International Journal of Information Technology and Management (6 papers in press)

Regular Issues

• Open Access

  Research on the Safety Monitoring of the Entire Process of Green and Low-Carbon Expressway Construction Based on the Improved Apriori Algorithm ( Free Full-text Access )

  by Yongjian Guo, Chenglin Xing, Xibo Wang, Yali Liang 
  Abstract: To overcome the problems of high false acceptance rates, high false rejection rates, and long response times in current monitoring methods, a new safety monitoring method for the whole process of green and low-carbon expressway construction based on an improved Apriori algorithm is proposed. Data on green and low-carbon expressway construction are collected, and an improved isolated forest algorithm is used for outlier detection and data preprocessing. An improved Apriori algorithm is designed, which first divides regions and then integrates them. This algorithm uses the processed data as a basis to assess construction safety status and achieve safety monitoring throughout the entire construction process. Experimental results show that the false acceptance rate of the proposed method remains stable between 4.12% and 7.95%, the false rejection rate remains stable between 3.84% and 7.28%, and the response time remains stable between 0.25s and 0.37s.
  Keywords: Improved Apriori algorithm; Expressway; Green and low-carbon construction; The Whole process; Safety monitoring; Improved isolated forest algorithm.
  DOI: 10.1504/IJITM.2026.10080128
   
  
• Can Blockchain Help Organizations Streamline Their Operations The Case of Luxury Brands  
  by Sarah Bouraga 
  Abstract: Luxury brands have been facing various pain points over the years, such as counterfeiting or the global issue of sustainability. They also have to create a deep connection with their consumers, making customer relationships essential. Blockchain can help address these issues and opportunities. Using a multiple-case study where we apply an exploratory and inductive approach, we address the following research questions: (i) How can blockchain streamline luxury brand business processes? (ii) How can luxury brands use blockchain to bring value to customers? (iii) How can DApps developers/designers make existing blockchain-based solutions more effective and efficient? This study allows us to draw various conclusions that can have implications in theory and practice In particular, the contribution lies in its identification of strategic and technological concerns around the implementation of a blockchain-based solution, the importance of sustainability, the recognition of characteristics of the blockchain-based application, and the acknowledgment of remaining
  Keywords: Blockchain; Non Fungible Token (NFT); Sustainability; Luxury Brand; Fashion; Counterfeiting 
  
  
• Can Blockchain Help Organisations Streamline Their Operations? The Case of Luxury Brands
  by Sarah Bouraga 
  Abstract: Luxury brands have been facing various pain points over the years, such as counterfeiting or the global issue of sustainability. They also have to create a deep connection with their consumers, making customer relationships essential. Blockchain can help address these issues and opportunities. Using a multiple-case study where we apply an exploratory and inductive approach, we address the following research questions: (i) How can blockchain streamline luxury brand business processes? (ii) How can luxury brands use blockchain to bring value to customers? (iii) How can DApps developers/designers make existing blockchain-based solutions more effective and efficient? This study allows us to draw various conclusions that can have implications in theory and practice In particular, the contribution lies in its identification of strategic and technological concerns around the implementation of a blockchain-based solution, the importance of sustainability, the recognition of characteristics of the blockchain-based application, and the acknowledgment of remaining challenges.
  Keywords: Blockchain; Non Fungible Token (NFT); Sustainability; Luxury Brand; Fashion; Counterfeiting .
  
  
• VRPM-HCM: Enhancing Cloud Power Efficiency Through Hybrid Machine Learning and Model Predictive Control  
  by Sai-Feng Zeng 
  Abstract: The proliferation of cloud computing has intensified energy consumption in data centres, demanding innovative solutions to balance power efficiency and performance. Traditional methods struggle to address dynamic interactions between virtual machines, workloads, and hardware in virtualised environments. This paper proposes VRPM-HCM, a novel framework that synergises model predictive control with machine learning to optimise power consumption while ensuring service-level agreement compliance. The framework introduces a dual-layer control mechanism for real-time CPU frequency adjustments and VM migrations. Experiments demonstrate that VRPM-HCM achieves 23.9% average power savings, reduces SLA violations by 1.2%2.7%, and maintains 91%94% resource utilisation, outperforming state-of-the-art baselines. These results validate its effectiveness in harmonising energy efficiency, performance guarantees, and hardware longevity in dynamic cloud environments.
  Keywords: virtual cluster; quality of service; power control; control theory.
  DOI: 10.1504/IJITM.2025.10076874
   
  
• Security Assessment and Improvement of Artificial Intelligence Technology in Information Retrieval  
  by Baolin Zheng, Shuqin Han, Zaihui Cao 
  Abstract: In view of dynamic security threats and malicious information in information retrieval, existing methods struggle to enhance intelligence and ensure security. This paper proposes an LSTM-DNN model integrating Long Short-Term Memory (LSTM) and Deep Neural Network (DNN). Retrieval data are collected and preprocessed, DNN extracts and fuses features, while LSTM captures temporal changes and identifies threats. The combined model strengthens security assessment and response to dynamic risks. Experiments show that with time-series feature capture and deep feature fusion, the model achieves precision and recall of 0.90 and 0.88 under imbalanced attack samples, demonstrating adaptability, robustness, and offering an effective security solution.
  Keywords: Information Retrieval System; Security Assessment; Dynamic Security Threats; LSTM-DNN Model; Malicious Information Identification.
  DOI: 10.1504/IJITM.2026.10080324
   
  

Special Issue on: OA Information Management and Information Visualisation - Part 3

• Open Access

  The role of business analysis in AI-driven digital transformation ( Free Full-text Access )

  by Korede J. Oluwamola  
  Abstract: Artificial intelligence (AI) is a key driver of digital transformation, enabling organizations to enhance decision-making, automate processes, and generate data-driven insights. However, realising its full potential requires alignment with organisational strategy and processes. This study examines the role of business analysis in facilitating AI-powered digital transformation through a qualitative systematic review based on the PRISMA framework. Twelve peer-reviewed studies across diverse organisational contexts were analysed to identify patterns of AI implementation. Findings indicate that business analysis mediates the translation of AI capabilities into strategic value by supporting process redesign, governance, data readiness, stakeholder engagement, and ethical practices. Rather than serving solely as a technical support function, business analysis emerges as a dynamic organisational capability integrating strategic, operational, and cultural dimensions. The study provides practical insights for organisations seeking responsible AI adoption to maximise long-term business value.
  Keywords: artificial intelligence; AI adoption; digital transformation; business analysis; organisational strategy; process redesign; governance; data readiness.
  DOI: 10.1504/IJITM.2026.10079741