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.

As the aging trend intensifies, the Chinese government prioritizes technological innovation in smart elderly care services to enhance quality and efficiency, catering to the diverse needs of the elderly. This study examines the acceptance and usage behavior of smart elderly care services among elderly individuals in Xi’an, using a modified Unified Theory of Acceptance and Use of Technology (UTAUT) model that includes digital literacy as a moderating variable. Data were collected via a survey of 299 elderly individuals aged 60 and above in Xi’an. The study aims to identify factors influencing the acceptance and usage behavior of smart elderly care services and to understand how digital literacy moderates the relationship between these factors and usage behavior. Regression analysis assessed the direct effects of Performance Expectancy (PE), Effort Expectancy (EE), Social Influence (SI), and Facilitating Conditions (FC) on usage behavior. These dimensions were then integrated into a comprehensive index Service Acceptance to evaluate their overall impact on usage behavior, with behavioral intention examined as a potential mediating variable. Results indicate that EE and SI significantly impact the adoption of smart elderly care services, whereas PE and FC do not. Behavioral intention mediates the relationship between these variables and usage behavior. Additionally, gender, age, and digital literacy significantly moderate the impact of service acceptance on usage behavior. This study provides valuable theoretical and practical insights for designing and promoting smart elderly care services, emphasizing the importance of usability and social promotion to enhance the quality of life for the elderly.

This study examined the labor regulations regarding the hours of work and rest for representative fishing countries (Norway) by the International Labor Organization (ILO) Convention C188—Work in Fishing, 2007. A dual comparative analysis with Norway is used to explore policy implications for the representation and protection of fishers’ labor standards in Korea. This study examined the possibility of synchronisation between national and international legislation on the hours of work and rest for fishers, with a particular focus on the Norwegian case. The objective is to identify policy enhancements related to the Korean Seafarers Act. This study looked in depth at the fatigue and well-being problems faced by Korean fishers working long times on various vessels. It is based on the results of a qualitative comparative study. To achieve the objectives, We proposed to ‘the name of the fishing vessel’, which are excluded from the protections afforded by the Seafarers Act and to clarify the regulations regarding the labor standards for them. This proposal will provide compensation and protection for Korean fishers’ labor rights. It aims to enhance labor conditions in line with ILO standards, harmonize national and international agreements to protect small-scale fisheries and contribute to the development of environmentally friendly propulsion technologies, such as hydrogen-fueled electric hybrids and LPG (Liquefied Petroleum Gas).

This paper aims to analyze the impact of access to Information and Communication Technologies (ICT) on the private returns to higher education (HE) focusing on gender inequality in 2020. Methodology: To evaluate the above impact a set of Mincerian equations will be estimated. The proposed approach mitigates biases associated with self-selection and individual heterogeneity. Data: The database comes from the National Household Income and Expenditure Survey (Encuesta Nacional de Ingresos y Gastos de los Hogares, ENIGH) from 2020. Results: Empirical evidence suggests that individuals that have HE have a positive and greater impact on their salary income compared to those with a lower educational level, being women that do not have access to ICT those with the lowest wage return. Policy: Access to ICT should be considered as one of the criteria that integrate social deprivation in the measurement of multidimensional poverty. Likewise, it is necessary to design public policies that promote the strengthening and creation of educational and/or training systems in technological matters for women. Limitations: No distinction was made between individuals that graduated from public or private schools, nor was income from sources other than work considered. Originality: This investigation evaluates the impact of access to ICT on the returns to higher education in Mexico, in 2020, addressing gender disparity.

The research utilizes a comprehensive dataset from MENA-listed companies, capturing data from 2013 to 2022 to scrutinize the influence of capital structure (CapSt) level on corporate performance across 11 distinct countries. This study analyzed 6870 firm-year observations using a quantitative research method through static and dynamic panel data analysis. The primary analysis reveals a positive correlation between the CapSt ratio and company performance using fixed effects (FE) techniques. Hence, the preliminary results were re-examined and affirmed using a two-step system generalized method of moment (GMM) estimator to address potential endogeneity concerns. This finding aligns with most studies conducted in advanced countries, indicating a positive correlation between CapSt and corporate performance. Furthermore, it is also consistent with some research conducted in less-developed markets. This research argues that, in the MENA region, the advantages of debt, such as tax saving, may outweigh the potential financial distress cost. Furthermore, it offers insights into the monitoring role of CapSt in MENA-listed companies. We strengthen our research results by employing various methodologies and using alternative measures of accounting performance and controlling size, notably panel quantile regression analysis.

The rapid advancement of information and communication technology has greatly facilitated access to information across various sectors, including healthcare services. This digital transformation demands enhanced knowledge and skills among healthcare providers, particularly in comprehensive midwifery care. However, midwives in rural areas face numerous challenges such as limited resources, cultural factors, knowledge disparities, geographic conditions, and technological adoption. This research aims to evaluate the impact of AI utilization on midwives’ knowledge and behavior to optimize the implementation of healthcare services in accordance with Delima Midwife Service standards in rural settings. The analysis encompasses competencies, characteristics, information systems, learning processes, and health examinations conducted by midwives in adopting AI. The research methodology employs a cross-sectional approach involving 413 rural midwives selected proportionally. Results from Partial Least Squares Structural Equation Modeling indicate that all reflective evaluation variables meet the required criteria. Fornell-Larcker criterion demonstrates that the square root of AVE is greater than other variables. The primary findings reveal that information systems (0.029) and midwives’ competencies (0.033) significantly influence AI utilization. Furthermore, midwives’ competencies (0.002), characteristics (0.031), and AI utilization (0.011) also significantly impact midwives’ knowledge and behavior. Midwives’ characteristics also significantly affect their competencies (0.000), while midwives’ learning influences health examinations (0.000). Midwives’ knowledge and behavior affect the transformation of healthcare services in rural midwifery (0.022). The model fit results in a value of 0.097, empirically supporting the explanation of relationships among variables in the model and meeting the established linearity test.