Ghana Communication Technology University (GCTU), was formerly known as Ghana Technology University College, and previously as Ghana Telecom University College. GCTU is a public-funded university, owned by government and founded in 2005. The change in name of the university to Ghana Communication Technology University(GCTU) was by way of the Public Universities' Bill, passed in 2020.
Vehicular ad-hoc networks (VANET) are crucial for improving road safety and traffic management in Intelligent Transportation Systems (ITS). However, these networks face significant security and privacy challenges due to their dynamic and decentralized nature. Traditional authentication methods, such as Public Key Infrastructure (PKI) and centralized systems, struggle with scalability, single points of failure, and privacy issues. To address these issues, this paper introduces DBVA, a Double-Layered Blockchain Architecture that integrates private and consortium blockchains to create a robust and scalable authentication framework for VANET. The DBVA framework segregates public transactions, such as traffic data, from private transactions, such as identity and location information, into separate blockchain layers, preserving privacy and enhancing security. Additionally, DBVA introduces strict access control smart contracts for the decentralized revocation of unauthorized vehicle privileges, minimizing communication risks and enhancing system resilience. A dynamic pseudonym identity generation mechanism with periodic updates further strengthens privacy by segregating real and pseudonymous identities into separate blockchain layers. Comprehensive performance evaluations reveal that DBVA significantly enhances computational efficiency, reducing the computational cost to 18.34 ms, lowering communication overhead to 992 bits per message, and minimizing storage requirements to just 50 units, making it competitive among contemporary schemes. Extensive security analysis and formal proof confirm that DBVA effectively meets all essential privacy and security requirements, making it a robust, reliable, and scalable solution for enhancing the security, privacy, and resilience of VANET.
PurposeThis study aims to evaluate the idiosyncrasies of consumer behavior in the context of green products. It examined the relationship between trust, green perceived value and price premiums.Design/methodology/approachA survey was conducted to collect data from 578 respondents using convenience sampling. The results were analyzed using the partial least squares approach to structural equation modeling.FindingsThe study revealed that green perceived value mediated the effects of customers' green product experiences on their willingness to pay price premiums. In addition, trust in green labeling did not directly influence consumers' willingness to pay more. However, it indirectly affected willingness to pay more through green perceived value.Research limitations/implicationsThis study focuses primarily on a single context, thus restricting the generalizability of the findings to other consumer groups or cultural situations. The cross-sectional nature of the data gathering further limits its capacity to establish conclusive causal correlations.Practical implicationsThis study provides empirical support for the links between trust, green perceived value and price premiums in the context of green products. These findings can guide marketers in creating more effective marketing efforts by emphasizing green labeling to increase consumer trust in their products' environmental features.Originality/valueTo the best of the authors' knowledge, this study is unique because it focuses on trust in green labeling as a catalyst that influences willingness to pay premium pricing. By applying signaling theory to a sustainable consumption context, it extends the applicability and deepens its relevance.
The growing prevalence of encrypted malicious network traffic poses significant challenges for cybersecurity, as it conceals the content from traditional detection methods. Temporal convolutional networks (TCNs) present promising capabilities for extracting complex temporal features and patterns from the dynamic traffic flow data. However, the unidirectional nature of traditional TCNs limits their effectiveness in capturing the full context of network traffic, which often exhibits bidirectional temporal dependencies. Consequently, a few studies have proposed bidirectional TCN (BiTCN) architectures to address the limitations. However, these methods present complex architectures that require a significant amount of parameters to be learned, which imposes high memory requirements on the computational resources for training such models. In this study, we introduce the efficient bidirectional TCN (eBiTCN) model, an efficient BiTCN that requires fewer parameters yet not at the expense of computational cost and effective detection. The eBiTCN framework combines a bidirectional processor, a lightweight gating mechanism, temporal attention, dropout, a novel loss function, and dense layers. Extensive experiments show that eBiTCN outperforms eight state-of-the-art competing models in terms of detection efficacy, speed, and scalability. The eBiTCN model showcased robust performance in detecting evolving attacks and excelled across various real-world datasets. Its efficiency in training speed and reduced memory usage translates to lower infrastructure costs, making it an accessible and effective choice for deployment. These findings highlight eBiTCN’s practicality and dependability in addressing contemporary network security needs.
This study explores the application of blockchain (BC) technology in enhancing terminal operations at West African seaports, with a specific focus on Tema Port in Ghana. The purpose is to address inefficiencies in cargo processing, traceability, and data integrity that often impede port performance. Using a multi-layered qualitative approach, including observation and value stream mapping, the study examines current operational challenges at Tema Port and proposes a BC adoption model tailored to ship operations, quay transfers, yard management, container freight stations, and receipt/delivery processes. The findings suggest that BC technology significantly improves transparency, operational efficiency, and data security across port processes, offering a unified ledger system accessible to all stakeholders. Based on these findings, the study recommends a phased BC implementation, beginning with targeted pilot programs to mitigate technological and infrastructural constraints common in developing regions. Implications for port managers, policymakers, and academics underscore BC’s potential to reduce operational costs, enhance real-time visibility, and improve compliance in port logistics. This study is limited by its focus on terminal operations at a single port; future research could explore BC’s impact on other areas of the maritime supply chain across multiple ports. The originality of this study lies in its contextualized BC model for West African ports, addressing specific challenges faced by developing regions and offering a foundational framework for future BC applications in logistics.
PurposeThis paper examines the effect of AI leadership on talent management among public service employees in Ghana. Drawing on transformational leadership theory (TLT) and the technology acceptance model (TAM), it explores the mediating role of innovative culture and the moderating effects of AI acceptance and digital maturity in this relationship.Design/methodology/approachA time-lagged research design was employed, collecting data in two phases through a quantitative survey. Convenience sampling was employed to select 378 public service employees. The hypothesized moderated-mediation effects were analyzed using PROCESS macro models.FindingsResults indicate that AI leadership positively impacts talent management through an innovative culture. AI acceptance and digital maturity were identified as significant moderators in these relationships.Research limitations/implicationsThe study suggests the transformative potential of AI leadership in talent management within public service organizations. It highlights the importance of fostering innovative organizational cultures and enhancing employee acceptance of AI technologies.Originality/valueThis study is among the first to uniquely integrate contemporary issues, such as AI leadership and digital transformation, with organizational dynamics, making it promising research. It provides valuable insights into how public service organizations can leverage AI-driven leadership to promote innovation and optimize talent outcomes.
