The relevance of virtual learning platforms has been increasingly recognised, and their merit in contributing to sustainable education is ever growing. Depending on the context, the benefits of these virtual platforms were revealed during the COVID-19 pandemic. Moreover, their impact has lingered on post-COVID-19, and virtual learning is now considered a viable option for continuing and sustainable education. Therefore, many countries have taken advantage of these virtual platforms to maximise student engagement, as evidenced by the reports in the existing literature. However, while these studies have explored how this can best be achieved, there are very few studies which have examined how the use of virtual platforms can help to deliver an educational approach that prepares young people to address the many and complex sustainability challenges of the future, i.e., the delivery of sustainable education. This study addresses this gap in the literature by exploring the question of how AI-powered automation can enhance student learning experiences in the Kingdom of Saudi Arabia (hereafter, KSA) as an alternative pathway for sustainable education. Data were collected from 1991 undergraduate and postgraduate students across 10 different Saudi universities using an online survey. The data were analysed using advanced structural equation modelling (SEM) to examine the relationship between student readiness and the (AI-powered) automation of administrative processes. The findings highlight the transformative potential of AI as an alternative pathway to sustainable education and for streamlining learning management system (LMS) operations. The implications of this study extend beyond the immediate instructional context, offering strategic direction for educators, LMS designers, policymakers, and institutional leaders in harnessing AI to equip individuals with the knowledge, skills, values, and attitudes necessary to contribute to a sustainable future.

This study evaluates the potential of IoT-enabled adaptive traffic management systems for mitigating urban congestion, enhancing mobility, and reducing environmental impacts in densely populated cities. Using London as a case study, the research develops a multiagent simulation framework to assess the effectiveness of advanced traffic management strategies—including adaptive signal control and dynamic rerouting—under varied traffic scenarios. Unlike conventional models that rely on static or reactive approaches, this framework integrates real-time data from IoT-enabled sensors with predictive analytics to enable proactive adjustments to traffic flows. Distinctively, the study couples this integration with a multiagent simulation environment that models the traffic actors—private vehicles, buses, cyclists, and emergency services—as autonomous, behaviourally dynamic agents responding to real-time conditions. This enables a more nuanced, realistic, and scalable evaluation of urban mobility strategies. The simulation results indicate substantial performance gains, including a 30% reduction in average travel times, a 50% decrease in congestion at major intersections, and a 28% decline in CO₂ emissions. These findings underscore the transformative potential of sensor-driven adaptive systems for advancing sustainable urban mobility. The study addresses critical gaps in the existing literature by focusing on scalability, equity, and multimodal inclusivity, particularly through the prioritisation of high-occupancy and essential traffic. Furthermore, it highlights the pivotal role of IoT sensor networks in real-time traffic monitoring, control, and optimisation. By demonstrating a novel and practical application of sensor technologies to traffic systems, the proposed framework makes a significant and timely contribution to the field and offers actionable insights for smart city planning and transportation policy.

Over the past two decades, environmental sustainability has become a key corporate and organisational issue. Today, firms are increasingly turning to existing and emerging digital technologies to help ensure that they meet the medium and long-term needs and expectations of customers and other stakeholders with respect to sustainability performance. This raises the important question of which digitisation factors most significantly impact environmental sustainability performance, as well as the mediating factor of sustainability innovation balance (the ability of a firm to balance the exploration of new innovations with the exploitation of existing innovations). A comprehensive survey instrument was developed and refined through expert feedback and a pilot study, leading to data collection from 374 professionals in the Freight and Logistics industry in Saudi Arabia, all of whom held senior positions in areas such as business development, IT, and Environmental, Social, and Governance (ESG) departments. This data was then analysed using structural equation modelling (SEM). The results of this analysis showed that the key factors impacting sustainability performance were digital competence, strategy alignment, digital adaptability, innovation exploitation and innovation exploration. These findings contribute to the current literature by expanding our understanding of the real-world drivers of sustainability performance. In practical terms, the study will help managers improve sustainability performance by enhancing resource efficiency, streamlining, and supply chain management, as well as improving employee engagement and training, fostering a culture of sustainability within the organisation.

Recent advances in technology have made truly open and accessible government significantly more realisable. One of the ways in which governments are using this technology is in the implementation of online portals that allow open (i.e., public and unrestricted) access to data and use of data. Such portals can be used by citizens and professionals to facilitate improved decision-making across a wide range of areas, from car-parking to promoting entrepreneurialism. However, the existence of portals per se is not enough. To maximise their potential, users must also feel that they are both accessible and usable. To gain insights into the current state of usability of OGD portals for professionals working in data-related areas, a comparative study of the portals of the G7 group was carried out, using a mixed methodology. This is the first specific comparison of these portals for such users, as well as the first study to add a user-centred qualitative dimension to the research. The study’s findings showed that the G7 countries are not maximising the potential of their portals or collaborating effectively. Addressing these issues, and building better cross-national consistency, would help to improve the value delivered by investment in OGD portals. The study also further supported an existing user-centred, heuristic evaluation framework for application to a more specific user group, as well as more generally.

Open government data (OGD) involves exposing government data to the public, guided by the values of clarity, accountability, honesty, and integrity. This study investigates the impact of the perceived quality of data, systems, and services on citizens’ trust in OGD, with the information systems success model as the theoretical framework. A questionnaire was delivered electronically to reach OGD users around the world. A total of 358 complete responses were obtained, representing 63.58% of all responses. Structural equation modeling was used to analyze the hypothesized relationships between constructs based on users’ responses. The findings confirm the impact of data, system, and service quality on citizens’ perceived trust in OGD. Moreover, perceived system and service quality had a positive impact on perceived data quality, and perceived service quality had a positive effect on perceived system quality. These findings indicate that OGD service quality affects data and system quality, making it the most fundamental motivator of citizens’ trust in OGD. This highlights the role of open government platforms in developing public services and providing users with complete and correct data, feedback tools, and data visualization.

In times of disruption, a company’s ability to manage its supply chain effectively can determine its success or failure. This paper explores the extent to which strategic partnership development, mediated by digital transformation, enhances supply chain effectiveness during such periods. A mixed methods approach was used, involving surveys and interviews with professionals from the Saudi Arabian manufacturing sector. The study’s findings reveal that digital transformation and strategic partnerships work synergistically together to enhance supply chain resilience and effectiveness, resulting in improved operational agility and adaptability. Four key enablers of supply chain digital transformation were identified: inter-business coordination, leadership, technological culture, and recruitment management. These insights contribute significantly to our understanding of how businesses can build resilient supply chains in uncertain environments.