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.

The study aimed to examine the influence of market orientation on SMEs’ performance with the mediating effect of supply chain agility and moderation of innovation capabilities. The data for the study were gathered from the manufacturing SMEs operating in major cities of Jordan. The questionnaire was distributed online to gather the maximum responses from managers of SMEs. The collected data were examined by using Smart Pls. The results highlighted that market orientation not only influences the SMEs’ performance, but it also helps them in developing supply chain agility.

The present study aimed to explore the moderating role of strategic momentum in the relationship between big data analytics capabilities and lean supply chain practices in eight textile companies in Jordan. A quantitative research methodology incorporating a cross-sectional design was adopted to gather questionnaire-based responses to investigate the hypotheses put forth. The sample for the study consisted of 116 respondents, who were selected from a diverse group of senior executives from various fields, including IT, logistics, marketing, production, and strategic planning. These individuals possessed both knowledge and skills in data and business analytics disciplines. The data were analyzed utilizing SPSS version 28 and the PROCESS v3.5 macro developed by Andrew F. Hayes. The results revealed that the strategic momentum positively moderates the relationship between big data analytics capabilities and lean supply chain practices. These findings indicate that high levels of strategic momentum allow an organization to increase resources and focus on investing in and developing its big data capabilities, thereby supporting the implementation of lean supply chain practices.

The objective of the study is to identify the impact of big data on sustainable supply chain management. The current research was conducted on hypermarkets in Jordan. Many of these hypermarket brands are widely scattered in Jordan, for instance, Carrefour, Kareem, Safeway and more. Accordingly, the target population in the current research was hypermarkets managers in Jordan as they are responsible for formulating such strategies in the companies they work for. A convenience sample was selected from the target population that included 770 managers based on the sample size formula. The study hypotheses were tested by covariance based structural equation modeling (CB-SEM). The study results showed the impact of each big data dimension on sustainable supply chain management. Based on this result, the researchers recommend the hypermarkets in Jordan to use modern and diverse methods for accurate collection of reliable data and save it in organized ways, and to employ advanced programs to analyze it and extract information of high value.

The global supply networks have been disrupted and weak connections exposed to an extent that few people have ever seen in their lifetime due to the COVID-19 epidemic. As a result of the severity of the crisis, every country and industry is feeling the effects, and the massive shifts in demand and supply that have happened throughout the epidemic are easily distinguishable from the effects of previous crises. We looked into the adaptability of alliance management and AI-driven supply chain analytics in the context of an ever-changing external environment. We examined four hypotheses in this area using survey data from the American auto components manufacturing industry. To do the analysis, we used Smart PLS. Alliance management capabilities, mediated by AI-powered supply chain analytics capacity, have been found to increase an organization's operational and financial performance. We also discovered, with environmental dynamics as a moderating factor, that alliance management capability has a substantial impact on AI-powered supply chain analytics capabilities. Based on our findings, we have a deep appreciation for the interplay between dynamic capacities and the relational view of organization. Finally, we pointed up the limitations of our study and offered a number of directions for future investigation that might help address some of the concerns that our results raise.

This study has tried to investigate the impact of knowledge sharing quality on E-supply chain management, with the mediating effect of E-trust. To attain the research purposes, a quantitative approach of research was applied. The needed data was collected from a sample consisting of 281 managers of Fast-Moving Consumer Goods (FMCG) companies in Jordan. A questionnaire was utilized to collect the data. Appropriate statistical analyses were conducted such as scale reliability and validity by using IBM SPSS 21 software. Structural model and hypothesis testing using AMOS software were then utilized. The results have shown that knowledge sharing quality with its main dimensions (usefulness, timeliness, accuracy, and relevance) has positive significant impacts on E-supply chain management. Besides that, E-trust has revealed a significant mediating impact between the studied independent and dependent factors. Other complementary future studies related to the practices of E-supply chain management practices, quality of knowledge sharing, and E-trust in other Jordanian organizations were also proposed.

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 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 present study examines the faculty staff’s socio-demographic factors (i.e., gender, academic ranking, and experience) as moderating variables on the relationship between the four interrelated factors (organizational, individual, technological, and client engagement) and their productivity (performance) during the Covid‐19 pandemic. A conceptual framework was developed by integrating several relevant studies in the field of Work from Home (WFH) productivity. To end this, we involved (n=388) academic staff working from home during the Covid-19 crisis to test the hypotheses in the higher education context. The findings showed that the academics’ WFH productivity was significantly associated with the four interrelated factors (organizational, individual, technological, and client-related factors) either collectively or individually, and the most important one was the individual-related factors. The moderation analysis reveals that the effect of the socio-demographic characteristics (gender, academic ranking, and experience) on WFH productivity was varied. Surprisingly, the study findings provided evidence for the first time that the client’s engagement (student) factor, which has not been studied before, was found as one of the main determinant factors of WFH productivity during the Covid-19 crisis.

Hospitals may keep track of all financial transactions using an accounting system. It can produce thorough hospital reports that give management or other interested parties a clear set of information to help them raise the efficiency of the supply chain. Therefore, the goal of this study was to look into the role of the application of an accounting system (AS) in raising the efficiency of the supply chain (SC) in Jordanian hospitals. A questionnaire was used as the data collection method. The descriptive statistical analysis was carried out using SPSS. In addition, 134 employees from these hospitals took part in the survey, according to the results of this study, AS plays a significant role in developing and raising the efficiency of SC in Jordanian hospitals.