The rapid expansion of smart cities has led to the widespread deployment of Internet of Things (IoT) devices for real-time data collection and urban optimization. However, these interconnected systems face critical cybersecurity risks, including data tampering, unauthorized access, and privacy breaches. This paper proposes a blockchain-based framework designed to enhance the security, integrity, and resilience of IoT data in smart city environments. Leveraging a private blockchain, the system ensures decentralized, tamper-proof data storage, and transaction verification through digital signatures and a lightweight Proof of Work consensus mechanism. Smart contracts are employed to automate access control and respond to anomalies in real time. A Python-based simulation demonstrates the framework’s effectiveness in securing IoT communications. The system supports rapid transaction validation with minimal latency and enables timely detection of anomalous patterns through integrated machine learning. Evaluations show that the framework maintains consistent performance across diverse smart city components such as transportation, healthcare, and building security. These results highlight the potential of the proposed solution to enable secure, scalable, and real-time IoT ecosystems for modern urban infrastructures.

The transportation sector is currently experiencing a significant transformation due to the influence of digital technologies, which are revolutionizing travel, goods transportation, and interactions with transportation systems. This study delves into the possibilities and obstacles presented by digital transformation in the realm of sustainable transportation. Moreover, it identifies the most effective methods for implementing digital transformation in this sector. Furthermore, our analysis sheds light on the potential impacts of digital transformation on sustainable development and environmental performance indicators within transportation systems. We discover that digital transformation can contribute to reduced greenhouse gas emissions, improved air quality, and increased resource efficiency, among other benefits. Nevertheless, we emphasize the potential risks and uncertainties associated with digital transformation, including concerns regarding data privacy, security, and ethics. Collectively, our research provides valuable insights into the opportunities and challenges presented by digital transformation in sustainable transportation. It also identifies best practices for successfully implementing digital transformation in this sector. The implications of our findings are significant for policymakers, businesses, and other stakeholders who aspire to drive the future of sustainable transportation through digital transformation.

Organisational competitiveness hinges on the strategic integration of digital transformation (DT), emerging skills (ES), and organizational health (OH) to foster sustainable performance. Despite the pivotal role of these variables, limited research investigates their interplay in Micro, Small, and Medium Enterprises (MSMEs) in Indonesia. This study addresses this gap by empirically examining how MSMEs navigate challenges and opportunities amid the digital transformation landscape. Specifically, the research probes the intermediary function of the synergistic integration between DT and ES, influencing organisational performance (OP) moderated by OH. Utilizing a validated questionnaire, a three-month convenience sample involved 120 MSME managers. Partial least squares structural equation modelling analysis was employed to assess hypotheses. Findings indicate a significant relationship between DT, ES, and OH, with DT influencing OP. Interestingly, ES alone does not impact OP. Structural equation modelling reveals OH as a mediating variable between DT, ES, and OP. While the proposed model is preliminary, offering avenues for further research, this study underscores the importance of emerging skills in the MSME sector, contributing to a nuanced understanding of organisational competitiveness dynamics.

This study examines the impact of emotional intelligence (EI) and employee motivation on employee performance within the telecommunication industry in the Sultanate of Oman. The target population consisted of 4344 non-managerial employees across nine telecommunication companies, including Omantel, Ooredoo, Vodafone, Oman Broadband Company, Awasr Oman & Co, TEO, Oman Tower Company L.L.C, Helios Tower, and Connect Arabia International. Employing a deductive research approach, finally data were collected via an online survey from 354 respondents. The hypotheses were tested using multiple regression analysis. The results indicate that all dimensions of EI self-awareness, self-regulation, empathy, and social skills positively and significantly influence employee performance, with social skills having the strongest effect. Furthermore, both intrinsic motivation factors, such as work itself and career development, and extrinsic motivation factors, including wages, rewards, working environment, and co-worker relationships, significantly enhance employee performance. The interaction between EI and employee motivation was found to amplify these positive effects. Among control variables, age and education level showed significant impacts, while gender did not. These findings underscore the critical role of both emotional intelligence and motivation in driving employee performance. The study suggests that managers and policymakers should adopt integrated strategies that develop EI competencies and enhance motivational factors to optimize employee performance, thereby contributing to the success of organizations in the telecommunication sector.

This research investigates the relationship between Generative Artificial Intelligence (GAI), media content, and copyright laws. As GAI technologies continue to evolve and permeate various aspects of the media landscape, questions regarding the creation and protection of intellectual property have become paramount. The study aims to highlight the impact of GAI generated content, and the challenge it poses to the traditional copyright framework. Furthermore, the research addresses the evolving role of copyright laws in adapting to the dynamic landscape shaped by artificial intelligence. It investigates whether existing legal frameworks are equipped to handle the complexities introduced by GAI, or if there is a need for legislative and policy reforms. Ultimately, this research contributes to the ongoing discourse on the intersection of GAI, media, and copyrights, providing insights that can guide policymakers, legal practitioners, and industry stakeholders in navigating the evolving landscape of intellectual property in the age of artificial intelligence.

The development of the maize agribusiness system is highly dependent on the role of social capital in facilitating interaction among actors in the chain of activities ranging from the provision of farm supplies to marketing. Therefore, this research aimed to characterize the key elements of social capital specifically bonding, bridging, and linking, as well as to demonstrate their respective roles. Data were collected from farmers and non-farmers actors engaged in various activities in the maize agribusiness system. The data obtained were processed using ATLAS Ti, applying open, axial, and selective coding techniques. The results showed the roles played by bonding, bridging, and linking social capital in the interaction between farmers and multiple actors in activities such as providing farm supplies, farming production, harvesting, post-harvest, and marketing. The combination of these social capital forms acted as the glue and wires that facilitated access to resources, collective decision-making, and reduced transaction costs. These results have theoretical implications, suggesting that bonding, bridging, and linking should be combined with the appropriate role composition for each activity in the agribusiness system.