The objective of this research is to assess the current state of e-banking in Saudi Arabia. The banking industry is rapidly evolving to use e-banking as an efficient and appropriate tool for customer satisfaction. Traditional banks recommend online banking as a particular service to their customers in order to provide them with faster and better service. As a result of the rapid advancement of technology, banks have used e-banking and mobile banking to both accumulate users and conduct banking transactions. Nonetheless, the primary challenge with electronic banking is satisfying customers who use Internet banking. Thus, the current study seeks to determine what factors affect e-payment adoption with e-banking services. mobile banking, e-wallets, and e-banking, as well as the mediating role of customer trust, can drive e-payment adoption. We distributed the survey online and offline to a total of 336 participants. A convenience sampling technique was used; structure equation modeling (SEM), convergence and discriminant validity; and model fitness were achieved through Smart PLS 3. The findings have shown that mobile banking, e-banking, and e-wallets are three significant independent variables that mediate the role of customer trust in influencing e-payment adoption when using Internet banking services. They should emphasize trust-building activities, specifically in relation to the new ways of e-payment such as e-banking, m-payments, NFC, and e-proximity, which will further help reduce consumer perceptions of risk. The system developers should design user-friendly applications and e-payment apps to enhance consumers’ belief in using them for payment purposes over any Internet-enabled device. They should promptly respond to consumers in cases of failed e-payment transactions and be able to promptly demonstrate transparency in settling claims for such failed transactions. Future studies could benefit from implementing probability sampling to facilitate comparisons with non-probability sampling studies. This study selected responses from only Saudi Arabian adopters of mobile payment technology. We need to conduct research on non-adopters and analyze the results using the model we proposed in this study. Due to time and resource constraints, in depth research using a mixed-methods approach could not be conducted. Future studies can utilize a mixed-methods approach for further understanding.
Introduction: In contemporary healthcare education, the integration of technology has emerged as an essential factor in enhancing the efficiency and efficacy of training methodologies. Particularly within the domain of cardiopulmonary resuscitation (CPR) training, the adoption of technology-driven approaches holds considerable potential for enriching the skills and proficiencies of healthcare practitioners. Through the utilization of innovative technologies, such as simulation software and leveraging smartphones as primary tools, CPR training programs can be customized to provide immersive, interactive, and authentic learning experiences. This study aims to validate a comprehensive CPR training module tailored explicitly for healthcare professionals, to integrate it into smartphones as a medium for delivering CPR training. Methods: Two validity tests, namely content validity and face validity were conducted to evaluate the validity of the Smart-CPR training module. A self-constructed measurement scale was utilized to assess four parameters: consistency, representativeness, clarity, and relevancy. Content validity employed the content validity ratio, with scores ranging between 1 and −1, indicating the level of consensus among experts regarding the significance of each item. Face validity was assessed using two indices: the item face validity index and the scale face validity index. Ratings of 3 or 4 were given a score of 1, while ratings of 1 or 2 received a score of 0. Result: The content validity shows that CVI values for ‘consistency’ and ‘representativeness’ were 0.99 for the module and questionnaire, and 0.96 and 0.97, respectively. ‘Clarity’ scored 0.99 for the module and 0.96 for the questionnaire, while ‘relevance’ achieved 0.99 for both. All 44 items exceeded the 0.83 threshold for face validity. The Lawshe’s content validity ratio (CVR) and content validity index (CVI) value were used to evaluate the content validity of both the CRSTP module and questionnaire, with CVR values result ranging from 0.80 to 0.99 across dimensions. These findings demonstrate robust content validity. Additionally, high CVI scores, mostly exceeding 0.95, suggest favorable outcomes and indicate no need for revisions. In face validity method, all 44 items surpassed the minimum threshold of 0.83, signifying a favourable outcome. Thus, all items were deemed acceptable. Conclusion: The Smart-CPR training module and questionnaires were meticulously developed to meet both face and content validity standards. All 44 items demonstrated appropriate levels of validity, ensuring they effectively enhance and maintain CPR competency among healthcare providers and potentially benefit the broader community. The positive results of the Smart-CPR training module confirm the high validity of the CPR competency assessment. Content validity, evaluated by experts, received a perfect score, demonstrating agreement on the relevance of each module component. Similarly, face validity, assessed by healthcare professionals, also received a flawless score, indicating consensus on the module’s clarity and relevance. These findings validate the module’s effectiveness in teaching CPR techniques to a diverse audience and ensuring compliance with established standards. With such strong validity, digitizing the module becomes more straightforward, facilitating easier sharing and use across digital platforms. Ultimately, the module’s high validity facilitates its integration into digital platforms, thereby enhancing CPR education and improving outcomes during real emergencies.
In the dynamic landscape of modern education, it is essential to understand and recognize the psychological habits that underpin students’ learning processes. These habits play a crucial role in shaping students’ learning outcomes, motivation, and overall educational experiences. This paper shifts the focus towards a more nuanced exploration of these psychological habits in learning, particularly among secondary school students. We propose an innovative assessment model that integrates multimodal data analysis with the quality function deployment theory and the subjective-objective assignment method. This model employs the G-1-entropy value method for an objective evaluation of students’ psychological learning habits. The G-1-entropy method stands out for its comprehensive, objective, and practical approach, offering valuable insights into students’ learning behaviors. By applying this method to assess the psychological aspects of learning, this study contributes to educational research and informs educational reforms. It provides a robust framework for understanding students’ learning habits, thereby aiding in the development of targeted educational strategies. The findings of this study offer strategic directions for educational management, teacher training, and curriculum development. This research not only advances theoretical knowledge in the field of educational psychology but also has practical implications for enhancing the quality of education. It serves as a scientific foundation for educators, administrators, and policymakers in shaping effective educational practices.
This study investigates the impact of artificial intelligence (AI) integration on preventing employee burnout through a human-centered, multimodal approach. Given the increasing prevalence of AI in workplace settings, this research seeks to understand how various dimensions of AI integration—such as the intensity of integration, employee training, personalization of AI tools, and the frequency of AI feedback—affect employee burnout. A quantitative approach was employed, involving a survey of 320 participants from high-stress sectors such as healthcare and IT. The findings reveal that the benefits of AI in reducing burnout are substantial yet highly dependent on the implementation strategy. Effective AI integration that includes comprehensive training, high personalization, and regular, constructive feedback correlates with lower levels of burnout. These results suggest that the mere introduction of AI technologies is insufficient for reducing burnout; instead, a holistic strategy that includes thorough employee training, tailored personalization, and continuous feedback is crucial for leveraging AI’s potential to alleviate workplace stress. This study provides valuable insights for organizational leaders and policymakers aiming to develop informed AI deployment strategies that prioritize employee well-being.
The rapidly growing construction industry often deals with complex and dynamic projects that pose significant safety risks. One of the state-owned companies in Indonesia is engaged in large-scale toll road construction projects with a high incidence of workplace accidents. This study aims to improve safety performance in toll road construction by implementing the Scrum framework. The study uses a System Dynamics approach to model interactions between the Scrum framework, project management, and work safety subsystems. Various scenarios were designed by modifying controlled variables and system structures, including introducing a punishment entity. These scenarios were evaluated based on their impact on reducing incidents and the incident rate over the project period. The results indicate that the combined scenario significantly reduces incidents and incident rates in different conditions. The study also finds a strong relationship between Scrum framework implementation and improved safety performance, demonstrating a reduction in incidents and incident rates by over 50% compared to existing conditions. This research underlines the effectiveness of the Scrum framework in enhancing safety in construction projects.
The purpose of this study is to predict the frequency of mortality from urban traffic injuries for the most vulnerable road users before, during and after the confinement caused by COVID-19 in Santiago de Cali, Colombia. Descriptive statistical methods were applied to the frequency of traffic crash frequency to identify vulnerable road users. Spatial georeferencing was carried out to analyze the distribution of road crashes in the three moments, before, during, and after confinement, subsequently, the behavior of the most vulnerable road users at those three moments was predicted within the framework of the probabilistic random walk. The statistical results showed that the most vulnerable road user was the cyclist, followed by motorcyclist, motorcycle passenger, and pedestrian. Spatial georeferencing between the years 2019 and 2020 showed a change in the behavior of the crash density, while in 2021 a trend like the distribution of 2019 was observed. The predictions of the daily crash frequencies of these road users in the three moments were very close to the reported crash frequency. The predictions were strengthened by considering a descriptive analysis of a range of values that may indicate the possibility of underreporting in cases registered in the city’s official agency. These results provide new elements for policy makers to develop and implement preventive measures, allocate emergency resources, analyze the establishment of policies, plans and strategies aimed at the prevention and control of crashes due to traffic injuries in the face of extraordinary situations such as the COVID-19 pandemic or other similar events.
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