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Despite the spread in usage and ownership of credit cards, few studies have examined its effect on consumer debt in developing nations. The main purpose of this paper is to understand consumers' attitude and spending behavior using credit cards.

This study is based on a questionnaire survey conducted in Malaysia. Based on an extensive review of literature, a model is developed to identify the psychographic factors that influence the consumer attitudes toward using credit cards.

The paper found support for some of the theoretical expectations and lends support to some of the earlier deviations reported in the literature.

The findings are likely to be important to banks and financial institutions issuing credit cards, as they help managers to have a better understanding of cardholders in Malaysia and their attitude and behavior toward usage of credit cards.

This paper makes a valuable contribution given the fact that there is a dearth of empirical studies of this nature focusing on Malaysia.

E-government is new to the public administration sector of Abu Dhabi and it is rapidly expanding. The purpose of this paper is to explore the factors that might motivate citizens to adopt the e-government public services provided by the Government of Abu Dhabi Emirate. The insights of the study will help government leaders to plan the delivery of public services effectively.

The study surveyed 638 United Arab Emirates (UAE) citizens living in three main districts of the Abu Dhabi Emirate. The research used an exploratory factor analysis that conforms the validity of the theoretical model to the data collected, confirmatory analysis to extract the latent factors and both multiple regression and structural equation modelling to test the research hypotheses.

The finding revealed that internet trust and performance expectancy was the strongest predictors of intention to use e-government services. Effort expectancy, facilitating conditions and trust had a positive influence on behavioural intention (BI). However, social influence (SI) did not have a significant effect. Gender, age and experience did not affect the relationship between SI and BI. It was also found that BI to use e-government services had a significant influence on the actual use of e-government sites.

When the government gets to know the major factors that affect the adoption of e-government services in Abu Dhabi, it can maximise its returns on ICT infrastructure investments by providing efficient service that could be adopted by the citizens.

The research has theoretical and practical value. Though the unified theory of acceptance and use of technology (UTAUT) model has previously been used in organisational settings, the present study uses a modified version in the context of citizens’ acceptance and use of e-government services. The present study thus provides an extension of the UTAUT model that could be suitable for developing countries such as the UAE.

This study aims to analyze research trends in civil engineering education accreditation, focusing on influential authors, top journals, leading institutions and countries and frequently cited articles. It also explores key research themes and proposes potential directions for future research in civil engineering education accreditation domain.

Data were retrieved from the Scopus database for the period 1985–2024, targeting articles referencing accreditation in civil engineering education. Performance analysis was conducted using Microsoft Excel, OpenRefine and biblioMagika, while science mapping was performed with the Bibliometrix R Package and VOSviewer.

The analysis demonstrates a consistent growth in publications on civil engineering education accreditation since 2000, with the United States leading contributions and Malaysia emerging as a notable contributor among developing countries. Contributions from 226 authors across worldwide institutions were identified. Six key research clusters were uncovered: (1) curricula and accreditation, (2) analytical and problem-solving skills, (3) construction practices and safety engineering, (4) undergraduate civil engineering programs, (5) professional standards in civil engineering and (6) research activities and development.

The findings provide valuable insights for institutions offering civil engineering programs, highlighting the need to align curricula with accreditation frameworks to ensure educational quality. Emphasis is placed on integrating elements such as outcome-based education, competency development and continuous quality improvement to prepare graduates for industry demands and global professional standards.

By offering a foundational framework for understanding the evolving landscape of accreditation, this study provides valuable guidance for institutions aiming to enhance educational quality and achieve alignment with international standards.

The credit card market is very large and segmented by targeting different types of consumers. One type of credit card is one that specifically targets people in the education sector, for instance, students, teachers and other staff members. This study aims to compare the features of education and other credit cards in Malaysia.

The study analyzes data concerning 234 credit cards by using descriptive statistics and a one-way analysis of variance test.

Out of 234 credit cards, this study found only two credit cards especially target education sector customers. The study evaluated 13 features of these credit cards and found that only 2 features are statistically significantly different from other conventional credit cards in Malaysia. These features are interest rate and cash withdrawal charge fees.

This is an original study based on the compilation of data from secondary sources. The findings will provide valuable insights to financial regulatory policymakers, academics and business managers.

Rapid industrialization and construction generate substantial concrete waste, leading to significant environmental issues. Nearly 10 billion metric tonnes of concrete waste are produced globally per year. In addition, concrete also accelerates the consumption of natural resources, leading to the depletion of these natural resources. Therefore, this study uses artificial intelligence (AI) to examine the utilization of recycled concrete aggregate (RCA) in concrete.

An extensive database of 583 data points are collected from the literature for predictive modeling. Four machine learning algorithms, namely artificial neural network (ANN), random forest (RF), ridge regression (RR) and least adjacent shrinkage and selection operator (LASSO) regression (LR), in predicting simultaneously concrete compressive and tensile strength were evaluated. The dataset contains 10 independent variables and two dependent variables. Statistical parameters, including coefficient of determination (R²), mean square error (MSE), mean absolute error (MAE) and root mean square error (RMSE), were employed to assess the accuracy of the algorithms. In addition, K-fold cross-validation was employed to validate the obtained results, and SHapley Additive exPlanations (SHAP) analysis was applied to identify the most sensitive parameters out of the 10 input parameters.

The results indicate that the RF prediction model performance is better and more satisfactory than other algorithms. Furthermore, the ANN algorithm ranks as the second most accurate algorithm. However, RR and LR exhibit poor findings with low accuracy. K-fold cross-validation was successfully applied to validate the obtained results and SHAP analysis indicates that cement content and recycled aggregate percentages are the effective input parameter. Therefore, special attention should be given to sensitive parameters to enhance the concrete performance.

This study uniquely applies AI to optimize the use of RCA in concrete production. By evaluating four machine learning algorithms, ANN, RF, RR and LR on a comprehensive dataset, this study identities the most effective predictive models for concrete compressive and tensile strength. The use of SHAP analysis to determine key input parameters and K-fold cross-validation for result validation adds to the study robustness. The findings highlight the superior performance of the RF model and provide actionable insights into enhancing concrete performance with RCA, contributing to sustainable construction practice.

The purpose of this paper is to develop a new Islamic credit card model that is in line with Shariah principles and can be adopted as an alternative to contemporary Islamic credit card models by Islamic financial institutions in Malaysia.

This paper is theoretical in nature and mainly based on descriptive research method approach.

The overall findings indicate that the contemporary practice of Islamic credit card in Malaysia is still controversial in its design and operation. Moreover, the adoption and practice of Shariah contracts in bay’ al-inah, tawarruq and ujrah models are not in line with fundamental doctrines of Shariah and are imbued with the practice of hilah (legal trick), which allows them to circumvent the prohibition of riba. The paper indicates that Al-Muqassah model possibly has a comparative advantage in design and operation when compared with the bay’ al-inah, tawarruq or ujrah models.

The paper is limited to develop a new Shariah-compliant Islamic credit card model. The paper presents a design and defines the underlying Islamic financial contracts and their working mechanisms in the proposed model. However, it will not address other related areas like consumer perception, legal and regulatory requirements.

The paper will have direct implications on contemporary practice of Islamic credit card in Malaysia and elsewhere. The practice of Al-Muqassah model can also possibly have effects on common well-being and economic development.

The paper has relevance for Islamic financial institutions offering Islamic credit cards. The proposed model is fully in line with fundamental doctrines of Shariah and performs the key functions of an Islamic credit card.