The present study demonstrates the fabrication of heterogeneous ternary composite photocatalysts consisting of TiO₂, kaolinite, and cement (TKCe),which is essential to overcome the practical barriers that are inherent to currently available photocatalysts. TKCe is prepared via a cost-effective method, which involves mechanical compression and thermal activation as major fabrication steps. The clay-cement ratio primarily determines TKCe mechanical strength and photocatalytic efficiency, where TKCe with the optimum clay-cement ratio, which is 1:1, results in a uniform matrix with fewer surface defects. The composites that have a clay-cement ratio below or above the optimum ratio account for comparatively low mechanical strength and photocatalytic activity due to inhomogeneous surfaces with more defects, including particle agglomeration and cracks. The TKCe mechanical strength comes mainly from clay-TiO₂ interactions and TiO₂-cement interactions. TiO₂-cement interactions result in CaTiO₃ formation, which significantly increases matrix interactions; however, the maximum composite performance is observed at the optimum titanate level; anything above or below this level deteriorates composite performance. Over 90% degradation rates are characteristic of all TKCe, which follow pseudo-first-order kinetics in methylene blue decontamination. The highest rate constant is observed with TKCe 1-1, which is 1.57 h⁻¹ and is the highest among all the binary composite photocatalysts that were fabricated previously. The TKCe 1-1 accounts for the highest mechanical strength, which is 6.97 MPa, while the lowest is observed with TKCe 3-1, indicating that the clay-cement ratio has a direct relation to composite strength. TKCe is a potential photocatalyst that can be obtained in variable sizes and shapes, complying with real industrial wastewater treatment requirements.

In the fast-paced modern society, enhancing employees’ professional qualities through training has become crucial for enterprise development. However, training satisfaction remains under-studied, particularly in specialized sectors such as the coal industry. Purpose: This study aims to investigate the impact of personal characteristics, organizational characteristics, and training design on training satisfaction, utilizing Baldwin and Ford’s transfer of training model as the theoretical framework. The study identifies how these factors influence training satisfaction and provides actionable insights for improving training effectiveness in China’s coal industry. Design/Methodology/Approach: A cross-sectional design that allowed the study to capture data at one point in time from a large sample of employees was employed to conduct an online survey involving 251 employees from the Huaibei Mining Group in Anhui Province, China. The survey was administered over three months, capturing a diverse sample with nearly equal gender distribution (51% male, 49% female) and a majority aged between 21 and 40. The participants represented various educational backgrounds, with 52.19% holding an undergraduate degree and most occupying entry-level positions (74.9%), providing a broad workforce representation. Findings: The research indicated that personal traits were the chief predictor of training satisfaction, showing a beta coefficient of 0.585 (95% CI: [0.423, 0.747]). Linear regression modeling indicates that training satisfaction is strongly related to organizational attributes (β = 0.276 with a confidence interval of 95% [0.109, 0.443]). In contrast, training design did not appear to be a strong predictor (β = 0.094, 95% CI: [−0.012, 0.200]). Employee training satisfaction was the principal outcome measure, measured with a 5-point Likert scale. The independent variables covered personal characteristics, organizational characteristics, and training design, all measured through validated items taken from former research. The consistency of the questionnaire from the inside was strong, as Cronbach’s alpha values stood between 0.891 and 0.936. We completed statistical testing using SPSS 27.0, complemented by multiple linear regression, to study the interactions between the variables. Practical implications: This research contributes to the literature by emphasizing the necessity for context-specific training approaches within the coal industry. It highlights the importance of considering personal and organizational characteristics when designing training programs to enhance employee satisfaction. The study suggests further exploration of the multifaceted factors influencing training satisfaction, reinforcing the relevance of Baldwin and Ford’s theoretical model in understanding training effectiveness. Ultimately, the findings provide valuable insights for organizations seeking to improve training outcomes and foster a more engaged workforce. Conclusion: The study concluded that personal and organizational characteristics significantly impact employee training satisfaction in the coal industry, with personal characteristics being the strongest predictor. The beta coefficient for personal characteristics was 0.585, indicating a strong positive relationship. Organizational characteristics also had a positive effect, with a beta coefficient of 0.276. However, training design did not show a significant impact on training satisfaction. These findings highlight the need for coal companies to focus on personal and organizational factors when designing training programs to enhance satisfaction and improve training outcomes.

The study sheds light on how service quality aspects affect customer satisfaction in the Saudi banking sector’s particular socio-cultural setting. Thus, the study examines the role of service quality dimensions on customer satisfaction in the banking industry of Saudi Arabia. The study examined how reliability, assurance, empathy, tangibility, and responsiveness affect customer satisfaction in the Saudi Arabian banking market using 250 bank clients. 250 Saudi bank customers completed a standardised questionnaire. These were normal bank customers with proper bank accounts. IBM SPSS correlational and multiple regression analysis investigated variable connections. The study found a significant favourable influence of reliability on customer satisfaction. However, assurance was not significant. Empathy had a significant impact on customer satisfaction. Tangibility shown a significant impact on customer satisfaction. Responsiveness was not significant. The study emphasises on reliability, empathy, and physical service delivery to boost banking customer happiness. The study found 3 of 5 service quality factors to be significant predictors. Service empathy, tangibility, and reliability greatly impacted customer satisfaction. Managers in Saudi banking should prioritize reliability, empathy, and tangibility to boost customer satisfaction. To keep customers happy, managers should monitor these service quality dimensions and adjust strategies based on feedback. Technology can improve service quality by streamlining processes and personalizing experiences.

Regional differentiation in the Russian Federation is considered to be high in terms of gross regional product (GRP) per capita level, growth rate, and other indicators. Inefficient use of region-specific spaces entails redistribution processes in order to maximize positive agglomeration effects throughout the country. These encompass economic restructuring based on production value-added chain extension and expanding inter-regional collaborative linkages. Besides, it is vital to assess the opportunities of individual Russian territories for participation therein. The research goal is to develop a scientifically based methodology to determine promising sectoral composition of the regional economies and that of spatial interactions. Such methodology would consider the feasibility of combining “smart” industrial specializations, regional resource potential, prevailing contradictions in the economic, innovative, and technological development of the country’s internal space. The proposed methodological approach opens the way to exploit the existing regional economic potential to the full, firstly, via establishing sectoral priorities of the region regarding the regulatory factors for the territorial capital to have a major effect on the increased potential GRP level; secondly, through benchmarking performance of the available development reserves within leading regions from homogeneous groups having similar characteristics and factor potentials; thirdly, via developing inter-regional integration prospects in terms of regional potential redistribution to ensure growth in potential gross domestic product. An extensive analytical and applied investigation of the proposed methodological approach was carried out from 2014 to 2020. Diversified estimates were obtained for a wide range of indicators due to evidences from 85 Russian regions and 13 types of economic activity. Such an integrated approach allows revealing actual imbalances and barriers that impede regional development, ensures the efficient use of production factors, and enables to trace ways to implement transformation policies and design effective regulatory mechanisms. The results provide arguments in favor of strengthening inter-regional connectivity and supporting inter-regional cooperation. This insight not only contributes to the academic discourse on complex development of a territory but also holds practical implications for policymakers and regional planners aimed at ensuring comprehensiveness and robustness of the evaluation supporting the decision-making process.

The national park with Chinese characteristics is the highest level of protection of a kind of natural protection, its establishment marks the park will implement the strictest ecological protection means. It is of great value to construct the utilization system of national park resources under the new natural protected area system in the new era to avoid the misunderstanding of “ecological protection only” and explore how to carry out the sustainable utilization of resources in the reform of national park system and mechanism. According to the analytic hierarchy process (AHP) and Delphi method, the evaluation framework, indicators, reference standards and weights of resource utilization under the national park system were determined in combination with the requirements of constructing the protected natural area system and the total value of resource ecosystem services (including harvest value, existence value and future value). Based on the application research of Bawangling zone of Hainan Tropical Rainforest National Park, the optimal resource utilization system in the future was proposed, and two optimization strategies of ecological adjustment of resource utilization system and construction of suitable resource utilization system were put forward.

Based on digital technology, the digital economy has typical characteristics of high efficiency, greenness, intelligence, innovation, strong penetration and so on, which can promote the sporting goods manufacturing industry (SGMI) to realize the goal of green development. This study selects panel data from 30 provinces in China over the period of 2011 to 2022. And the green total factor productivity of the sporting goods manufacturing industry (SGTFP) is used to reflect the green development of SGMI. The level of digital economy development (DIG) and the SGTFP are measured by using the entropy method and the Super-SBM model with undesirable outputs. Based on the method of coupling coordination degree model, the coordinated development degree of DIG and SGTFP is analyzed first. Then, by making use of the fixed effect model, intermediary effect model and spatial Durbin model, the influence of DIG on the green development of SGMI and its mechanism are empirically studied. The results show that DIG, SGTFP and the degree of their coupling and coordination are generally on the rise. The benchmark regression results show that the coefficient of DIG on SGTFP is 0.213; that is, the digital economy can significantly promote the improvement of green development in SGMI. According to the analysis of the spatial Durbin model, the impact of the digital economy on SGTFP has a certain spatial spillover, that is, the development of digital economy in the region will have a certain promoting effect on the green development of SGMI in the surrounding region. The intermediary effect model analyzes the influence mechanism and finds that the digital economy mainly boosts SGTFP through green innovation technology and energy consumption structure.