Diabetes mellitus is a serious health disease that affects people all over the world. The number of persons identified with diabetes mellitus rises each year. α -Glucosidase is a digestive enzyme used to control diabetes mellitus. The searching for new potent α-glucosidase inhibitors capable of delaying carbohydrate digestion in the human body is an important strategy towards control of diabetes mellitus. In this work, a series of quinoline-based Schiff base derivatives already identified as α-glucosidase inhibitory activity was studied by using 2D/3D-QSAR approach. The best HQSAR/A-B-C-H-Ch-DA and CoMSIA/SEDA models were constructed using thirteen molecules in the training set, resulting in favorable values of Q2 (0.834 and 0.607), and high values of R2 (0.985 and 0.912), respectively. The generated HQSAR/A-B-C-H-Ch-DA and CoMSIA/SEDA contour plots were precious for designing and enhancing the α-glucosidase inhibitory activity of quinoline-based Schiff base molecules. Considering these results, two novel α-glucosidase compounds were designed to possess significant activity. The newly suggested molecules showed good outcomes in the preliminary in silico ADME/Tox evaluations. Molecular docking results revealed that the new designed inhibitors have a good stability in the active pocket of the studied receptor compared to voglibose, clinically used as an α-glucosidase inhibitor. MD simulation and MM-GBSA results confirmed the molecular docking outcomes. Finally, DFT analysis was useful in determining the most electrophilic and nucleophilic centers of the two designed α-glucosidase inhibitors.

This study aims to examine the factors affecting Jordanian Islamic banks’ customers’ adoption of electronic banks. The study relied on quantitative methods, where the study designed a questionnaire based on the Technology Acceptance Model (TAM) which derived from the Theory of Reasoned Action (TRA). The study sample consisted of 470 respondents. The study applied the Partial Least Squares Structural Equation Modeling (PLS-SEM), where the results of the Chi-square test and the standardized root mean square residual (SRMR) test showed the validity of the model for analysis. The results showed that usefulness, privacy, and awareness affect the adoption of e-banking, and that ease to use and electronic skills affect the adoption of e-banking through usefulness. The results also show that Infrastructure does not affect the adoption of e-banking, and Convenience does not affect the adoption of e-banking through Intention to use e-banking. The study advises Islamic banks to spread awareness about the importance of electronic banking and design easy-to-use electronic services that enjoy privacy and security.

The current study aims to determine the factors influencing the intention to employ digital libraries among postgraduate students in Jordanian universities. The data were gathered through questionnaires in the format of Google Forms. The questionnaires were distributed to postgraduate students enrolled in Jordanian universities with digital libraries, who were recruited via purposive sampling. A total of 261 responses were received, with 67 deemed unsuitable for the study analysis and subsequently excluded. Resultantly, 194 valid questionnaires were finalized for data analysis. The SMART-partial least squares (PLS) software was utilized to conduct structural equation modelling (SEM) to test the study hypotheses. This study discovered that the variables, namely performance expectancy, effort, and facilitating conditions expectancy, were significantly and positively associated with the outcome variable, which is the intention to employ digital libraries. Meanwhile, social influence was revealed to be insignificant. Performance expectancy also significantly mediated the correlations between technological readiness and the intention to utilize and between online self-efficacy and the intention to utilize. The present study focused only on potential users among postgraduate students at Jordanian universities with digital libraries. The findings contributed valuable insights into the academic sector, especially library management to enhance the rate of digital library or e-library adoption at Jordanian universities. Digital library managers and policymakers could leverage the findings to design pertinent strategies that increase user engagement within digital library environments. The UTAUT model was demonstrated to be capable of predicting users’ intentions of employing digital libraries and corroborated the mediation role of performance expectancy on the associations between technological readiness and the intention to utilize and between online self-efficacy and the intention to use.

The goal of this research is to test the mediating effect of product symbolism on the relationship between conspicuous consumption and social identity formation in the branded clothing sector of young adults. Young adults between the ages of 20-35 who wear branded clothes in Sri Lanka were considered the target population. The data was collected through a survey to find answers to the identified research questions through a quantitative approach. The Snowball sampling method was used as the sampling method for this study. The Sobel Test was carried out using an online calculator to measure the statistical significance of the mediation. The results showed that the effect of conspicuous consumption on social identity formation mediated through product symbolism could be judged as statistically significant. The findings can help with market segmentation and brand positioning. Knowing these symbolic value attachments to branded clothes, marketers can create their marketing mix strategies to provide solutions for self-image enhancement and sustainable competitive advantage from both consumer and company points of view.

This research investigated how data privacy practices may impact reverse logistics in the automotive engineering sector, particularly by examining whether environmental efficiency plays a mediating role. This research uses the Resource-Based View (RBV) and Dynamic Capabilities Theory (DCT) to understand how data privacy-driven processes support environmental practices and reverse logistics optimization. Primary research is done through structured questionnaires of automotive engineering professionals. The partial least squares structural equation modeling (PLS-SEM) approach tested the relationships amongst data privacy, environmental efficiency, and reverse logistics. However, the results further clarify how key intermediate outcomes, after all, improved environmental efficiency, affected by robust data privacy practices, may enhance reverse logistics processes. The nexus of data privacy and environmental efficiency highlights the critical need to embed respect for private sector information into logistics strategies that achieve superior business performance and also protect corporate sustainability. The findings suggested that environmental consequences must be considered in the flexibility of data-privacy measures with important strategic implications for firms operating in a complex and more environmentally conscious market. This study makes a novel contribution to the extant literature by empirically detecting how environmental efficiency mediates data privacy practices and reverse logistics. These findings will be useful for industry practitioners to use data privacy to enable sustainable logistics management of business operations within automotive engineering.

The study aimed to clarify the most important interconnected factors in the tourism sector “especially in hotels” that contribute to enhancing the interaction of current customers of hotels operating in tourism sector in light of the presence of the customer’s hotel experience as a moderator variable, through an empirical study on hotels, based on an analysis of the opinions of a sample of hotels customers in this sector. The study has been done depending on a questionnaire designed for this purpose and the study employs SmartPLS to analyze the data collected. The study found that the variables: employee efficiency, improving service quality, re-engineering business processes, and enhancing customer relationship management affect the business output generated by current customers of hotels, but the impact of these factors varies on the customers repurchase intention. The factor (Employee’s competencies- EC) has the greatest degree of correlation with an impact coefficient of (-0.227), while the lowest degree of correlation is for the factor (Reengineering business process- RBP) with an impact coefficient of (-0.034). By adopting the variable (CSE) as a moderator variable, the relationships between the independent factors and the dependent factor showed a significant change from the inverse relationship to the direct relationship. The study also showed, through the coefficient of determination (16.1%), that the selected independent factors can be developed either by expanding the sample or by selecting other simple factors or a composite of more than one factor. The moderator variable showed a negative effect on the relationship between the dependent factor (CR) and both factors (ERM and ISQ), while its effect was positive on the relationship between the dependent factor and the other independent factors (RBP and EC).

This quantitative study examined the relationships between privacy, trust and level of service quality, and customer satisfaction. Jordanian firm employees involved in CRM technology were the study samples. Data from 620 completed questionnaires were analyzed utilizing AMOS software version 23. The study hypotheses were tested through Structural Equation Modelling (SEM). The causal relationships among the study’s main variables were examined as well. Results showed a positive impact of trust, privacy, and level of service quality on customer satisfaction. Managers and practitioners could pursue this study results in their CRM systems implementation. Additionally, the relations between privacy, trust and level of service quality, and customer satisfaction could be examined further as these relations in CRM systems have not been adequately examined, especially in emergent industries of developing countries.

This study aimed to demonstrate the impact of artificial intelligence with its dimensions (genetic algorithms, neural networks, intelligent agents, and machine learning) on tax compliance through the mediating role of electronic auditing. The research method used in this study was the descriptive analytic technique, to describe and analyze the phenomenon of the study, which is the effect of artificial intelligence on tax compliance through the mediation of electronic auditing and its relevance to the Jordanian tax authorities. The targeted study population was 205 auditors comprising the directorate of first commercial, directorate of second commercial, directorate of industrial and directorate of services of the income and sales tax department. These are the persons who represent the parties with special knowledge and experience in tax auditing issues. Because of the restricted number of people in the research, an extensive survey technique was applied to choose the study sample. The sample for this research study became the population amounting to 205 people in the Director of Large Taxpayer and medium Tax Payer Department of Income and Sales Tax. SPSS V. 20 was used to process and analyze all the data employing several statistical techniques. In line with the stated objectives, the study established important conclusions where the first was the presence of a significant effect of artificial intelligence on tax compliance through the influential electronic auditing variable. This means to emphasize the significance and function of technologies and AI in the sphere of electronic auditing and to develop their potential in organizing the tax processes and increasing the level of tax compliance. The first systematic suggestions stress the fact that improvements and modernization of the IT environment within the scope of tax departments is needed in order to ensure sufficient support for electronic auditing and artificial intelligence, and to equip the latter with suitable tools and big data analysis software.

With the rapid advancement of blockchain technology, SMEs face an opportunity to leverage decentralized ledger systems to address longstanding challenges related to financial transparency. This study aims to assess the implications of blockchain adoption for SMEs operating in the Jordanian context, focusing on its potential to improve accountability, trust, and efficiency in financial operations. Drawing on quantitative research methods, this paper examines the current state of financial transparency using a structural equation modeling approach of 215 surveys. The findings indicated that there is a positive impact of block-chain technology on enhancing financial transparency. The findings of this research contribute to both academic understanding and practical implications for policymakers, regulators, and SMEs in Jordan seeking to enhance financial transparency through blockchain technology. By shedding light on the positive impact of blockchain on financial transparency in the Jordanian SME sector, this paper aims to inform strategic decision-making and stimulate further research in this emerging field. Ultimately, it underscores the transformative potential of block-chain technology in promoting accountability, trust, and eco-nomic development among SMEs in Jordan and beyond.

Despite the recognized importance of service quality in supply chain management, there has been limited research examining the interplay between digital leadership, service quality, and supply chain management. This study employs bibliometric analysis techniques to investigate how digital leadership influences service quality within the context of supply chain management. Utilizing VOSviewer v1.6.20, we analyzed 490 publications from the Web of Science database pertinent to this domain. Our findings reveal that advanced technologies, including digital leadership, IoT, AI, and blockchain, play a crucial role in modernizing supply chains, enhancing operational efficiency, and achieving environmental objectives. The study discusses the broader implications for both theoretical frameworks and practical applications in the field.