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.

The introduction of artificial intelligence (AI) marks the beginning of a revolutionary period for the global economic environments, particularly in the developing economies of Africa. This concept paper explores the various ways in which AI can stimulate economic growth and innovation in developing markets, despite the challenges they face. By examining examples like VetAfrica, we investigate how AI-powered applications are transforming conventional business models and improving access to financial resources. This highlights the potential of AI in overcoming obstacles such as inefficient procedures and restricted availability of capital. Although AI shows potential, its implementation in these areas faces obstacles such as insufficient digital infrastructure, limited data availability, and a lack of necessary skills. There is a strong focus on the need for a balanced integration of AI, which involves aligning technological progress with ethical considerations and economic inclusivity. This paper focuses on clarifying the capabilities of AI in addressing economic disparities, improving productivity, and promoting sustainable development. It also aims to address the challenges associated with digital infrastructure, regulatory frameworks, and workforce transformation. The methodology involves a comprehensive review of relevant theories, literature, and policy documents, complemented by comparative analysis across South Africa, Nigeria, and Mauritius to illustrate transformative strategies in AI adoption. We propose strategic recommendations to effectively and ethically utilize the potential of AI, by advocating for substantial investments in digital infrastructure, education, and legal frameworks. This will enable Africa to fully benefit from the transformative impact of AI on its economic landscape. This discourse seeks to offer valuable insights for policymakers, entrepreneurs, and investors, emphasizing innovative AI applications for business growth and financing, thereby promoting economic empowerment in developing economies.

On 17 February 2008, Kosovo declared its independence from Serbia, receiving recognition from over half of the UN member states, the majority of the European Union, Council of Europe and NATO member states, as well as the most industrialized states in the global economic forum. However, Kosovo did not receive recognition from Serbia, China, Russia, India, certain states with diplomatic grievances with the USA, communist dictatorial states like North Korea, and five EU member states, including Romania, Greece, Cyprus, Slovakia, and Spain. This article focuses on Spain’s possibilities and reasons for recognizing Kosovo or not. Using qualitative methodology, five university professors—two from Madrid, one from Barcelona, and two Kosovar professors, one from the University of Pristina and the other from the University of Winchester, England—were interviewed with open-ended questions in November-December 2023. The research identified opportunities and reasons for Spain’s hesitation in recognizing Kosovo, including Spain’s domestic context, historical relations with the Western Balkans and the newly formed countries after the dissolution of Yugoslavia in the early 1990s, as well as the European and international political context. The research results show that Spain has been hesitant to recognize new states quickly, not only in the case of Kosovo, due to the context of autonomist aspirations within Spain and reluctance to draw parallels between Kosovo and Spain’s autonomous regions.

The research aims to explore the role of Electronic Human Resources Management on employee performance through employee engagement. The present research’s population included all Jordanian Service and Public Administration Commission employees. The data was collection through a questionnaire that was administered for the study Population. 262 questionnaires collected from employees working in Service and Public Administration Commission in Jordan valid for statistics. The analysis of the data was undertaken through the use of SEM (structural equation modelling). The results showed that E-HRM has a direct impact on employee performance and employee engagement. Consequently, the indication from the results was that a significant role in mediation within the effect that E-HRM had upon employee performance been played by employee engagement. The conclusion reached was that transformation of the public sector through implementation of technological HRM methods fosters employee engagement, with that being a key driver for the alignment of employee behaviors for the achievement of high levels of employee performance.

Public open spaces, such as squares, parks, and sports fields, serve as crucial hubs during and after disasters, fostering a sense of normalcy and community, promoting social cohesion, and facilitating community recovery. Additionally, they offer opportunities for promoting physical and mental well-being during such crises. This study aims to enhance the responsiveness of public open spaces to disasters by prioritizing disaster resilience in their planning and design. This study consists of two main stages. Firstly, a literature review is conducted to explore the current trends in research on public open space planning and design and the incorporation of disaster resilience. Results indicate that the primary focus of the current research on planning and designing public open spaces centers around sociocultural, psychological, environmental, and economic benefits. There is limited emphasis on integrating disaster resilience into public open space planning and design, leading to a lack of clear guidance for planners and architects. The emphasis on disaster resilience in public open space planning and design mainly began after 2010, with a notable increase observed in the last six years (2017–2023). This emphasis notably centers on climate change impacts, followed by floods, and then earthquakes. Secondly, drawing on the pivotal role of public open spaces during disasters, the importance of urban planning and design, and the existing gap in incorporating disaster resilience in current research on public open space planning and design, this study develops a novel framework for enhancing public open spaces’ responsiveness to disasters through resilient urban planning and design, based on four main disaster resilience criteria: multifunctionality, efficiency, safety, and accessibility. The insights gleaned from this study offer invaluable guidance to planners, architects, and decision-makers, empowering them to develop public open spaces that can effectively respond to various circumstances, ultimately contributing to bolstering community resilience and sustainability.

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 coastal area of Bohai Bay of China has a wide distribution of salt-accumulated soils which could pose a problem to the sustainable development of the local ecology. As a result, the land remains largely degraded and unsuitable for biophysical and agricultural purposes. In this study, we characterized the soil and native plants in the area, to properly understand and identify species with satisfactory adaptation to saline soil and of high economic or ecological value that could be further developed or domesticated, using appropriate cultivation techniques. The goal was to determine the salinity parameters of the soil, identify the inhabiting plant species and contribute to the ecosystem data base for the Bay area. A field survey involving soil and plant sampling and analyses was conducted in Yanshan and Haixing Counties of Hebei Province, China, to estimate the level of salt ions as well as plant species population and type. The mean electrical conductivity (EC) of the soils ranged from 0.47 in more remote locations to 23.8 ds/m in locations closer to the coastline and the total salt ions from 0.05 to 8.8 g/kg, respectively. Each of the salinity parameters, except HCO₃⁻ showed wide variations as judged from the coefficient of variation (CV) values. The EC, as well as chloride, sulphate, Mg and Na ions increased significantly towards the coastline but the HCO₃⁻ ion showed a relatively even distribution across sampling points. Sodium was the most abundant cation and chloride and sulphate the most abundant anions. Therefore, the most dominant salinity-inducing salt that should be properly managed for sustainable ecosystem health was sodium chloride. Based on the EC readings, the most remote location from the coastline was non-saline but otherwise, the salinity ranged from slightly to strongly-very strongly saline towards the coast. There were considerably wide variations in the number and distribution of plant species across sampling locations, but most were dominated entirely Phragmites australis, Setaria viridis and Sueda salsa. Other species identified were Aeluropus littoralis, Chloris virgata, Heteropappus altaicus, Imperata cylindrica, Puccinellia distans, Puccinellia tenuiflora and Scorzonera austriaca. On average, the sampling points furthest from the coast produced the most biomass, and the point with the highest elevation had the most diverse species composition. Among species, Digitaria sanguinalis produced the highest dry mass, followed by Lolium perenne and H. altaicus, but there were considerable variations in biomass yield across sampling locations, with the location nearest the coastline having no vegetation. The observed variations in soil and vegetation should be strongly considered by planners to allow for the sustainable development of the Bahai bay area.