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THE RELATIONSHIP BETWEEN OPEN INNOVATION AND ORGANIZATIONAL PERFORMANCE: EVIDENCE FROM MALAYSIAN PUBLIC SERVICE ORGANIZATIONS
No full textWhile confronting a multitude of internal and external challenges, public service organizations are consistently subjected to greater expectation and public scrutiny to perform. As such, previous studies have suggested that innovation could play important roles in enhancing the performance of public service organizations, especially by leveraging external resources and capabilities through open innovation. Despite the promise of how advantageous open innovation is, there is conflicting evidence of its impact on organizational performance. Therefore, this study was conducted to investigate the relationship between open innovation and organizational performance in the context of public service organizations. Through a survey questionnaire collected from 112 out of 155 local authorities in Malaysia, quantitative data were analyzed using PLS-SEM in the SmartPLS 4 software to test hypotheses of this study. The results suggest that while open innovation has a significant positive effect on organizational performance, the relationship was not moderated by the type of innovation. The findings of this study provide some new insights into the impact of open innovation on organizational performance, particularly in the public sector. Nevertheless, it is recommended for future research to investigate the specific impacts of different open innovation activities or types on performance in a more diverse context
PINN-Based Tool Wear Modeling and Prediction
No full textTo address the challenges of low prediction accuracy and weak physical interpretability in tool wear modeling, this study proposes a Physics-Informed Neural Network (PINN)-based hybrid framework that integrates wear stage perception and physical prior knowledge. Four representative models-Long Short-Term Memory (LSTM), Stepwise Dual-Driven, Basquin-based PINN, and Empirical Formula-PINN (EF-PINN)-are constructed and systematically evaluated using real milling vibration datasets. The EF-PINN embeds empirical wear laws as soft physical constraints within the neural network loss function, enabling a balanced fusion of data-driven adaptability and physical interpretability. Experimental results demonstrate that EF-PINN achieves superior performance in wear trend fitting, nonlinear degradation modeling, and generalization under varying cutting conditions, significantly outperforming traditional data-driven and purely mechanism-based approaches. The main contributions of this work are: (1) Establishing a unified comparative framework for data-, hybrid-, and physics-informed models; (2) Developing an EF-PINN that bridges the gap between empirical knowledge and data-driven learning; and (3) Experimentally validating the effectiveness of integrating physical priors to enhance reliability and confidence. This study provides a new paradigm for high-precision, interpretable, and robust tool wear prediction in intelligent manufacturing
Multiclass Eye Disease Classification Using Transfer Learning Approach
No full textOphthalmologists commonly use retinal fundus
images for diagnosis. Recently, automation of this process using deep learning has gained significant attention. Multiclass classification, which distinguishes among multiple eye diseases, is more representative of actual clinical settings, however, it presents challenges such as limited availability of annotated datasets, class imbalance, overlapping clinical features across various eye diseases and disease heterogeneity. This study develops deep learning models for multiclass classification of three major eye diseases—cataracts, diabetic retinopathy, and glaucoma—alongside normal cases. A larger and more diverse
dataset was obtained by combining multiple publicly available, well-annotated datasets. Four deep learning models: VGG16, Inception-v3, ResNet50 and EfficientNet-B0, were deployed using a transfer learning approach. These models achieved test accuracies ranging from 74.29% to 78.79%, with ResNet50 performing the best, achieving an accuracy of 78.79%, precision of 80.04%, recall of 78.79%, and an F1-score of 78.76%. The results demonstrate the effectiveness of transfer learning for multiclass classification of eye diseases. Notably, the models
were trained and evaluated on a heterogeneous dataset that
simulates real-world variability in image acquisition,
highlighting their generalization capabilities and robustness to inconsistency. The study provides valuable insights about the performance of pre-trained deep learning models under realistic conditions, supporting their potential as assistive diagnostic tools in actual clinical scenarios
THE IMPACT OF GREEN BANKING ON THE FINANCIAL PERFORMANCE OF BANKS IN MALAYSIA.
No full textThis study aims to investigate how green banking impacts the financial performance of Malaysian commercial banks. To accomplish this, the research used theories like Natural Resource-Based View, Innovation Theory, and Stakeholder Theory. By analysing secondary data from 15 banks over six years (2018-2023). While prior research by Sharif, Sofuoglu, Kocak, and Anwar (2024) identified a knowledge gap in green banking within Malaysia, this study seeks to bridge that gap. The results indicate that green finance initiatives may positively influence the financial performance of banks. This study offers valuable perspectives for policymakers, regulators, and financial institutions by underscoring the importance of promoting green finance initiatives. By exploring the link between green finance and financial outcomes, banks are equipped to make informed choices that bolster their sustainability efforts and strengthen their long-term financial health. It encourages banks to embed sustainability within their business strategies, enabling them to not only support environmental sustainability but also enhance their financial performance, fostering a resilient and sustainable future. Keywords: Operational efficiency, loan-to-deposit ratio, non-performing loan, return on assets.INTRODUCTIONThis study investigates the impact of green banking on the financial performance of banks in Malaysia. Green banking involves the integration of environmental sustainability into the operations and services of financial institutions. As global awareness ofenvironmental issues increases, many banks are adopting green banking practices to contribute to sustainable development, reduce their carbon footprint, and offer environmentally-friendly financial products. The primary focus of this research is to assesshow these green banking initiatives influence the financial performance of banks in Malaysia, considering key financial indicators such as profitability, cost efficiency, and overall market competitiveness. This chapter introduces the research topic and provides a framework for the study. It begins by outlining the background of the study, which presents the context and relevance of the research. It then defines the problem statement, explaining the need for this study and highlighting the gap in current literature. The research questions and research objectives are also clearly stated, guiding the direction of the study. In addition, this chapter emphasizes the significance of the study, highlighting its potential contributions to the banking sector and policy development. Finally, the scope of the study is defined, and an overview of the organization of the thesis is provided, summarizing the structure and contents of the following chapters.This study is motivated by the increasing global and national emphasis on sustainable finance. In Malaysia, green banking remains an emerging area with limited empirical evidence on ho
EMPOWERING KAMPUNG PEROS: A COLLABORATIVE ART-BASED SULAM PROJECT FOR SUSTAINABLE TOURISM
No full textThis SULAM project highlights how a collaborative arts and digital storytelling initiative empowered the community of Kampung Peros located within the Sarawak Delta Geopark to promote sustainable tourism. By merging creative disciplines such as mural design, documentary filmmaking, and digital marketing, the project increased the village’s visibility, enhanced cultural preservation, and built the digital and creative capacities of local residents. This community-led transformation has contributed to new economic opportunities, revitalized cultural pride, and aligned with national and global goals for sustainable development.
Keywords: Sustainable Tourism, Community Empowerment, Visual Arts, Sarawak Delta Geopark, Cultural Preservation, Kampung Pero
CORPORATE DETERMINANTS OF DIVIDEND POLICY: EMPIRICAL EVIDENCE FROM MALAYSIAN PUBLIC LISTED FIRMS
No full textThis study investigates the determinants of dividend policy among 30 firms listed on the FTSE Bursa Malaysia KLCI (FBMKLCI) from 2015 to 2023. Drawing on signaling theory and agency cost theory, the analysis examines the influence of liquidity, profitability and leverage on dividend payout ratios (DPR). Using pooled OLS regression with robust standard errors, the results reveal that control variable of growth opportunities have a significant and positive effect on dividend payout, suggesting that Malaysian firms use dividends as a credible signal of financial strength and future prospects. In contrast, liquidity, profitability, and leverage are statistically insignificant, indicating that these financial factors are not the primary drivers of dividend decisions among large-cap firms. The findings extend existing evidence from emerging markets and also provides practical insights for managers, investors, and policymakers in developing dividend strategies that enhance market confidence and shareholder value
Enhanced Real-Time CO₂ Monitoring Framework with IoT Integration for Domestic-scale Carbon Capture Machine
No full textThis paper presents an enhanced real-time Carbon Dioxide (CO₂) monitoring framework for a Domestic�scaled Carbon Capture Machine (DSCCM) developed for small�scale fish-smoking operations in cottage industries. The system
incorporates a three-stage emission filtration and treatment
process consisting of: (i) a high-temperature catalyzer for
filtering particulates and converting volatile compounds such as carbon monoxide (CO) and polycyclic aromatic hydrocarbons (PAHs) into CO₂, (ii) a water-based scrubber to separate CO₂ from ambient air, and (iii) a low-temperature catalyzer to ensure that residual emissions are rendered non-toxic CO₂. CO₂ concentrations before and after capture are monitored using industrial-grade Non-Dispersive Infrared (NDIR) sensors (SKU: 101991028), integrated with a Raspberry Pi-based Node�RED dashboard for real-time data visualization and analytics. Experimental validation demonstrated a CO₂ scrubbing efficiency ranging from 73.56% to 90.79%, with notably narrow ±3–8% deviation margin when compared to a calibrated Testo 440 reference device. The system is cost-effective, modular, and suitable for deployment in unregulated emission environments,
contributing to more inclusive carbon mitigation strategies in rural and artisanal industries
THE IMPACT OF MACROECONOMIC VARIABLES ON ISLAMIC STOCKS MARKET PERFORMANCE IN MALAYSIA
No full textThis study examines the relationship between macroeconomic variables and the performance of Islamic stocks in Malaysia, focusing on the FTSE Bursa Malaysia Hijrah Shariah Index.
By analyzing the effects of interest rates, inflation, gross domestic product (GDP), and foreign direct investment (FDI), the research addresses existing gaps in understanding how these factors influence Shariah-compliant equity markets. The study adopts a quantitative design using 15 years of quarterly data (2009–2023), yielding 60 observations. An Autoregressive Distributed Lag (ARDL) model is applied to assess both short- and long-run dynamics, complemented by diagnostic tests to ensure validity and reliability. The results show that GDP exerts a statistically significant negative influence on Islamic stock market performance
in both the short and long run, whereas interest rates, inflation, and FDI exhibit no significant effects. These findings offer important implications for investors, policymakers, and other stakeholders, supporting more informed decision-making and contributing to efforts to
strengthen the resilience of Malaysia’s Islamic capital market