INTI Institutional Repository
Not a member yet
2178 research outputs found
Sort by
Importance of Top Management Commitment to Organizational Citizenship Behaviour towards the Environment, Green Training and Environmental Performance in Pakistani Industries
No full textThis research examines the interplay of green training, organisational citizenship behaviour toward the environment, top management commitment, and environmental performance in four different industrial units in Pakistan. These units have been implementing environmentally friendly policies and conforming their environmental activities to the regulatory framework of Pakistan’s National Environment Quality Standards in a sustainable manner. In particular, this research aims to ascertain how green training affects organisational citizenship behaviour toward the environment, and to evaluate the impact of top management commitment to environmental performance and green training. According to hypothesis testing results based on 222 key informants randomly recruited from the industry, green training positively relates to civic organisational behaviour toward the environment. In addition, top management commitment is entirely related to environmental performance. In contrast, green training is also positively associated with top management commitment. This study supports the ability motivation opportunity and resource-based view theories by demonstrating that top management commitment is a key factor in encouraging environmental performance and promoting green training that leads to organisational citizenship behaviour toward the environment. This study has several limitations, as the cross-sectional data were only from the manufacturing sector in Pakistan. The researchers strongly suggest that future studies use mixed-method research to understand the phenomenon better. Future researchers could conduct comparative research by using the current instrument in the service sector. Finally, future researchers could use multilevel modelling and potential moderators and mediators to constructively re-examine the model tested in this study by incorporating new variables accordingly
Systematic Literature Review on Visual Analytics of Predictive Maintenance in the Manufacturing Industry
No full textThe widespread adoption of cyber-physical systems and other cutting-edge digital technology in manufacturing industry production facilities may motivate stakeholders to embrace the idea
of Industry 4.0. Some industrial companies already have different sensors installed on their machines;
however, without proper analysis, the data collected is not useful. This systematic review’s main goal
is to synthesize the existing evidence on the application of predictive maintenance (PdM) with visual
aids and to identify the key knowledge gaps in areas including utilities, power generation, industry,
and energy consumption. After a thorough search and evaluation for relevancy, 37 documents were
identified. Moreover, we identified the visual analytics of PdM, including anomaly detection, planning/scheduling, exploratory data analysis (EDA), and explainable artificial intelligence (XAI). The
findings revealed that anomaly detection was a major domain in PdM-related works. We conclude
that most of the literature lacks depth in terms of an overall framework that combines data-driven and
knowledge-driven techniques of PdM in the manufacturing industry. Some works that utilized both
techniques indicated promising results, but there is insufficient research on involving maintenance
personnel’s feedback in the latter stage of PdM architecture. Thus, there are still pertinent issues
that need to be investigated, and limitations that need to be overcome before PdM is deployed with
minimal human involvement
Effect of anode distance on built-up edge in textured tools produced by plasma focus
No full textIn this paper, the concept of producing a textured tool from AISI304 stainless steel with a plasma focus machine is investigated. A nitrogen ion beam is aimed at a steel sample in an effort to harden it by nitriding and thus render it suitable for use a cutting tool. The results show that the hardness is only slightly enhanced. However, the pitted surface caused by the ion beam gives the steel sample a surface texture that is suitable for a film of solid lubricant to anchor itself. This leads to a decrease in the formation of the built-up edge when performing a dry cutting process on a ductile material such as aluminium. In this dry cutting process, a built-up edge of aluminium material tends to form and adhere to the steel cutting edge and this affects the overall performance of the steel tool. By varying the distance of the anode to the steel tool in the plasma focus nitriding process and then measuring the corresponding amount of built-up edge formed, it is found that, at shorter anode distances, the built-up edge effect is less pronounced
A Cross-Sectional Study Between Organizational Commitment and Citizenship Behavior in Malaysian Bank Simpanan Nasional
No full textThis study aims at evaluating the relationship between organizational
commitment on non-supervisory citizenship behavior in the Bank Simpanan
Nasional, Malaysia. The focal point of the study is to find how negative
individual points of view resulting in lack of commitment and the low
degree of loyalty can impact employee manners such as insufficient
professionalism, poor teamwork, less self-awareness and high turnover in
the current situation. This undesirable trait was also found to be prevalent
among other current banking industry situations. The survey and a
systematic analysis method have been employed to achieve the research
objectives. The sample numbered 172 (Male = 48.8%; Female = 51.2%) of
the non-supervisory staff, selected through purposive or judgmental
sampling. Respondents are selected among non-supervisory employees in
this study. This study uses the quantitative method. The hypotheses further
show a significant positive relationship between first order construct of
organizational commitment and non-supervisory citizenship behaviorOrganizational and Individual. The relationship variables are examined
using IBM Statistical Packages for the Social Sciences (SPSS) software
Version 24. Findings of this study reveal that organizational commitment on
citizenship behavior has a positive and significant relationship. This study
recommends that the bank enhance employee commitment to promote
positive citizenship behavior
An Empirical Analysis of Liquidity, Solvency, Capital Structure and Financial Health of Small and Medium Enterprises in Malaysia
No full textSmall and Medium Enterprises (SMEs) have been the backbone of Malaysian economy as they are generally deemed as the driving force of economic growth, job creation, and poverty reduction in the country. They have been the means through which accelerated economic growth and rapid industrialization have been achieved. While their contributions to development are generally acknowledged, Small and Medium Enterprises confront many obstacles that limit their short to long-term survival and development. To ensure Small and Medium Enterprises to survive, therefore, the purpose of this study is to carry out a financial diagnosis of Malaysian Small and Medium Enterprises financial performance by focusing on their liquidity, solvency, capital structure, and profitability positions using financial ratio analysis. The financial ratios used in this study are solvency ratio, debt-to-equity ratio, current ratio, return on equity ratio and return on asset ratio. Data for the study covered the period 2015 to 2020 and 100 private limited companies from different sectors registered under the SME Corporation website are selected randomly from the listing of SME100 Awards. Data collected through the analysis of key ratios are analyzed using multiple regression. Then, test and assess the Beta Coefficient followed by Multicollinearity test, with the aim to identify the extend of correlation between independent variables and dependent variables. The outcome of this study would provide some insights to internal and external stakeholders towards designing and implementing future strategies to enhance enterprises financial performance
Cloud-Based Enhanced Storage System Using Android Technology
No full textCloud storage is a secure-oriented aspect for users. It provides on-demand service to the user, where users can connect to a cloud through network to store user’s data in the cloud. In a frequently connected world, users obtain personal or shared data stored in the cloud such as Dropbox, Google Drive and Microsoft One Drive with the various gadget. This shows the popularity of cloud storage being used among users. This project aims to integrate enhance features in cloud storage which can be more adaptability for users. This proposed system contains the mobile application and web application that implemented using Android Studio for mobile app, PHP for a web app and it will be stored in the cloud via Google Cloud. This system also provides basic characteristics such as delete file, attach documents and file recovery. The enhancement characteristics are QR Code and chatbot where, QR code used to scan into a web for website and chatbot allow the users to communicate within the same application. The author has chosen the questionnaire and case study as fact-finding method for proposed system
A Narrative Review on Mindfulness Practices in Optimizing Performance Among Sports Individuals
No full textMindfulness practice has become an increasingly popular intervention in optimizing athletic performance in sports. Numerous studies have reported on applying mindfulness for improving the performance of various sports such as tennis, table tennis, shooting, cricket, archery, golf, running, hockey, swimming, and cycling. This narrative review addresses different existing mindfulness programs that enhance sports performance, the outcome measures of mindfulness therapy, and identifies the anxiety and depression that affect the performance of sports individuals. To cope with the issues, the efficacy of mindfulness in performance enhancement and future research directions on mindfulness needs attention
Theory of constraint application on quality management and organizational performance in the construction industry
No full textThis paper aims to review the relationship between the construction industry and the theory of constraints, which significantly impact quality management and organizational performance. Several studies have shown that adopting and implementing quality management is likely to improve an organization's performance. As a result, the relationship between quality management and organizational performance in the construction industry has not been extensively researched by linking this theory (e.g. theory of constraint). This review paper contributes to the body of knowledge on quality management and organizational performance by linking the theory of constraints to improve performance in the Malaysian construction industry through empirical evidence. Practically, this paper gives construction industry practitioners a push to better understand the roles of quality management and its ability to improve organizational performance through its theory of constraint (TOC) use. This review recommended that the analysis of structures should continue by using long-term activity-based costing (ABC) tools in future research
Strategies in Minimizing Dependency on Foreign Workers in Malaysian Construction Industry
No full textThe Malaysian construction industry contributes significantly to the country's economic growth as
well as the development of social and economic buildings. Majority of the construction companies
prefer to hire foreign labour due to the easy employment and low wages rate as well as the
unpleasant working environment (3D - Dirty, Dangerous, and Difficult) that local workers find
undesirable. As a result, the number of migrant workers has gradually increased. Indeed, the
influx of migrant workers has undeniably caused negative impacts to human health, such as
malaria and COVID-19, as well as political and social problems. These shortcomings have
influenced our country's economic development. As a result, this paper intends to determine the
strategies in minimizing the dependency on foreign labours in the Malaysian construction industry
by identifying the factors as well as the negative impact induced by foreign labours. This study
focuses only on the general opinions of the registered construction firms in Kuala Lumpur. The
opinions of respondents were gathered from questionnaire surveys and phone interviews to provide
a more comprehensive analysis of the current situation of reliance level on foreign labours. It was
found that one of the negative impacts that agreed by most of the respondents is affecting the level
of productivity due to insufficient expertise of foreign labours. According to the results, all the
strategies listed are viable, but stronger agreements are seen on the allocation of incentive to import
work-saving technologies with the aid of the Government. Also, the results obtained had certain
validity which makes strategies workable, as the responses were received from the registered
contractors who act as employers to foreign workers. This research enhances the direction for
relevant parties such as the Government, CIDB, and IBS-related firms to adopt potential strategies
to reduce the dependence on foreign labour. The professional boards have to restructure awareness
campaigns into the form of comprehensive awareness programmes and exhibits of best practice
for IBS to be recognized and widely used
Breast Cancer Prediction Model Using Machine Learning
No full textBreast cancer requires early detection, hence it can be prevented earlier or treated more optimally. This article aims to demonstrate predictive modelling of breast cancer and evaluate the accuracy of its predictions using a machine learning approach. This study uses secondary data from the Wisconsin Breast Cancer Dataset (BCWD) which consists of predictive factors for breast cancer and labels for benign or malignant cancers that result. Modelling with machine learning is done by selecting three candidate algorithms, namely Random Forest, Support Vector Machine, and Logistic Regression. Evaluation of the classification performance of each algorithm is carried out by analysing its sensitivity, specificity, and accuracy. The experimental results show that Random Forest has better prediction accuracy (99.6%) followed by Support Vector Machine (98.7%), and Logistic Regression (93.9%)