This research attempts to investigate the technological, organizational, and environmental aspects that impact the banking industry's use of business intelligence (BI). In addition, the present research aims to quantify the effect of business intelligence adoption on bank performance to contribute to the current understanding of business intelligence adoption. Upon the completion of the sample verification procedure, 232 samples are collected. Throughout the research investigation, the SEM software is used to process all the acquired data. The study's findings indicate that TOE had a direct and beneficial effect on the adoption of BI systems by banks. Based on the results of the study, the researchers believe that decision-maker and managers would define all activities, responsibilities, and work processes using business intelligence platforms in order to increase their organization's versatility and performance.

This study aims to examine the connection between the disclosure of AI and financial performance of the banking sector in Jordan within a robust panel econometric setup. The purpose of this study is to examine the connection between Artificial Intelligence (AI) disclosure and financial performance of Jordanian banks in a wide-ranging panel econometric approach. The study uses the annual data of the 20 banks in Jordan for the period (2017-2023). The current study differs from previous studies in using panel unit root tests, panel cointegration analysis, fixed-effects and random-effects estimation, Hausman specification testing, and dynamic System Generalized Method of Moments (System GMM) estimation to overcome econometric problems such as non-stationarities, heteroskedasticity, serial correlation, cross-sectional dependence, and endogeneity. AI disclosure is assessed using a newly-developed AI Disclosure Index (AIDI) created by analyzing the textual content of annual reports against the AI Disclosure categories derived from the validated AI disclosure categories covering AI infrastructure, applications, governance, cybersecurity, and digital transformation. ROA and ROE are used for measuring financial performance. The empirical results show that AI disclosure has a positive and significant impact on bank financial performance, as measured by ROE, while accounting for the dynamic persistence and heterogeneity of banks. The results are consistent with alternative specifications and diagnostic procedures. The study is a novel and valuable addition to the literature, as it combines cutting-edge financial econometric techniques with AI disclosure analysis in a new banking market. The results indicate that clear transparency in AI use boosts operational efficiency, builds stakeholder trust, and fosters financial sustainability in banking institutions. The study also offers policy recommendations to regulators and financial institutions to develop a standard for disclosure of AI.

This paper examines the mediating role of Corporate Social Responsibility (CSR) in the relationship between digital marketing tools, specifically Social Media and Electronic Customer Relationship Management (Social CRM), and two strategic marketing outcomes: Digital Marketing Capabilities and Innovation Orientation in digital services, within the Jordanian service industry. A quantitative, cross-sectional survey design was employed. The sample comprised 157 managers and employees working in marketing departments of Jordanian service companies, including banking, telecommunications, and travel agencies. A structured questionnaire was developed using validated scales from previous literature. The hypothesized relationships, including mediation effects, were tested using Partial Least Squares Structural Equation Modeling (PLS-SEM) with Smart-PLS software. The findings reveal that both Social Media and Social CRM have significant positive effects on Digital Marketing Capabilities and Innovation Orientation. Furthermore, CSR partially mediates the relationship between digital marketing tools (Social Media and Social CRM) and Digital Marketing Capabilities. However, CSR does not mediate the effect of digital marketing tools on Innovation Orientation. These results suggest that CSR serves as an important mechanism for building marketing capabilities in the digital environment but is not a prerequisite for fostering innovation. This study contributes to the marketing literature as one of the first empirical investigations to examine the mediating role of CSR in the link between digital marketing tools and strategic marketing outcomes within the Jordanian context. It extends prior research by integrating Social CRM and digital marketing tools into a unified mediation model.

This study investigates the impact of project management capabilities on organizational performance, with a particular focus on the mediating roles of supply coordination, information technology integration, and process innovation. Data was collected from 85 suppliers providing goods and services to educational institutions in Irbid, Jordan, through questionnaires distributed from January 2025. The research adopts a causal quantitative approach, SEM-PLS to analyze the relationships between the variables. The findings reveal that project management capabilities positively influence supply coordination, information technology integration, and process innovation. Moreover, information technology integration and supply coordination significantly enhance organizational performance. This study contributes to a deeper understanding of how project management practices, supported by effective technology integration and strong supply chain coordination, can lead to improvements in organizational performance, especially within educational settings. The results underscore the importance of aligning project management capabilities with technological and collaborative strategies to promote innovation and efficiency.

This study examines the impact of information technology infrastructure efficiency and top management support on the successful adoption of e-learning systems in private Jordanian universities. Based on the DeLone and McLean Information Systems Success Model, data were collected from 265 faculty members, administrative staff, and students using a structured questionnaire. Statistical analysis using multiple regression and structural equation modeling revealed that both infrastructure efficiency (β = 0.41) and top management support (β = 0.38) significantly positively affect e-learning system adoption success, collectively explaining 64% of the variance in success. The results confirm that successful e-learning adoption depends not only on technical aspects but also requires strategic and financial support from top leadership. The study provides an integrated framework for university decision-makers, recommending continuous investment in technological infrastructure while enhancing the leadership role of top management to ensure the sustainability of e-learning initiatives.

Technology has significantly transformed knowledge, education, and access to information by introducing online learning platforms, interactive games, and virtual reality simulations in traditional classrooms, creating a dynamic, engaging, and inclusive learning environment. The ChatGBT project (a pre-developed transformer for training) is a remarkable achievement in artificial intelligence technology. It allows students tailored and efficient learning experiences by providing individual feedback and explanations. ChatGPT e-learning platform has been extensively studied for its adoption and acceptance, but there is a significant gap in research on its acceptability and use, highlighting the need for further exploration. The goal of this work is to bridge this disparity by introducing a comprehensive model that includes three basic elements: performance expectation, expected effort, and social impact. A total of 241 graduate students were surveyed and their data were analyzed using structural equation modeling techniques. The results indicate that “expectation of performance and expected effort” have the greatest impact and importance in determining students’ intentions to use learning platforms via ChatGPT, while social influence does not play an important role. This study enhances the current body of knowledge related to artificial intelligence and environmental sustainability, and provides important insights for professionals, policymakers, and producers of artificial intelligence products. These observations may provide guidance for creating and implementing artificial intelligence technologies to match consumers’ needs and preferences more effectively, while also taking into account broader environmental conditions.