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This study aims to address the critical need for innovative financing solutions in the global housing sector, focusing specifically on Malaysia’s distinct housing finance system encompassing both conventional and Islamic loans. The primary objective is to develop a transformative housing finance model that addresses affordability challenges and reshapes the Malaysian housing landscape.

The study presents an alternate housing finance model for Malaysia, integrating lower monthly payments and reduced household debt. Key variables include house price appreciation rates, interest rates, initial guarantee fees and loan-to-value ratios. Inspired by the Help to Buy (HTB) scheme, the model aligns with proven global initiatives for enhanced affordability, balancing payment amounts, loan interest rates and acceptable price thresholds.

The study’s findings promise to address affordability disparities and reshape Malaysia’s housing finance landscape. The emphasis is on introducing a structured repayment plan that offers a sustainable path to homeownership, particularly for low-income families. Incorporating the future value adaptation concept, inspired by reverse mortgages and Islamic finance, enhances adaptability, ensuring long-term sustainability despite economic shifts.

The proposed model promotes widespread access to homeownership, offering practical solutions for policymakers to improve affordability, prompting adaptable risk management strategies for financial institutions and empowering potential homebuyers with increased flexibility.

The study introduces a transformative housing finance model for Malaysia, merging elements from reverse mortgages, Islamic finance and the HTB scheme, offering potential applicability to similar systems globally.

The main objective of this study is to examine the impact of the Theory of Planned Behavior (TPB) on the behavioral intentions of Fintech usage. The model incorporates perceived behavioral control, attitude, and subjective norms, and the researcher has also included perceived risk and perceived trust. This study involved 192 respondents who were Jordanian citizens. An online questionnaire was used as the survey instrument for data collection. The proposed hypotheses were statistically tested using SmartPLS and SPSS software after examining the data based on initial assumptions. The outcome of the data analysis supports several published hypotheses, with all hypotheses being supported. The significant value of this research lies in its examination of the TPB in the Jordanian context, incorporating perceived risk and perceived trust. To the best of the authors’ knowledge, no previous study has tested the TPB in the Jordanian setting by including perceived risk and trust to understand the behavioral expectations of Jordanian citizens regarding Fintech usage.

This study aims to identify the main factors affecting export competitiveness and its barriers, focusing on the minerals industry so that a scale is achieved for measuring export competitiveness in this industry.

The research was conducted with a mixed method approach in the minerals industry. Among the active companies involved in this industry, 34 export companies and export management companies were selected and evaluated. In the qualitative phase, 18 experts and managers of the industry were interviewed to identify the factors affecting the export competitiveness of these companies and the barriers ahead of them. In the quantitative phase, a questionnaire was distributed among 412 managers and experts in this industry to categorize the identified factors and to measure the relationships among them. For data analysis in the qualitative phase, theme analysis was used. For the quantitative phase, factor analysis and structural equation modeling were adopted.

In addition to identifying the main components affecting the competitiveness of companies in exporting minerals as well as the main barriers ahead of them, the findings of the current research categorized these components using factor analysis. These components were categorized into factors, such as manufacturing factors, demand conditions, related and supporting industries, structural factors, competitive strategy and governmental supports. Afterward, their impacts on export competitiveness were measured and supported.

Although some studies have been conducted to examine the competitiveness in different industries, no research has been found that has examined and identified the main factors affecting export competitiveness and their impacts in the minerals industry with a mixed quantitative and qualitative approach. The findings of this research may help managers and policymakers, at the industrial and national levels, to reach a scale for assessing the export companies involved in this industry by identifying the most essential factors of export competitiveness of minerals. Furthermore, the findings of this research can act as a model for future researchers to develop a scale for export competitiveness in other industries.

Drawing upon social exchange theory, this research investigates the interplay of corporate philanthropy, environmental marketing strategy, relationship quality, greenwashing, and customer citizenship behavior in the family-owned hotels of an emerging market.

A field survey questionnaire was used to gather the data from 394 hotel customers by randomly selecting three premium family-owned hotels in Lahore: Faletti’s, Avari, and Holiday Inn. The data was analyzed using the structural regression modeling (SRM) technique with the assistance of AMOS version 24.

The results show that corporate philanthropy and environmental marketing strategy positively influence relationship quality, and relationship quality positively influences customer citizenship behavior. Relationship quality partially mediates the association between corporate philanthropy and customer citizenship behavior, but we found that greenwashing does not have a moderating role.

This research has theoretical implications for marketing scholars and practical implications of family-owned hotels in emerging markets.

The study has contributed contextually by collecting a unique dataset from family-owned hotels in an emerging market. Theoretically, we have conceptualized a model through the Social Exchange Theory by recommending relationship quality as a mediator and greenwashing as a moderator.

This study aims to examine the influence of various factors on the customers’ purchase intention of renewable energy in Jordan. The hypotheses and model of the study were adopted from previous studies.

The present study was undertaken based on an online survey of 428 Jordanians who are nonusers of renewable energy. The sample was selected using a stratified random sampling method using a structured questionnaire method. Data were analyzed using SPSS version 25.

The results indicated that attitudes, subjective norms (social influence), perceived price, knowledge and perceived behavioral control significantly affect the purchase intention of Jordanian customers to adopt renewable energy. Moreover, the study confirms that there are statistically significant differences between demographic variables such as age, income and education about renewable energy purchasing intentions, whereas gender was not significant.

Some limitations have been identified. First, the generalizability of the findings is one of the common limitations of scientific research, and this study is not an exception. In this regard, the current study has been carried out in the south of Jordan. Therefore, to expand the validity of the findings, future studies need to be attempted in other places in Jordan. Second, the existing study focused on solar panel systems as a form of renewable energy. Future studies could focus on other kinds of renewable energy, such as wind energy. Third, although the sample size of this study was appropriate and sufficient, future studies could use larger samples to enhance the robustness of the results.

The findings of the current study could help practitioners in the renewable energy industry by identifying the key factors that motivate Jordanian customers to purchase and use such technology. They may use the findings of this study in the formulation of marketing policies and the development of marketing strategies to attract more customers to purchase and use renewable energy appliances like solar panels.

This is one of the few studies in the energy industry of Jordan devoted to developing and testing a model of determinants of purchasing intentions for solar panel systems that focuses on renewable energy purchasing behavior. Further, this study used demographic variables as control variables, which makes the study different from other studies by investigating the role of demographic characteristics in the context of the purchase intention for solar panel systems.

This paper aims to identify and provide a theoretical explanation for the barriers that hinder the adoption of emerging technologies in the architecture, engineering and construction industry, irrespective of the company’s size, specialization or geographical location. In addition, the paper proposes potential areas for future research in this domain.

A list of barriers hindering the adoption of emerging technologies was identified and clarified using a systematic literature review of various scientific sources.

Twenty-five barriers were recognized and explained and some suggestions for future research studies were provided.

The barriers related to a specific country or region or to a specific technology were excluded.

By providing a deeper comprehension of the barriers hindering the adoption of emerging technologies, this review is expected to encourage their adoption in the industry. Furthermore, it could prove valuable in devising effective strategies for the successful implementation of these technologies.

The purpose of the study is to classify the radiographic images into three categories such as fillings, cavity and implant to identify dental diseases because dental disease is a very common dental health problem for all people. The detection of dental issues and the selection of the most suitable method of treatment are both determined by the results of a radiological examination. Dental x-rays provide important information about the insides of teeth and their surrounding cells, which helps dentists detect dental issues that are not immediately visible. The analysis of dental x-rays, which is typically done by dentists, is a time-consuming process that can become an error-prone technique due to the wide variations in the structure of teeth and the dentist's lack of expertise. The workload of a dental professional and the chance of misinterpretation can be decreased by the availability of such a system, which can interpret the result of an x-ray automatically.

This study uses deep learning (DL) models to identify dental diseases in order to tackle this issue. Four different DL models, such as ResNet-101, Xception, DenseNet-201 and EfficientNet-B0, were evaluated in order to determine which one would be the most useful for the detection of dental diseases (such as fillings, cavity and implant).

Loss and accuracy curves have been used to analyze the model. However, the EfficientNet-B0 model performed better compared to Xception, DenseNet-201 and ResNet-101. The accuracy, recall, F1-score and AUC values for this model were 98.91, 98.91, 98.74 and 99.98%, respectively. The accuracy rates for the Xception, ResNet-101 and DenseNet-201 are 96.74, 93.48 and 95.65%, respectively.

The present study can benefit dentists from using the DL model to more accurately diagnose dental problems.

This study is conducted to evaluate dental diseases using Convolutional neural network (CNN) techniques to assist dentists in selecting the most effective technique for a particular clinical condition.

This study attempts to fill the research gap by extending sustainability literature and providing empirical evidence that considers sustainability marketing commitment (SMC) as a fundamental attribute of effective marketing strategy that consequently improves tourism service quality, as represented by service attractiveness.

In the current study, data was collected from 313 tourism and hospitality firms. To test the model, this study applied structural equation modeling (SEM) to investigate the relationships among environmental strategy, SMC, supplier trust and service attractiveness in a mediation-moderation setting.

The results indicate that the multiple mediation effects of environmental strategy may indirectly influence tourist attractiveness through SMC and tourism services. The two-way moderating effects reveal that supplier trust and socialization strengthen the service attractiveness development process, while three-way interaction discovered that socialization and supplier trust positively moderate the relationships between tourism services and service attractiveness.

Sustainable strategy is a future trend for tourism business management; however, unknown to most is the role of marketing and environmental strategy in tourism business due to lack of integration with concepts in marketing strategy, with the multidimensionality of tourism services, and with the function of trust and socialization, critically undermining analyses of service attractiveness. This paper combines corporate sustainability and sustainability marketing methods to explore how an environmental strategy can improve tourism services and enhance a destination's attractiveness based on a mediation-moderation mechanism.

The purpose of this paper is to investigate the efficacy of bacterial exopolysaccharides (Eps) in reactive black 5 (RB5) textile dye wastewater bioremediation.

The Eps were produced by bacteria isolated from cotton gin trash soils collected from different cotton-growing regions in Kenya for comparison purposes. A broth medium reconstituted using molasses was assessed for its capacity to produce the Eps. RB5 textile dye wastewater was optimized for dye removal under different temperatures, times and molasses concentrations. Dye removal was studied by Lovibond-Day Light Comparator, UV–Vis spectrophotometer and FTIR.

It was found that cotton gin trash soils contained Eps-producing bacteria. Three of the Eps studied were found to have the capacity to remove at least 80% of the dye from the wastewater.

This research did not assess the efficacy of the RB5 dye removal from the wastewater by mixtures of the Eps.

Bioremediation of textile dye wastewater with Eps produced by bacteria cultured from cotton gin trash soil is significant because it will offer an effective and cleaner alternative to the chemical coagulants.

Alternative treatment of textile wastewater with the Eps would result in safer water being released into the water bodies as opposed to the chemically treated wastewater that contains remnant chemicals.

Research on the use of Eps produced by bacteria isolated from cotton gin trash soils for removal of RB5 dye from textile wastewater has not been done before.

Policymakers are developing national strategic plans to encourage organizations to adopt Construction 4.0 technologies. However, organizations often adopt the recommended technologies without aligning with organizational vision. Furthermore, there is no prioritization on which Construction 4.0 technology should be adopted, including the impact of the technologies on different criteria such as safety and health. Therefore, this study aims to evaluate Construction 4.0 technologies listed in a national strategic plan that targets the enhancement of safety and health.

A list of Construction 4.0 technologies from a national strategic plan is evaluated using the fuzzy technique for order preference by similarity to ideal solution (TOPSIS) method. Then, the data are analyzed using reliability, fuzzy TOPSIS, normalization, Pareto, sensitivity, ranking and correlation analyses.

The analyses identified six Construction 4.0 technologies that are critical in enhancing safety and health: Internet of Things, autonomous construction, big data and predictive analytics, artificial Intelligence, building information modeling and augmented reality and virtualization. In addition, six pairs of Construction 4.0 technologies illustrate strong relationships.

This study contributes to the existing body of knowledge by ranking a list of Construction 4.0 technologies in a national strategic plan that targets the enhancement of safety and health. Decision-makers can use the study findings to prioritize the technologies during the adoption process. Also, to the best of the authors’ knowledge, this study is the first to evaluate the impact of Construction 4.0 technologies listed in a national strategic plan on a specific criterion.