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Internet of Things (IoT) Adoption by Organisation: A Systematic Review : DOI: https://doi.org/10.33093/ijomfa.2025.6.2.11
No full textDespite the transformative potential of the Internet of Things (IoT) and Industry 4.0, adoption of IoT technologies remains slow and limited in organisations. This study addresses this challenge by conducting a systematic review to identify key factors influencing IoT adoption from the organisation level and social science perspective. Using the PRISMA protocol, a total of 16 empirical articles published between 2016 and 2024 were selected from Scopus and Web of Science databases. A deductive thematic analysis guided by the Technology-Organisation-Environment (TOE) framework revealed that relative advantage, organisational readiness, and competitive pressure were the most frequently cited determinants of adoption. Meanwhile, trust, awareness of IoT, leadership characteristics and government support were identified as underexplored variables. The findings provide theoretical contributions by refining adoption models and offer practical insights for policymakers and practitioners seeking to accelerate the implementation of IoT. Future research is recommended to apply qualitative designs and expand search strategies to include expert-verified keywords and alternative databases.
A preliminary investigation of personality traits and characteristics of young agropreneurs
No full textAgricultural entrepreneurship (agroentrepreneurship) plays a crucial role in Malaysia's agricultural industry, with the agricultural sector being a key driver of the nation's economic development and poverty reduction. Through a literature review, this study identifies three key personality traits that may predict the success of young agroentrepreneurs: individual dynamic capabilities, entrepreneurial orientation, and entrepreneurial self-efficacy. These traits are vital to agroentrepreneurs, as they need to adapt to rapid market changes, discover and seize opportunities, deal with challenges, innovate, take calculated risks, and maintain a competitive edge. Thus, this study examined agroentrepreneurs’ scores on these traits and characteristics. This study used a questionnaire to measure individual dynamic capabilities, individual entrepreneurial orientation, and entrepreneurial self-efficacy. Data were gathered from 54 participants during training sessions by the Malaysian Agricultural Research and Development Institute (MARDI) and the Federal Agricultural Marketing Authority (FAMA). The results indicate that agroentrepreneurs scored relatively high on most of these traits and characteristics, suggesting potential success in the sector. Of all traits and characteristics, passion, perseverance, and innovativeness had the highest mean scores. The government can support the development of high-potential agroentrepreneurs by creating programs that develop entrepreneurial qualities, encouraging youth to become agroentrepreneurs, improving education and training programs, and offering financial assistance, such as grants or loans, to young agroentrepreneurs
Flexible leadership strengthens workplace spirituality relationship with adaptive performance
No full textUsing private high schools and vocational schools in nine (9) municipalities in Indonesia's East Java Province as the unit of analysis, this study was designed using a positive behavioral management approach to evaluate the effect of flexible leadership on adaptive performance and the role of flexible leadership as a moderator in the relationship between workplace spirituality and adaptive performance. Using Smart PLS software as an analytical tool, this study employs the partial least squares structural equation modeling (PLS-SEM) statistical approach. Flexible leadership considerably improves adaptive performance and modifies the association between workplace spirituality and adaptive performance according to the results of the hypothesis test. Organizations, including educational institutions, need to train leaders to develop flexible leadership skills, especially in the context of leadership that supports spiritual values because it plays an important role in improving adaptive performance. Flexible leadership is not only compatible with sustainability, but is also important for organizations that aim to thrive in a rapidly changing world. Improving adaptive performance is necessary so that private schools can provide the best educational services
More than just a job: the motivational forces behind public sector employees’ performance
No full textThe public sector relies on human capital as its most valuable resource, which directly affects the performance level of a government. Hence, employee motivation is crucial to ensure the efficient use of public resources to achieve policy objectives. This study examines the factors influencing public servants' motivation and performance using Self-Determination Theory, which encompasses both intrinsic and extrinsic motivational factors. Data were collected from 303 public servants and analyzed using SmartPLS software. The findings indicate that compensation, empowerment, and job satisfaction have a positive impact on motivation, whereas self-development and the work environment do not. Motivation is also linked to employee performance. These insights can help policymakers enhance motivation strategies and improve efficiency, retention, and service quality while maintaining low operating costs. This study also contributes to Self-Determination Theory by offering practical implications for researchers and practitioners seeking to understand and enhance motivation in the public sector. Strengthening these factors can improve public service outcomes and overall sector effectiveness
Representation of Power and Domination in Deviant Religious Practices in the Film Bidaah: A Critical Discourse Study
No full textThis study aims to analyse the representation of deviant religious practices and the construction of power in the film Bidaah using the Critical Discourse Analysis (CDA) approach. The film was selected for its complex portrayal of religious deviation through the character of Walid, a charismatic spiritual leader who manipulates religious symbols to consolidate personal authority. Practices such as "spiritual marriages" without legal or Islamic validity, ritualistic glorification of the leader, foot-washing rites as a form of tabarruk (seeking blessings), forced abortion, and ideologically driven divorce are examined as forms of deviation cloaked in religious legitimacy. This research employs a qualitative method with content analysis of the film’s narrative, visual symbolism, and dialogue. Data were analysed using Fairclough’s three-stage CDA framework: textual analysis, discursive practice, and sociocultural context. The findings reveal that Bidaah exposes the dynamics of power within a closed religious community, where the spiritual leader monopolises religious interpretation and exerts control over individuals' bodies and choices, especially those of women. The film illustrates how language, symbols, and rituals legitimise exploitation under the guise of piety. These practices are not only deviant from Islamic legal principles, particularly in the domains of aqidah (creed) and fiqh (jurisprudence), but also violate the objectives of Islamic law (maqasid al-sharia), including the protection of intellect, religion, and lineage. In conclusion, Bidaah offers a sharp social critique of the misuse of religious authority as a tool of domination. The significance of this study lies in its contribution to fostering critical religious literacy in society and providing guidance for filmmakers and religious leaders to convey Islamic narratives in a responsible and ethically grounded manner through popular media
Editor's Preview: Communicating Islam, Gender and Sustainability in a Mediated World
No full textThis thematic issue explores how Islam, gender, and sustainability intersect through communication across cultural, religious, and social contexts. It invites scholarly work that examines how Islamic values inform gender roles and environmental ethics, and how these are communicated in media, education, policy, and public discourse. The issue aims to highlight faith-based narratives that support sustainability and gender equity, while also critiquing representations that reinforce inequality or environmental neglect. By bringing together diverse disciplines, this issue seeks to advance inclusive, ethical, and context-sensitive understandings of sustainable development rooted in Islamic thought and responsive to gendered experiences in contemporary society
K-Means Clustering Optimization of Toddler Malnutrition Status Using Elbow Method
No full textThe problem of nutritional status is still a major challenge in the health sector in developing countries, including Indonesia. Malnutrition in toddlers can have serious long-term impacts on children's growth and development, including increased risk of disease, impaired cognitive function, and low productivity in the future. To overcome this problem, an in-depth analysis is needed to determine the distribution of nutritional status of toddlers in one of the provincial capitals in Indonesia, which can be used as a basis for planning more effective interventions. This study uses the K-Means algorithm to classify areas based on the prevalence of malnutrition in toddlers across all sub districts in the city. Determination of the optimal number of clusters was carried out using the Elbow method, which showed that the most appropriate clusters were two clusters. To assess the quality of the cluster, the Davies Bouldin Index (DBI) was used which produced a score of 0.361, while the Silhouette Score was 0.799, indicating that the cluster results were of high quality. The clustering results showed significant variations in the prevalence of malnutrition in various sub districts. Cluster 0 represents areas with low prevalence of malnutrition, comprising six sub districts, while Cluster 1 includes ten sub districts with high prevalence of malnutrition. By identifying these high-risk areas more clearly, health authorities and practitioners can develop more targeted and effective nutrition interventions. This research highlights the importance of data driven decision making in public health, supporting augmented intelligence in identifying and addressing nutritional problems in urban areas. The insights provided by this clustering approach contribute to more efficient and strategic health intervention planning
A Conceptual Approach to Predicting Seismic Events and Flood Risks Using Convolutional Neural Networks
No full textThis paper explores the application of convolutional neural networks (CNNs) in predictive modelling for seismic events and flood risks, with a particular focus on forecasting extreme quantile events that exceed historical data limits. Traditional risk assessment methods often struggle to estimate such extremes, highlighting the need for more advanced predictive models capable of handling rare but high-impact events. This research enhances CNN architecture to improve accuracy in high quantile predictions by integrating multi-source spatiotemporal data, addressing a critical research gap. The methodology involves incorporating diverse datasets, including geospatial, meteorological, and historical seismic or flood records, into CNN models to augment predictive capabilities. These models undergo systematic validation using historical events and real-world data to assess their reliability, robustness, and practical relevance. Furthermore, the study evaluates the potential of these advanced prediction models to inform disaster risk management and mitigation strategies. By leveraging deep learning techniques and optimizing CNN structures, this research aims to refine forecasting precision, supporting proactive disaster preparedness. The anticipated outcome is an improved predictive framework that enhances early warning systems, facilitates informed decision-making, and strengthens emergency response mechanisms. Ultimately, this study contributes to the broader goal of increasing resilience against natural disasters by equipping policymakers, emergency responders, and urban planners with more accurate and timely risk assessments
Exploring Big Data Management Approaches and Applications: A Case Study of Real-Time Data Analytics in Air Traffic Management
No full textThe rapid proliferation of digital devices has generated vast amounts of data, presenting significant challenges in collection, processing, and analysis that traditional systems struggle to overcome. This study investigates big data management approaches, explicitly focusing on technologies capable of efficiently handling real-time data at scale. Within the context of Air Operations, we propose a Hadoop-based architecture designed to support the Observe-Orient-Decide-Act (OODA) loop and enhance air traffic management. By leveraging a distributed system deployed on a cloud-based platform, we demonstrate a cost-effective solution for optimised data processing and improved decision-making capabilities. Our analysis highlights the advantages of using Hadoop's distributed file system (HDFS) for managing both structured and unstructured data generated by various sensors and devices. Additionally, we explore the integration of real-time processing technologies, such as Apache Kafka and Spark, to facilitate timely insights essential for operational effectiveness. Cloud deployment not only enhances resource accessibility but also offers flexibility and scalability, which are crucial for adapting to the dynamic nature of defence operations. We also address critical considerations for security and compliance when handling sensitive military data in cloud environments and recommend strategies to mitigate potential risks. The study concludes with recommendations for addressing future technological needs in big data management, including the incorporation of machine learning for predictive analytics and improved data visualisation tools. By implementing our proposed architecture, the military/ civil aviation can enhance its operational efficiency and decision-making processes, positioning itself to meet future challenges in an increasingly data-driven environment