Digital transformation is important not only in the manufacturing sector but can also help service-based organizations to achieve competitive advantage. Therefore, this study has examined the impact of digital transformation on competitive advantage and the mediating role of entrepreneurial orientation. Innovation capability is considered a moderator between digital transformation and competitive advantage. The data for the research were gathered from service companies in Jordan, and AMOS was utilized for the analysis. The results revealed that digital transformation not only influences competitive advantage but also affects entrepreneurial orientation. Entrepreneurial orientation significantly mediates the relationship between digital transformation and competitive advantage. In addition, innovation capabilities moderate the relationship between digital transformation, competitive advantage, and entrepreneurial orientation. Innovation, production, and operational managers as well as owners of service companies can use the results of this research as a guideline for policy-making in order to develop a competitive advantage.

Earlier literature has shown that the implementation of FinTech innovations is not only determined by banks, financial institutions, or government support, but also by the perception and experiences of FinTech users. FinTech research has shown encouraging findings from scholars in developed countries. However, little is known about the users’ acceptance and use of FinTech in Jordan. The aim of this study is to investigate the determinants of users’ intentions and e-Loyalty toward FinTech adoption in Jordan post the COVID-19 era. A conceptual framework was developed by integrating the four original constructs of the unified theory of acceptance and use of technology (UTAUT), namely performance expectancy (PE), effort expectancy (EE), social influence (SI), and facilitating conditions (FC), with three additional factors: personal innovativeness (PI), financial literacy (FL), and uncertainty avoidance (UA). In addition, the proposed model considered the e-Loyalty of FinTech users as a consequence of having a good FinTech experience. A quantitative approach using a cross-sectional online questionnaire was applied to collect data from 423 FinTech users. Data were analyzed utilizing structural equation modeling (SEM) based on AMOS 26.0 software package. The findings revealed that UA has a moderating effect on the relationship between FC and users’ intentions. Also, PI has a significant impact on PE and EE. While PE, SI, and FC are factors that enhance behavioral intentions. In return, it builds users’ e-Loyalty toward FinTech services and is deemed a new normal behavior. This study may help FinTech service providers and policymakers better understand the, currently relatively low, usage rate of FinTech, and how it contributes to the development of strategies that boost the acceptance and e-Loyalty of FinTech by Jordanian users after the COVID-19 era, where FinTech is still considered an innovation.

Bank lending to SMEs plays a vital role in economic growth, contributing significantly to employment and GDP. Access to bank lending is crucial for small- and medium-sized enterprises (SMEs), as they contribute significantly to global employment and GDP. New financial technologies promise better bank operations, fewer costs, and enhanced credit supply to SMEs. However, there is still a lack of empirical findings on how these technologies can solve demand-side bank lending problems for small- and medium-sized firms. This study gathered data from a sample of 381 respondents, comprising CEOs, managers, officers, loan managers, IT consultants, and other relevant stakeholders. The findings indicate that the adoption of blockchain technologies, as well as the adoption of Big Data technologies encompassing cloud computing, data analytics, algorithms, and programming, along with the adoption of mobile banking technologies, have had a substantial positive impact on bank credit supplies for small- and medium-sized enterprises (SMEs) in Pakistan. This novel study contributes to existing knowledge in two ways. First, it provides knowledge to SMEs looking to adopt new technologies; second, it provides knowledge to a manager looking to finance the SMEs with information asymmetries. This research also provides key findings for researchers and policymakers.

This study aims to determine the impact of green marketing (green perceived value), green products (green buildings), and environmental concerns on Jordanian consumers’ attitudes toward buying green buildings in Jordan. The research population includes all consumers in Amman, the capital of Jordan, who might be interested in buying such buildings. A convenience sample is used to collect data from the respondents by distributing the questionnaire among 400 consumers using Google Forms. 357 questionnaires were found valid for statistical analysis. The results of the multiple regression test showed that R equals 0.815, which indicated that green marketing and consumers’ attitudes toward buying green buildings in Jordan are positively and highly correlated, with a percentage of 81.5%. R square equals 0.664, indicating that the variation in green marketing explains 66.4% of the variance in consumers’ attitudes toward green buildings in Jordan. Moreover, the hierarchical multiple regression test showed that there is an increase in R and R2 values in the existence of product awareness as a moderating variable between green marketing and consumers’ attitudes toward buying green buildings in Jordan.

The rising complexity of financial fraud in highly digitalized regions such as the Gulf Cooperation Council (GCC) poses challenging issues owing to class imbalance, adversarial attacks, concept drift, and explainability requirements. This paper suggests a hybrid machine-learning framework (HMLF) that incorporates SMOTEBoost and cost-sensitive learning to address imbalances, adversarial training and FraudGAN to ensure robustness, DDM and ADWIN to achieve adaptive learning, and SHAP, LIME, and human-in-the-loop (HITL) analysis to ensure explainability. Employing real transaction data from the GCC banks, the framework is tested through a design science research approach. Experiments illustrate significant gains in fraud recall (from 35% to 85%), adversarial robustness (attack success rate decreased from 35% to 5%), and drift recovery (within 24 h), while retaining operational latency below 150 milliseconds. This paper substantiates that incorporating technical resilience with institutional constraints offers an auditable, scalable, and regulation-compliant solution for detecting fraud in high-risk financial contexts.

All major sectors are rapidly embracing AI technology to provide rapid and quality services to patients. Along with opportunities, the integration of AI in healthcare has some ethical and legal challenges. The present paper aims to discuss ethical and legal concerns of integrating AI technology into the Jordanian healthcare system. Focus-group discussion (FGD), a qualitative method, was applied to collect primary data from six participants. Results show that the Jordanian government is proactive in integrating AI in core sectors, including healthcare. There are some legal provisions to promote secure and safe AI-driven services. However, the legal system does not have a special law that could regulate AI-system. It is highly recommended that the laws should be much more comprehensive, and the training of ethics should be the priority in the Jordanian healthcare system.