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Integrating Analytical Hierarchical Process and Quadrant Matrix Analysis in a Decision Analytics Framework for Flood Management Planning
No full textFlood management planning (FMP) requires decision analytics approaches that can prioritize multiple criteria while accounting for uncertainty in expert judgment and data availability. This study presents a decision analytics framework that integrates the Analytic Hierarchy Process (AHP) and Quadrant Matrix Analysis (QMA) to identify key flood and trade-off criteria, and to develop a structural plan to support FMP decision making. Using the PESTEL framework, a refined set of 40 criteria was assessed through structured elicitation involving 10 experts from diverse disciplines. AHP was applied to find the relative importance of each criterion, while QMA mapped the criteria by both importance and certainty. The AHP results indicate that the Political, Legal, and Economic domains were the main driving criteria for FMP. At the criterion level, P1: Fair distribution of resources was ranked first (0.1917), followed by L1: Land ownership for flood protection (0.0739) and L4: International constitutional standards and guidelines (0.0543). QMA, in contrast, identified 25 “Must‑Have” criteria, primarily within the Environmental, Social, and Technological domains. A comparison of AHP and QMA outputs reveals that criterion certainty significantly affects practical applicability, even for criteria that are highly ranked in importance. By jointly considering importance and certainty, EC7: Economic loss, EC5: Financial budget, and L3: Flood Disaster Institutional emerged as "Very Highly Ranked" and "Must-Have". The framework also incorporates a structured criterion‑reflection stage, informed by the Weather Model, to refine expert evaluations. Overall, the proposed decision analytics framework enhances clarity and consistency in the selection of criteria and offers practical guidance for FMP in Malaysia and other planning contexts
ERGONOMIC RISK ASSESSMENT IN AN OFFICE ENVIRONMENT USING THE CORNELL MUSCULOSKELETAL DISCOMFORT QUESTIONNAIRE (CMDQ) AND RAPID OFFICE STRAIN ASSESSMENT (ROSA)
No full textProlonged sitting and suboptimal workstation design are key contributors to musculoskeletal discomfort among office workers. This study aimed to identify ergonomic risks in a sedentary office setting, focusing on discomfort patterns and workstation design deficiencies. A mixed-methods approach was adopted involving the Cornell Musculoskeletal Discomfort Questionnaire (CMDQ) and the Rapid Office Strain Assessment (ROSA). Fifty office workers completed the CMDQ, from which seven individuals with high-discomfort scores were further assessed using the ROSA method. Results indicated that the most affected body regions were the shoulders (56%), lower back (46%), and neck (44%). The ROSA evaluations revealed a high average risk score of 5.42, with poor chair ergonomics (mean score: 5.29) identified as the primary concern. Other workstation components, such as the monitor and keyboard setup, showed moderate risk levels. The study concludes that ergonomic interventions, particularly in chair design and usage, are urgently required. Recommendations include replacing non-ergonomic chairs, promoting ergonomic awareness, and incorporating physical activity into daily routines to reduce musculoskeletal risks in sedentary workplaces
LABOUR RIGHTS PROTECTION FOR PLATFORM WORKERS: LESSONS FOR MALAYSIA
No full textDigital labour platforms have emerged as a solution to unemployment issues around the world over the past decade. The flexibility and independence offered on digital labour platforms have attracted workers to perform gig work on digital platforms. Issues such as unfair payment systems and unjust terminations of contracts by platform providers have affected the sustainability of digital labour platforms in Malaysia. This study aims to achieve two research objectives. The first is to examine the labour rights issues surrounding platform workers. Canada has taken immediate steps to enact a statute and has amended its existing legislation to ensure its platform workers are protected. Therefore, the second objective of this study is to analyse how Canada provides labour protection for the country’s platform workers. The objectives of this study are achieved through adopting a qualitative method by way of content analysis of journal articles and relevant government statutes. Semi-structured interviews with relevant ministries and government agencies were conducted, and the results were analysed. A comparative analysis method was used to compare the legislative frameworks in Malaysia and Canada. It is suggested that Malaysian policymakers should refer to the Digital Platform Workers’ Rights Act 2022 (DPWRA) and the Employment Standards Act 2000 (ESA) in formulating protection for platform workers. This study underlines the urgent need for integrated policy reforms to ensure fair and sustainable digital labour practices in Malaysia
USAGE OF VOICE ASSISTANT: A BIBLIOMETRIC LITERATURE REVIEW AND RESEARCH AGENDA
No full textVoice assistant (VA) is one of the most popular artificial intelligence (AI) applications among users. This study aims to provide a comprehensive overview of major stakeholders, namely by affiliation, country, journal, author and article. It is hoped that in using the present study’s proposed conceptual structure, a future research agenda will be provided concerning the use of VA as a field of study in its own right. Following the preferred reporting framework for systematic reviews and the PRISMA meta-analyses guideline, 505 articles in the Scopus database were selected, and a bibliometric analysis was conducted using Biblioshiny. Various methods and tools, such as keyword analysis, thematic evolution, and thematic mapping, were employed to analyse the data. This study presents findings on the most influential stakeholders, along with the results of the keyword analysis, thematic evolution, and thematic mapping. Furthermore, by synthesising the bibliometric analysis results, five key research themes, namely technical attribute, trust and privacy, experience, as well as adoption and application context, have been identified. and future research agenda within the field were put forward. This research is an example of an early bibliometric analysis focusing on the topic of VA usage. It is hoped that the findings will contribute to a better understanding of the use of VA and thus, offer valuable insights for practitioners in the VA industry
SUSTAINABLE AGROTOURISM IN MALAYSIA: A SYSTEMATIC REVIEW OF DEVELOPMENT, SOCIOECONOMIC IMPACTS, AND FUTURE CHALLENGES
No full textThis study aims to provide a systematic review of agrotourism in Malaysia, including its development, socio-economic impacts, challenges, and potential to assist in post-COVID-19 recovery, all while aligning with the United Nations’ Sustainable Development Goals. Utilising a systematic review approach based on the PRISMA guidelines, literature from key academic databases was scrutinised, yielding 20 relevant articles from 2011 to 2024. The review highlights that Malaysia’s agrotourism, strengthened by government policies and entrepreneurial efforts, has potential benefits such as rural income diversification and cultural heritage preservation. However, it also faces challenges, including skill gaps and infrastructure limitations. The study emphasises the need for improved skills training, infrastructure upgrades, sustainability promotion, and targeted marketing efforts. This review contributes to the theoretical understanding of agrotourism’s role in sustainable rural development and the integration of agrotourism within Malaysia’s post-pandemic recovery strategy. The study suggests practical measures for incorporating agrotourism into Malaysia’s recovery plans and identifies avenues for future research, including exploring tourist motivations, assessing community and environmental impacts, examining technological innovations, and evaluating its integration with broader rural development strategies. Overall, this review underscores agrotourism’s potential as a key driver of sustainable rural growth, economic resilience, and the preservation of Malaysia’s cultural and natural heritage
BARRIERS AND DRIVERS FOR ADOPTING THE CHEMICAL LEASING CONCEPT TOWARD SUSTAINABLE VEGETABLE FARMING IN SRI LANKA
No full textThe heavy use of synthetic agrochemicals is a common feature of vegetable farming. This excessive use of agrochemicals underlies fundamental problems related to health degradation, higher vegetable production costs, and environmental damage. The Chemical Leasing Concept (CLC) is based on the premise that it can enable users to reduce the costs associated with high chemical use, reduce environmental and health harms, and curb chemical overuse. Thus, the purpose of this study was to identify the barriers and drivers to the adoption of the Chemical Leasing Concept. The study employed a mixed-methods approach, and data were collected from 30 full-time, medium-scale vegetable farmers. The data were analyzed using thematic analysis for qualitative data and the Participatory Ranking Method (PRM) for quantitative data. The findings confirmed that the most significant barriers included: (1) farmers’ unawareness of Chemical Leasing, (2) doubt about the practicality of the Chemical Leasing concept, (3) uncertain weather and climate conditions, (4) Chemical Leasing being viewed as a risk, (5) a lack of norms, standards, and frameworks to implement Chemical Leasing, and (6) soil infertility. In contrast, the most significant drivers identified were: (1) saving farmers’ time through convenience, (2) providing a solution to agrochemical shortages, (3) avoiding the import and use of inferior agrochemicals, (4) reducing costs and increasing profits, (5) producing healthier products, and (6) access to expert knowledge. Further, awareness campaigns, trust-building initiatives, and financial risk management schemes were recommended to overcome the identified barriers
A PHENOMENOLOGICAL INQUIRY OF DIGITAL RESEARCH ADVISING
No full textPurpose – Digital research advising to address the emerging needs of student researchers across different levels has become popular in recent times. This phenomenological study is aimed at exploring digital research advising as it is experienced by senior research advisers.
Methodology – Using a hermeneutic phenomenological design, the participants’ lifeworlds, their lived body, lived time, lived space, lived human relations, and lived things were analyzed using Van Manen’s contemporary model. Data was collected through in-depth interviews. Categories of themes were identified after the process of linguistic transformation.
Findings – The following five themes captured the lifeworlds of the research advisers: acknowledging corporeal connections, redefining academic space, humanizing digital advising, leveraging the digital toolbox, and investing time.
Significance – This study renders value to academic institutions and active researchers who want to appreciate and understand the meaning ascribed to the nuanced experiences of senior research advisers transitioning from traditional to digital advising. It also offers a foundation of initial insights to inform future research in diverse academic settings
A CRITICAL REVIEW OF THE NIGERIAN ENTREPRENEURIAL ECOSYSTEM:UNDERSTANDING AND LEVERAGING THE OPPORTUNITIES
No full textThe Nigerian entrepreneurial ecosystem is a dynamic yet complex framework that influences economic diversification and development. Despite the immense potential of the Nigerian economy, the ecosystem faces systemic challenges that hinder its effectiveness. Institutional voids, inadequate infrastructure, limited access to finance, a widening skills gap, regulatory bottlenecks, and restricted market access collectively impede entrepreneurial growth and economic transformation in the country. This study adopts a systematic review approach to analyse the Nigerian entrepreneurial ecosystem by examining its key components, identifying prevailing challenges, and exploring strategies to leverage its potential. Drawing on an extensive review of scholarly literature, policy documents, and empirical studies, the study addresses the existing gap in understanding the interplay among the ecosystem’s core elements. The study reveals the pivotal role of government policies, financial institutions, digital infrastructure, and market linkages in shaping entrepreneurial outcomes. The findings emphasise the need for targeted interventions, including policy reforms, capacity-building initiatives, public–private partnerships, and improved access to funding, as essential steps towards bridging existing gaps and unlocking the full potential of Nigerian entrepreneurial ecosystem
OWNERSHIP STRUCTURE AND FIRM GROWTH: A SYSTEMATIC LITERATURE REVIEW AND AVENUES FOR FUTURE RESEARCH
No full textOwnership structure is a key element of corporate governance that helps firms to better perform organizational activities and improve firm growth. Studies have been conducted to expand our understanding of the linkage of corporate ownership structure and firm growth; however, systematization of prior findings is needed to provide a more conclusive picture regarding the nature of the impact of ownership structure on firm growth. The present study used a systematic literature review (SLR) method to review the published research work related to the objectives of this study. It conducted a SLR of 20 selected research articles published in national and international journals from 2009 to 2024. The review has identified that studies conducted on the relationship between ownership structure and firm growth had primarily classified ownership structure into different equity ownership. Prior literature mainly focused on particular ownership categories, namely state vs foreign ownership, family vs non-family ownership and ownership concentration when studying ownership structure in relation to firm growth. The study found that firm growth was estimated mainly by the following three measures: asset growth, sales growth, and employment. Understanding the direction of the effect of different ownership structure variables on firm growth is important for academicians, policy makers, and shareholders. This study has made the evidence more accessible to policy and decision makers. The integrated findings of the study have provided a comprehensive knowledge of the direction of the influence of different ownership variables on firm growth. The study also explores specific components of ownership structure that have been identified in prior research as the most important contributors to firm growth
A Hybrid Machine Learning Model for Streaming Frequency-Based Anomaly Detection in Banking Transactions
No full textThe increasing sophistication of fraudulent activities in digital financial systems necessitates real-time anomaly detection models that can adapt to evolving transactional behaviours. While prior research has explored machine learning approaches for fraud detection, most rely on static datasets and overlook temporal dependencies inherent in financial transaction streams. This study addresses this critical gap by proposing a hybrid anomaly detection model that integrates dynamic streaming-frequency analysis via a 7-day sliding window, an unsupervised Long Short-Term Memory (LSTM) -autoencoder for anomaly scoring, and a supervised Artificial Neural Network (ANN) for classification. The sliding window mechanism enables the model to capture short-term temporal fluctuations and behavioural patterns, aligning with the streaming nature of financial data. The LSTM-autoencoder is trained exclusively on normal transaction sequences to learn temporal dependencies and compute reconstruction errors, which serve as deep anomaly features. These features are then fed into the ANN to classify transactions as normal or anomalous. Experimental results on the IBM Anti-Money Laundering (AML) dataset demonstrate the effectiveness of the proposed framework, achieving a classification accuracy of 99.92%, precision of 94.12%, recall of 88.43%, and F1 score of 91.19%. This layered architecture not only enhances early detection of anomalous behaviour but also provides a scalable, adaptive solution for real-time fraud detection in streaming financial environments