JOURNAL INFORMATION AND TECHNOLOGY MANAGEMENT (JISTM)

A SYSTEMATIC LITERATURE REVIEW ON INTERFUSION AUGMENTED REALITY MODEL (IARM) BASED ON IMMERSIVE ENVIRONMENT, ASSISTIVE TECHNOLOGY AND AFFECTIVE DESIGN PRINCIPLES FOR VISUALLY IMPAIRED INTERACTION

2026-06-11T10:44:10+08:00

Augmented Reality (AR) has emerged as a promising technology for enhancing interaction experiences quality and well-being for visually impaired (VI) users. However, existing solutions are often fragmented, focusing on isolated components such as visual enhancement, auditory navigation, or assistive functionalities without a unified integration framework. While existing systematic literature reviews (SLR) have focused on AR’s impact across various domains such as education, healthcare, and entertainment, there has been limited attention to AR’s applications designed for visually impaired individuals, particularly in their failure to incorporate affective design principles. This study aims to systematically review current AR-based and immersive technologies for visually impaired interaction and identify key components that contribute to effective user experience. A systematic literature review (SLR) was conducted following the PRISMA approach using three databases: Scopus, IEEE Xplore, and Web of Science. A total of 90 records were identified, with 62 remaining after duplicate removal. Following title, abstract, and full-text screening, 24 studies were included for analysis. The findings reveal four dominant themes: assistive navigation and spatial awareness, multisensory interaction, affective and adaptive interaction, and AR-based accessibility enhancement. Despite advancements in each area, the results indicate a lack of integration across these components. Based on these findings, this study proposes a conceptual direction towards an Interfusion Augmented Reality Model (IARM), which emphasizes the integration of immersive, assistive, affective, and AR elements to enhance visually impaired interaction experiences. This study contributes to the development of unified and user-centred AR accessibility frameworks by integrating immersive, assistive, affective, and interaction-oriented design components into a single conceptual direction through the proposed Interfusion Augmented Reality Model (IARM). The framework provides a structured reference for researchers, designers, and developers in designing more holistic, adaptive, and multisensory AR interaction experiences for visually impaired users.

INTEGRATING ASTRONOMICAL KNOWLEDGE WITH HADITH THROUGH MODERN TECHNOLOGICAL TOOLS

2026-06-11T10:09:02+08:00

The integration of astronomical knowledge with Hadith represents a significant interdisciplinary approach in contemporary Islamic scholarship. This study examines how modern technological tools can enhance the understanding and interpretation of Hadith related to astronomical phenomena, such as lunar observation (ru’yah), timekeeping, and celestial events. Traditionally, the interpretation of such Hadith relied heavily on classical methodologies rooted in textual analysis and the scholarly legacy of early Muslim jurists and muhaddithun. However, the rapid advancement of digital technologies, including astronomical simulation software, big data analytics, and online Hadith databases, has opened new avenues for more precise and contextually informed analysis. This research adopts a qualitative and analytical approach by examining selected Hadith texts alongside contemporary astronomical data and technological applications. It highlights how tools such as lunar visibility models, digital repositories, and computational astronomy contribute to a more accurate understanding of prophetic traditions, particularly in matters related to the Islamic calendar and religious observances. The study also explores the conceptual integration of Naqli (revealed knowledge) and Aqli (rational/scientific knowledge), emphasizing that technological advancements should complement rather than replace traditional Hadith methodologies. The findings indicate that modern technology plays a crucial role in bridging the gap between classical interpretations and current scientific knowledge, offering more reliable and consistent outcomes in issues such as moon sighting and calendar determination. Nevertheless, the study also identifies several challenges, including methodological limitations, overreliance on technology, and the need to maintain the epistemological integrity of Islamic scholarship.

THE EFFECTS OF INFORMATION TECHNOLOGY ON WORK EFFICIENCY AMONG PUBLIC AUDITORS IN MALAYSIA

2026-06-10T07:30:24+08:00

The study aimed to explore the effects of Information Technology (IT) on work efficiency among public auditors in Malaysia. Key factors such as IT competency of the auditor, IT competency of the organization and auditors’ attitudes towards the rapid changes in IT were examined by applying the Hertzberg’s Two-Factor Theory and collecting a total number of 140 questionnaires from the public sector auditors at the National Audit Department (NAD) in Malaysia. The data was analysed by using statistical techniques including reliability test, normality test, descriptive analysis and Pearson’s correlation analysis. The study provides significant results that indicate the effects of IT competency of the auditor, IT competency of the organization and auditors’ attitudes towards the rapid changes in IT on the auditors’ work efficiency would encourage auditors and organizations in the accounting industry to have a higher level of IT competency and adopt the current technologies. The study also highlights several IT benefits for a body of knowledge and future research in the accounting field.

SWARM INTELLIGENCE IN INTERNET OF THINGS ENVIRONMENTS: A SCOPING REVIEW

2026-06-25T14:49:51+08:00

The rapid growth of the Internet of Things (IoT) has created significant challenges related to energy consumption, routing efficiency, resource allocation, communication reliability, and cybersecurity. Swarm Intelligence (SI) techniques have increasingly been adopted due to their adaptive and distributed optimization capabilities to address these issues. This study aimed to identify the SI techniques applied in IoT environments and to examine their major application domains and optimisation objectives. This scoping review is based on the six-stage framework proposed by Arksey and O'Malley. Scopus and Web of Science (WOS) are two databases used to find relevant studies based on the topic and published between 2020 and 2026. 19 journal articles were selected and analyzed using thematic and comparative approaches after applying the screening and eligibility criteria. The findings found that SI techniques have been widely adopted in a variety of IoT applications, including in cybersecurity, WSNs, fog computing, IIoT, smart cities, and intelligent transportation systems. Frequently applied SI techniques included PSO, ACO, ABC, SSA, CSA, ACS, FMGWO, and several hybrid optimisation frameworks. These approaches were found to improve energy efficiency, routing performance, resource allocation, QoS, communication reliability, intrusion detection, and network lifetime. The review also identified an increasing trend towards hybrid SI approaches that integrate swarm-based optimisation with deep learning, federated learning, and evolutionary optimization techniques. To conclude, this review demonstrates the significant contribution of swarm intelligence to IoT environment. Although there are some challenges that remain unresolved. In the future, research should focus on addressing these limitations to improve the adaptability and effectiveness of optimization strategies in IoT systems.

THE ROLE OF TECHNOLOGY IN NURSING DOCUMENTATION: A CHRONOLOGICAL REVIEW

2026-06-07T09:09:26+08:00

This temporal literature review of The Role of Technology in Nursing Documentation aims to synthesise the trends and evolution of the digital integration in health. Although the use of technology, such as electronic health records, has been embraced, inconsistencies in their use, effectiveness, and fit with nursing processes suggest a need for a temporal perspective. To address this challenge, a thorough and sophisticated search was conducted in the Scopus database using keywords Electronic Health Records, Nursing Documentation, Digital Records, and Technology. A total of 114 primary studies were identified after reviewing the literature. The outcomes were clustered into four time periods to represent the trends in research activity and emphasis: (1) the Nascent and Exploratory Phase (2004-2008) that showed initial adoption and feasibility of the system; (2) the Initial Growth and Conceptual Expansion phase (2009-2013) that showed increasing interest and theoretical framework development; (3) the Consolidation and Fluctuating Maturity phase (2014-2022) that showed a steady state in publication output with variable effectiveness of the system and user adaptation; and (4) the Renewed Acceleration and Digital Transformation Phase (2024-2026) that showed an increase in innovation through digital transformation and integration of new technologies. The descriptive analysis of the temporal distribution of the studies shows an increasing trend in research activity, with the highest percentage in the recent phase. Overall, the review shows a dynamic trend in technology integration in nursing documentation with improvements and setbacks. The research concludes that although digital systems have greatly improved documentation, further development, user-friendly design, and policy support are needed to ensure they are being used to their full potential.

FROM RULES TO GRAPH LEARNING: A REVIEW OF COMPUTATIONAL APPROACHES TO DETECT SUSPICIOUS BANK TRANSACTIONS

2026-06-25T14:23:55+08:00

Automated systems for detecting suspicious transaction were introduced in the early 2000s to manage the growing volume and complexity of financial transactions. Subsequent technological advancements have driven the convergence of Artificial Intelligence (AI) and Big Data Analytics for transaction data analysis. However, these advancements come at considerable implementation cost and despite significant investment, critical limitations persist that require attention to mitigate financial losses. This review maps the evolution of approaches used to detect suspicious bank transactions between 2012 and 2025, and analyses the datasets employed in the reviewed studies. Articles were sourced from Scopus-indexed journals using the search term "money laundering detection", and the collection was restricted to computer science publications focusing on suspicious bank transaction detection. The screening process excluded studies on conceptual profiling, risk assessment, Hawala networks, and fraud. The remaining articles were then analysed to extract identified problems and limitations, proposed solutions, algorithms, and dataset characteristics. Datasets were classified into three categories: forensic criminal investigation datasets, operational bank AML/SAR-level datasets, and synthetic or simulator-based datasets. The findings indicate a clear methodological progression from rule-based and clustering approaches to supervised machine learning, and subsequently to graph-based and deep learning models. However, more than 20% of the reviewed studies relied on synthetic datasets which are unvalidated using actual money laundering activity. Given the absence of detailed forensic insights in such datasets, findings derived from synthetic data must be interpreted with caution. Beyond detection methods and algorithms, dataset realism is equally critical, particularly in the context of public policy and banking practice.

A THREE-LAYER BLOCKCHAIN FRAMEWORK FOR SMART COLD CHAIN TRACEABILITY OF FRESH AGRICULTURAL PRODUCTS

2026-06-11T10:30:45+08:00

Ensuring end-to-end traceability in fresh agricultural product cold chains remains a persistent challenge, as existing systems suffer from centralised data vulnerability, absence of automated enforcement mechanisms, and disconnection between traceability records and analytical decision-support tools. This paper proposes a three-layer blockchain architecture based on Hyperledger Fabric. The system integrates smart contracts and big data analytics to strengthen traceability and supply chain transparency. It is designed to address operational inefficiencies in the distribution of temperature-sensitive perishable goods. The framework structures cold chain management into three layers: Data, Contract, and Application. The Data Layer adopts a hybrid on-chain/off-chain storage mechanism with hash anchoring to ensure integrity and scalability. The Contract Layer deploys three specialised smart contracts for quality certification, transaction settlement, and cross-organisational information sharing. The Application Layer integrates a big data analytics module that performs parameter optimisation and feeds the results back into the contract layer, forming a closed-loop system. Comparative analysis against four representative existing approaches demonstrates that the proposed architecture offers broader smart contract coverage and deeper analytical integration than current solutions. The closed-loop feedback mechanism transforms the traceability system from a static recording tool into an adaptive management platform. It is capable of continuous operational refinement. The contribution of this paper lies in the design and conceptual evaluation of the proposed architecture rather than in an empirically validated implementation, and prototype deployment together with quantitative performance assessment is planned as a subsequent research stage. Limitations concerning the dependency of the framework on Internet of Things (IoT) infrastructure, the scalability of transaction throughput under high-frequency monitoring conditions, and the governance of automated parameter updates are acknowledged as directions for further investigation.

A CONCEPTUAL INTEGRATION OF 5D BIM AND BIG DATA ANALYTICS FOR ENHANCED PROJECT COST MANAGEMENT

2026-06-10T07:38:44+08:00

Project cost management (PCM) is crucial for achieving cost efficiency and financial control in construction projects. However, persistent issues remain such as the reliance on outdated and incomplete historical data, which often leads to inaccurate cost estimation and forecasting. While 5D Building Information Modelling (BIM) offers improvement in cost data integration, it struggles when managing large and complex datasets. Big data analytics (BDA) has therefore been proposed as a complementary approach to enhance BIM capabilities by enabling advanced data processing and predictive analytics. However, the conceptual relationships between 5D BIM, BDA and PCM remain insufficiently explored in existing literature. This gap highlights the need for a better understanding of their integration. Therefore, the present study reviews and synthesizes existing literature on 5D BIM, BDA and PCM to develop a theoretical framework that highlights the key components and potential benefits of their integration. The findings provide a foundation for future empirical research and support decision-makers in evaluating the strategic value of investing in BDA to enhance BIM-enabled project cost management.

THE USE OF ARTIFICIAL INTELLIGENCE AND MACHINE LEARNING IN FINANCIAL SECTOR. A DECISION-MAKING FRAMEWORK

2026-06-07T09:16:39+08:00

This study provides an overall review on current state of Artificial Intelligence (AI) and Machine Learning (ML) adoption in financial sector as well as explores a framework for identification of potential tasks for automation using AI and ML. The study utilizes a qualitative research methodology grounded in Dynamic Capabilities Theory. The research examines existing processes automated in financial institutions. The overall approach comprised review of existing literature, obtaining primary data through semi-structured interviews and performing thematic analysis. Analysis of data identified that AI & ML models are used for predictive analytics, fraud detection, credit risk assessment, investment portfolio, auditing, compliance monitoring, and customer services across the financial sector. Common criteria for selecting tasks were identified during primary data collection are also explored in this study. The study also discusses concerns shared by participants while they are selecting processes for automation. The research work also assisted in development of a framework to support the process for tasks automation for AI/ML.

A SOCIO-TECHNICAL FRAMEWORK FOR INTERNET OF THINGS (IOT) ADOPTION IN URBAN FARMING: MALAYSIA

2026-06-25T14:38:58+08:00

Urban farming represents a essential strategy for improving food security, sustainability and resource management efficiency in rapidly urbanising countries such as Malaysia. Accelerating urbanisation and the implementation of digital transformation initiatives in smart agriculture technologies changes the agricultures landscape. The Internet of Things (IoT) has notably enhanced the efficiency, sustainability and productivity of urban farming systems, particularly in hydroponic and vertical farming. However, IoT implementation in urban farming remains limited due to budgetary constraints, insufficient digital literacy, infrastructural constraints, technical complexity, legislative barriers, and resistance to behavioural change. Existing research has focused on technology implementation and system performance, with limited analysis of the interplay among technological, behavioural, infrastructural, and institutional elements. Although the socio-technical aspects of technology adoption have been widely examined in the broader agricultural context, a comprehensive framework specifically addressing IoT adoption in Malaysian urban farming remains lacking. Therefore, this research proposes an integrated socio-technical framework based on Socio-Technical Systems Theory (STS) with technological and non-technological determinants to describe the adoption of IoT in Malaysian urban farming. A qualitative literature-based method was employed by synthesising findings from selected studies on smart agriculture, hydroponics, vertical farming, IoT technologies, and technology adoption. The findings indicate that IoT technologies enhance the efficiency, sustainability, productivity, and resource management of urban farming systems. Still, these benefits can only be fully realised with support from economic readiness, government support, technical competency, good infrastructure and positive user behaviour. The proposed framework integrates technological, infrastructural, policy, behaviour, and economic into a socio-technical framework for the Malaysian context. In addition, it provides practical guidance for policymakers, educators, practitioners, and urban communities to sustain urban farming and strengthen national food security initiatives.