This study aims to model the relationship between business intelligence (BI), supply chain integration (SCI), and firm performance in Jordanian small and medium-sized enterprises (SMEs) using structural equation modeling (SEM). The study utilizes a sample of 400 SMEs from different sectors in Jordan to investigate the hypothesized relationships between the constructs. The results show that BI positively influences SCI and firm performance in Jordanian SMEs. Moreover, SCI was found to mediate the relationship between BI and firm performance. The study also found that the impact of BI on firm performance is fully mediated by SCI, suggesting that SCI plays a crucial role in enhancing firm performance in the context of Jordanian SMEs. The study makes several significant contributions to the literature on supply chain management and business intelligence in the context of SMEs. First, it provides empirical evidence of the positive impact of BI on SCI and firm performance. Second, it sheds light on the mediating role of SCI in the relationship between BI and firm performance. Third, the study contributes to the limited literature on supply chain management and business intelligence in the context of Jordanian SMEs. The findings of this study have practical implications for managers of SMEs in Jordan. They highlight the importance of investing in BI tools and strategies to enhance SCI and firm performance. Additionally, the study suggests that managers should focus on improving their firms' SCI practices to fully exploit the benefits of BI and improve their overall performance. Overall, this study provides new insights into the relationship between BI, SCI, and firm performance in the context of Jordanian SMEs. The study's findings can guide policymakers, researchers, and practitioners in developing and implementing effective strategies to improve supply chain management and business intelligence practices in SMEs, particularly in emerging markets such as Jordan.

This study investigates the impact of cloud-based supply chain management on organizational agility, using a Structural Equation Modeling (SEM) approach. The research is motivated by the growing importance of cloud computing in supply chain management and the need for empirical studies that assess its benefits and challenges. Drawing on a survey of 200 supply chain managers from various industries, we develop and test a theoretical model that explores the relationships between cloud adoption and organizational agility. Hypotheses for the study are tested using the structural equation model. According to the study, Cloud-based SCM has a statistically significant effect on agility and flexibility. The findings have important practical and theoretical implications and provide insights that can help managers and practitioners make informed decisions regarding the implementation of cloud-based SCM solutions and the development of strategies that enhance supply chain agility and competitiveness.

The increasing popularity of intelligence systems in accounting and auditing domains has led to the interest towards drivers of blockchain technology adoption. Consequently, this empirical study inspected the antecedent constructs with direct and indirect impact on blockchain technology adoption in the accounting domain. Data were gathered from 346 accountants employed in Information technology (IT) companies, through an online survey. Structural equation modeling with Smart PLS 4 was employed for research model testing. Out of thirteen proposed direct hypotheses, twelve were accepted. Mainly, the obtained empirical results confirmed effort expectancy impacting blockchain technology adoption the most. Furthermore, the obtained results also confirmed the mediation role of effort expectancy and performance expectancy.

The effect of contextual factors namely information quality, service quality, system quality, Technological readiness, trust in applications (app) and COVID-19 health anxiety, on the intention and consequently the actual use of Mobile Payment (MP) app was examined in this study. Trust, as mediator to the relationship between technological readiness and intention to use MB-app was examined also. Data were obtained from 740 Jordanian Mobile Banking (MB) app users through an online survey. The relationship between service quality, system quality, information quality, trust in the app, COVID-19 health anxiety, Technological readiness and the intentions to use MB-app and the actual use of MB-app was empirically examined. The results showed a positive relationship between service quality, system quality, information quality, trust in the app and COVID-19 health anxiety, and the intentions to use MB-app, and in turn he actual use of MB-app, and a positive mediation of trust on the relationship between COVID-19 health anxiety and the intentions to use MB-app.

E-learning in knowledge management was examined in this study, specifically on how it assists organizations in improving knowledge transfer and e-learning management, to increase performance and employee knowledge management. In this study, e-learning and knowledge management systems and technology were jointly implemented, and its impact on organizational performance was examined. Organizational management was also explored. The present study investigated the relationship between knowledge management (KM) and innovation performance (IP). The mediating effect of knowledge Management was deeply explored. Randomly selected managers from 57 Jordanian manufacturing companies were the study samples, and there were 470 managers involved in this study, from strategic, tactical, and operational levels. Questionnaires were used to gather data, and the questionnaire items covered the constructs of knowledge management, organizational learning (OL), knowledge-oriented leadership (KOL) and IP. A research model was proposed and was tested using structural equation modeling (SEM). The findings were as follows: KOL positively affected KM; KOL positively affected IP; OL negatively affected IP; KOL positively affected KM; OL positively affected KM; KM positively affected IP and KM mediated the relationship between KOL, OL and IP.