Labaran Isiaku

Purpose: To identify and explain the critical risks that impede Internet of Things (IoT) adoption in smart cities, reveal their causal interdependencies and propose a prioritized roadmap to support data-driven urban decision-making. Design/methodology/approach: A hybrid fuzzy multi-criteria decision-making framework integrates Fuzzy DEMATEL and Fuzzy TOPSIS using expert inputs from academia, government and industry. DEMATEL maps cause–effect relationships among risks; TOPSIS ranks them by severity, likelihood, controllability and sustainability. Findings: Infrastructure limitations, cybersecurity vulnerabilities and regulatory gaps emerge as dominant causal risks. Dependent risks, including public trust and technological complexity appear downstream. The combined analysis directs attention to strengthening infrastructure, instituting robust cybersecurity frameworks and enhancing governance mechanisms. Research limitations/implications: Results reflect expert judgments within the study's context; generalizability may be constrained. Future research could validate the model with multi-city datasets, longitudinal evidence and comparative analyses of alternative MCDM techniques. Practical implications: The study delivers a ranked, actionable risk-mitigation agenda to guide resource allocation and policy design for urban administrators and policymakers. Social implications: Mitigating foundational risks can bolster citizen trust, resilience, and inclusive digital transformation in smart cities. Originality/value: By combining causal mapping (DEMATEL) with prioritization (TOPSIS), the study advances IoT risk management in smart-city contexts and offers a replicable tool for strategic governance.

Purpose: This study examines the systemic challenges associated with adopting edge–cloud continuum architectures for real-time decision systems and identifies the underlying causal drivers and dependent outcomes shaping sustainable deployment. Design/methodology/approach: A Fuzzy Decision-Making Trial and Evaluation Laboratory (Fuzzy DEMATEL) method was employed to model causal relationships among eight key challenges: latency minimization, scalability and data growth, interoperability, cybersecurity and privacy, energy efficiency and cost, reliability and fault tolerance, network bandwidth, and regulatory governance. Pairwise influence assessments were collected from fifteen domain experts and aggregated using triangular fuzzy numbers. Sensitivity analysis was conducted to assess the structural robustness of the causal classifications. Findings: The results indicate that latency minimization, scalability, energy efficiency, and reliability function as causal drivers, while governance, interoperability, cybersecurity, and bandwidth constraints emerge as effect-side outcomes. This demonstrates that performance-oriented technical enablers shape downstream institutional and coordination challenges within the edge–cloud continuum. Practical implications: The findings offer a decision-support roadmap for managers and policymakers to prioritize upstream technical drivers, enabling more effective mitigation of downstream governance and security risks. Originality/value: The study advances soft computing applications by providing a causal, system-level perspective on edge–cloud adoption, moving beyond isolated challenge rankings to reveal indirect influence structures in real-time digital infrastructures.

Purpose: This study investigates the strategic enablers of sustainable AI-driven transformation in Nigeria’s public sector. It aims to identify the key drivers and dependencies that can support not only digital modernization but also long-term institutional resilience, inclusive governance and improved service equity. Design/methodology/approach: A fuzzy Decision-Making Trial and Evaluation Laboratory (DEMATEL) framework was applied to evaluate 12 high-impact enablers of AI adoption. Data were gathered through expert surveys with digital transformation professionals in government agencies. This method facilitated the construction of a causal model highlighting the influence and dependence relationships among the enablers. Findings: The analysis identifies policy frameworks, digital infrastructure and leadership commitment as dominant causal drivers of AI adoption, while organizational culture, capacity building and data availability emerge as dependent outcomes. Strengthening these foundational enablers is essential for achieving a sustainable and scalable integration of AI into public services. The model provides a decision-support tool for prioritizing resource allocation in a way that ensures long-term impact, continuity and adaptability. Nonetheless, by concentrating solely on enabling factors, the study does not account for potential barriers or risks that may hinder AI implementation, an aspect that future investigations should explore to offer a more balanced and actionable perspective. Originality/value: This study contributes a novel, prescriptive framework that links AI strategy with sustainable public sector innovation in a developing country context. It advances the application of fuzzy DEMATEL in government transformation research and offers actionable guidance for building future-ready institutions capable of delivering equitable and enduring service improvements.

Purpose: This study explores barriers to IoT adoption in the circular economy (CE). While IoT enhances resource efficiency and automation, its implementation faces challenges. Existing research overlooks specific IoT-related barriers and their interconnections within CE. This study identifies key obstacles and examines their relationships using Fuzzy DEMATEL, helping managers make informed decisions under uncertainty to support effective CE adoption. Design/methodology/approach: Using Fuzzy DEMATEL, expert opinions on ten barriers were collected through pairwise comparisons to assess their interrelationships. The method quantifies both direct and indirect influences, distinguishing causal and effect barriers. This analytical approach aids managers in understanding complex barrier interactions to improve strategic decision-making in IoT-enabled CE implementations. Findings: Key barriers include high costs, privacy concerns, data-access issues, and resistance to change. These affect scalability, interoperability, and connectivity challenges. Addressing these will ease IoT integration. The study offers actionable insights and a structured framework to guide managers and policymakers in prioritizing barriers and designing targeted strategies for smoother IoT-driven circular economy transitions. Originality/value: This study uniquely focuses on IoT adoption barriers in CE, identifying causal relationships with Fuzzy DEMATEL to prioritize interventions. Unlike general Industry 4.0 studies, it highlights IoT-specific challenges and their interdependencies, supporting managers and researchers in navigating complexity and uncertainty. The findings provide a valuable foundation for accelerating sustainable, IoT-driven circular economy adoption.

Purpose: This study investigates the determinants influencing continuous use intention to use Business Intelligence (BI) systems within commercial banks in Nigeria. It aims to enhance the understanding of how technological, organisational, and environmental aspects impact the sustained adoption of BI systems, providing insights for improving their long-term effectiveness in the banking sector. Design/methodology/approach: The study employs a partial least squares structural equation modelling (PLS-SEM) approach to analyse data collected from 346 respondents, including IT managers, business intelligence managers, and other relevant personnel from six major banks. The research framework integrates the Technology, Organisation, and Environment (TOE) framework and the Information Systems (IS) success model. Findings: Compatibility, top management support, competitive pressure (CMP), information quality, and system quality positively influence BI system use, while complexity negatively affects it. Regulatory support does not significantly moderate the relationship between top management support and CMP, emphasising internal and competitive factors in sustained BI adoption. Originality/value: By integrating the TOE framework and IS success model, this study highlights key factors influencing BI system use in Nigerian banks. It underscores the need for user-friendly, high-quality systems, strong internal management, and proactive competitive strategies to ensure sustained adoption and long-term success.

This research is aimed at critically examining the concept of gamification and its impact on human activities in the contemporary world, particularly in workplaces or organizations. During the course of the research, other vital concepts like an employee and emotional engagement will also be addressed at length. In order to achieve this aim, the research adopted the positivist philosophical approach as well as a combination of both qualitative and quantitative research. It was discovered that gamification, when applied to human activities, tends to yield a high level of emotional engagement. Similarly, the use of gamification in workplaces enhances employee engagement, competition, motivation and a high level of productivity.

Gamification has emerged as a promising strategy to enhance engagement and learning outcomes in education. However, its adoption in developing countries faces persistent challenges. This study systematically reviews 43 research articles to identify key barriers to gamification adoption and provides new insights into their underlying causes. The findings highlight specific cultural misconceptions, such as the perception of gamification as mere entertainment rather than an educational tool, alongside language barriers and resistance to non-traditional teaching methods. Technological barriers, including limited access to digital devices, high costs, and low digital literacy, further hinder adoption. Institutional challenges, such as rigid curricula, insufficient teacher training, and a lack of supportive policies, exacerbate these issues. Unlike previous studies, this research not only categorizes these barriers but also provides a framework for addressing them. Specific policy recommendations include integrating gamification into national education strategies, subsidizing digital infrastructure, and designing teacher training programs focused on gamified pedagogy. By advocating for localized and context-sensitive gamification strategies, this study offers practical insights for educators, policymakers, and technology developers.