challenges and constraints in India, the authors proposed a sustainable model for implementation. Based on the viewpoints of the different stakeholders, the authors find that online degrees can be instrumental in bringing inclusivity in higher education. There are obvious constraints like a lack of IT infrastructure, the inexperience of faculty in online pedagogy, and the need for more expertise in the administration of online programs by existing universities. However, using SWAYAM as a platform can overcome most of these constraints, as it reduces the burden on individual universities. Hence, the authors proposed models where SWAYAM (technology platform) and Universities (academic partners) can come together to provide a sustainable education model.

This study applies machine learning methods such as Decision Tree (CART) and Random Forest to classify drought intensity based on meteorological data. The goal of the study was to evaluate the effectiveness of these methods for drought classification and their use in water resource management and agriculture. The methodology involved using two machine learning models that analyzed temperature and humidity indicators, as well as wind speed indicators. The models were trained and tested on real meteorological data to assess their accuracy and identify key factors affecting predictions. Results showed that the Random Forest model achieved the highest accuracy of 94.4% when analyzing temperature and humidity indicators, while the Decision Tree (CART) achieved an accuracy of 93.2%. When analyzing wind speed indicators, the models’ accuracies were 91.3% and 93.0%, respectively. Feature importance revealed that atmospheric pressure, temperature at 2 m, and wind speed are key factors influencing drought intensity. One of the study’s limitations was the insufficient amount of data for high drought levels (classes 4 and 5), indicating the need for further data collection. The innovation of this study lies in the integration of various meteorological parameters to build drought classification models, achieving high prediction accuracy. Unlike previous studies, our approach demonstrates that using a wide range of meteorological data can significantly improve drought classification accuracy. Significant findings include the necessity to expand the dataset and integrate additional climatic parameters to improve models and enhance their reliability.

This study examined the factors influencing the organizational satisfaction of employees in public institutions. In the case of public institutions that must provide stable public services on behalf of the government, the organizational satisfaction of employees will be more important. In this regard, this study includes the perception of HRM and trust between employees as affecting factors, and the perception of HRM consisted of sub-components such as fairness of evaluation and excellence of education and training. Moreover, this study considered trust between employees as a mediator. In more specific, online surveys were conducted with 705 employees of public institutions in Korea, and the Structural Equation Model (SEM) was performed. The results indicated that the perception of HRM affected organizational satisfaction directly or indirectly. In addition, trust between employees mediated between all sub-components of perception of HRM and organizational satisfaction. Particularly, trust between employees has been verified to increase the influence of the perception HRM. Meanwhile, in the case of Korea, there are more public institutions than other countries, and many other countries are showing high interest in Korea’s public institution operation system. In this respect, dealing with Korean public institutions as examples provides important international implications.