Introduction: Many detrimental effects on employees’ health and wellbeing might result from inadequate illumination in the workplace. Headaches and trouble focusing can result from eye strain brought on by inadequate illumination. The purpose of this study was to simulate and optimize workplace illumination in the ceramic industry. Materials and methods: A common Luxmeter ST-1300 was used to measure the illumination in seven workplaces at a height of 100 cm above the floor. DIALux evo version 7.1 software was used to simulate the illumination of workplaces. To optimize the illumination conditions, a numerical experiment design consisting of 16 scenarios was used for each of the workplaces. Four factors were considered for each scenario: luminaire height, number of luminaires, luminous flux, and light loss factor. The Design-Expert program version 13.0.5.0 was applied for developing the scenarios. Finally, by developing quadratic models for each workplace, the optimization process was implemented. Results: Every workplace had illumination levels that were measured to be between 250 and 300 lux. Instead of using compact fluorescent luminaires, LED technology was recommended to maximize the illumination conditions for the workers. Following optimization, 376 lux of illumination were visible at each workstation in every workspace. For the majority of the workspaces, the simulated illumination was expected to have a desirability degree greater than 0.9. The uniformity and illumination of the workplace were significantly impacted by the two factors of luminaire height and luminaire count. Conclusion: The primary outcomes of this optimization were the environmental, political, and socioeconomic ones, including reduced consumption power, high light flux, and environmental compatibility. Nonetheless, the optimization technique applied in this work can be applied to the design of similar situations, such as residential infrastructure.

This research study aims 1) to create a structural equation model for sports sponsorship of halal products in Thailand and 2) to examine the direct and indirect influence of variables that are components of the structural equation model for halal products, specifically in the context of becoming a sports sponsorship for halal products in Thailand. The study focused on a sample group of Thai Muslims interested in watching and following the news and participating in Thai sporting events. The researcher chose a sample size of 400 participants from this population, excluding backup data gathering and data analysis, to ensure the questionnaire’s quality and dependability. The results of the data analysis from the structural equation model created show that it is consistent with empirical data. The results of the statistical hypothesis test reveal that the level of religious adherence and the level of awareness of entering into sponsorship have both direct and indirect influences on consumer attitudes and purchase intentions with statistical significance at 0.01. It can also be identified that if a sponsor increases awareness among Muslim viewers through branding or product presentations in events that feature halal symbols or indicate compliance with religious standards, it will lead to a more positive attitude and higher purchase intentions. This insight can be applied to marketing promotion in administrative regions or countries where the majority of the population is Muslim.

This investigation extends into the intricate fabric of customer-based corporate reputation within the banking industry, applying advanced analytics to decipher the nuances of customer perceptions. By integrating structural equation modeling, particularly through SmartPLS4, we thoroughly examine the interrelations of perceived quality, competence, likeability, and trust, and how they culminate in customer satisfaction and loyalty. Our comprehensive dataset is drawn from a varied demographic of banking consumers, ensuring a holistic view of the sector’s reputation dynamics. The research reveals the profound influence of these constructs on customer decision-making, with likeability emerging as a critical driver of satisfaction and allegiance to the bank. We also rigorously test our model’s internal consistency and convergent validity, establishing its reliability and robustness. While the direct involvement of Business Intelligence (BI) tools in the research design may not be overtly articulated, the analytical techniques and data-driven approach at the core of our methodology are synonymous with BI’s capabilities. The insights garnered from our analysis have direct implications for data-driven decision-making in banking. They inform strategies that could include enhancing service personalization, refining reputation management, and improving customer retention efforts. We acknowledge the need to more explicitly detail the role of BI within the research process. BI’s latent presence is inherent in the analytical processes employed to interpret complex data and generate actionable insights, which are crucial for crafting targeted marketing strategies. In summary, our research not only contributes to academic discourse on marketing and customer perception but also implicitly demonstrates the value that BI methodologies bring to understanding and influencing consumer behavior in the banking sector. It is this blend of analytics and marketing intelligence that equips banks with the strategic leverage necessary to thrive in today’s competitive financial landscape.

This research focuses on the construction of the competency of “Double-qualified” teachers in higher vocational colleges. Through comprehensive literature analysis, in-depth interviews and questionnaire surveys, a competency model covering three dimensions, namely personality charm, teaching literacy and practical skills, has been successfully established. This model provides a scientific basis for higher vocational colleges in teacher selection, performance evaluation and professional training, and particularly emphasizes the importance of teachers’ cultivation of students’ practical abilities and professional qualities in the context of vocational education. The research reveals that these three competency dimensions are interdependent and jointly influence teachers’ educational and teaching achievements as well as students’ career development.

Hazards are the primary cause of occupational accidents, as well as occupational safety and health issues. Therefore, identifying potential hazards is critical to reducing the consequences of accidents. Risk assessment is a widely employed hazard analysis method that mitigates and monitors potential hazards in our everyday lives and occupational environments. Risk assessment and hazard analysis are observing, collecting data, and generating a written report. During this process, safety engineers manually and periodically control, identify, and assess potential hazards and risks. Utilizing a mobile application as a tool might significantly decrease the time and paperwork involved in this process. This paper explains the sequential processes involved in developing a mobile application designed for hazard analysis for safety engineers. This study comprehensively discusses creating and integrating mobile application features for hazard analysis, adhering to the Unified Modeling Language (UML) approach. The mobile application was developed by implementing a 10-step approach. Safety engineers from the region were interviewed to extract the knowledge and opinions of experts regarding the application’s effectiveness, requirements, and features. These interview results are used during the requirement gathering phase of the mobile application design and development. Data collection was facilitated by utilizing voice notes, photos, and videos, enabling users to engage in a more convenient alternative to manual note-taking with this mobile application. The mobile application will automatically generate a report once the safety engineer completes the risk assessment.

Road accidents involving motorcyclists significantly threaten sustainable mobility and community safety, necessitating a comprehensive examination of contributing factors. This study investigates the behavioral aspects of motorcyclists, including riding anger, sensation-seeking, and mindfulness, which play crucial roles in road accidents. The study employed structural equation modeling to analyze the data, utilizing a cross-sectional design and self-administered questionnaires. The results indicate that riding anger and sensation-seeking tendencies have a direct impact on the likelihood of road accidents, while mindfulness mitigates these effects. Specifically, mindfulness partially mediates the relationships between riding anger and road accident proneness, as well as between sensation-seeking and road accident proneness. These findings underscore the importance of effective anger management, addressing sensation-seeking tendencies, and promoting mindfulness practices among motorcyclists to enhance road safety and sustainable mobility. The insights gained from this research are invaluable for relevant agencies and stakeholders striving to reduce motorcycle-related accidents and foster sustainable communities through targeted interventions and educational programs.