The increasing demand for electricity and the need to reduce carbon emissions have made optimizing energy usage and promoting sustainability critical in the modern economy. This research paper explores the design and implementation of an Intelligent-Electricity Consumption and Billing Information System (IEBCIS), focusing on its role in addressing electricity sustainability challenges. Using the Design Science Research (DSR) methodology, the system's architecture collects, analyses, and visualizes electricity usage data, providing users with valuable insights into their consumption patterns. The research involved developing and validating the IEBCIS prototype, with results demonstrating enhanced real-time monitoring, load shedding schedules, and billing information. These results were validated through user testing and feedback, contributing to the scientific knowledge of intelligent energy management systems. The contributions of this research include the development of a framework for intelligent energy management and the integration of data-driven insights to optimize electricity consumption, reduce costs, and promote sustainable energy use. This research was conducted over a time scope of two years (24 months) and entails design, development, pilot test implementation and validation phases.

This study addresses the rising concerns of technostress experienced by teachers due to the increased reliance on educational technology in both classroom and online settings. Technostress, defined as the adverse psychological effects arising from the use of information communication technologies, has been documented to impact teacher performance and overall well-being. Despite the importance of educational technology in enhancing teaching and learning experiences, many educators report elevated levels of anxiety, stress, and pressures associated with their use of these tools. This study presents practical strategies to help teachers alleviate or prevent technostress while using educational technology. This study used a quantitative approach with a survey conducted among 113 university and schoolteachers. The data analysis included frequency and percentage distribution of categorical variables, Cronbach's alpha for reliability, chi-square test, and exploratory factor analysis to identify strategies for symptom prevention. The results indicated that while many teachers experienced symptoms of technostress due to several factors, some did not. The study concluded with specific strategies, and many teachers agreed highly. The implications of this study are profound for educational institutions, policymakers, and teacher training programs as they underscore the necessity of providing comprehensive training, support, and resources to help educators manage technostress effectively. By integrating these strategies into professional developmental programs and fostering a supportive teaching environment, schools and universities can promote better mental health for teachers, improving students' educational outcomes.

The global Testing, Inspection, and Certification (TIC) service market is experiencing significant growth, driven by rising demand for high-quality and safety-related TIC services across various industries. This research aims to redesign a position map and strategy for Indonesian TIC State-Owned Enterprises (SOEs) in the Red Ocean competition. This systematic literature review analyzed 17 journals. The results show that the Indonesian TIC SOEs are intensively competing in the Red Ocean competition. In designing the position map in the Red Ocean competition, the SOEs must use technology in their operational activities to implement good corporate governance, collaborative strategies, resource management, and leadership styles aligned with the organizational culture.

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.