Recently, there have been a growing number of articles focusing on the benefits of adopting e-SCM systems and the value of such systems in supply chain performance. However, less academic research was devoted to understanding factors affecting the adoption intention of such systems. This study uses the technology, organization, and environment (TOE) framework to examine factors that affect the adoption of e-SCM systems in Jordan, where limited research has been conducted in this country. Through an online survey filled by 251 participants via the LinkedIn website, the study shows that perceived relative advantage, financial resources, employee competency, top management support, competitive pressures, and customer pressure positively impact the adoption intention of e-SCM systems. The findings confirm the association between variables embedded in the TOE framework and the adoption intention of innovative supply chain systems and solutions and support earlier findings. According to the study findings, e-SCM systems providers should focus on the relative advantage these systems offer to increase the likelihood of their adoption.

This research aims to fill the research gap with empirical evidence that exists about the impact of blockchain and smart inventory systems on supply chain performance in the retail industry in the UAE. The proposed model is uniquely researched as no prior research explores the link between supply chain performances, blockchain, and smart inventory in prestigious academic journals. A quantitative technique with convenient cluster sampling is used. A descriptive, exploratory, causal and analytical design was applied—a sample size of 303 respondents was used for data analysis through regression and hypothesis with ANOVA. The findings revealed a significant positive impact of blockchain and smart inventory systems on SC performance. Limited construct-based research can be focused on more industries and constructs for future studies. There are numerous chances for businesses to leverage blockchain technology to their advantage over the competition, giving them the chance to strengthen their market position. Managers must carefully consider the qualities of their goods, services, and supply chains to ascertain whether they require or would sufficiently benefit from blockchain.

This study came with the aim of identifying the impact of the green supply chain on sustainability. This research targeted managers at the senior and middle levels of the Pharmaceutical Industry in Jordan, as they were formulating the company's strategies and determining its policies. A purposive sample consisting of 258 managers was selected. To gather the data needed for the analysis, a self-report questionnaire was used formulated electronically through Google Forms. AMOS software was used to examine the research hypotheses. The study concluded that there was an impact of the green supply chain with its dimensions (Eco-Design, Green Distribution, Green Purchasing, Green Manufacturing, and Green Reverse Logistics) on sustainability. Based on this result, the researcher recommends pharmaceutical companies in Jordan to take green initiatives and the trends towards implementing a green supply chain approach that reduces the consumption of non-renewable resources and waste, and to establish special laws and regulations in the company that oblige employees to apply the green approach in their practices within the work.

The aim of this study is to identify the effect of supply chain resilience as measured by supply chain flexibility, supply chain collaboration, and supply chain agility on supply chain performance. A sample consisting of employees from chemical industrial companies in Jordan was selected to collect data using an electronic questionnaire. Analyzing data via SmartPLS 3.0, the results showed that supply chain collaboration and supply chain agility as key dimensions of supply chain resilience had significant effects on supply chain performance, while supply chain flexibility exerted insignificant effect on supply chain performance. Therefore, managers are recommended to improve their firms’ abilities to carry out effective work with partners and to enhance firms’ abilities to respond quickly to unpredictable changes. Scholars are also requested to conduct further studies such as investigating the effect of supply chain redundancy on supply chain performance.

This paper examines the health operations flexibility dimensions in the United Arab Emirate in the healthcare sector by employing Structural Equation Modeling (SEM) approaches. The study also attempts to determine the numbers for the operational flexibility dimensions which will help the researchers in future find healthcare operational flexibility dimensions valid and reliable. A model consisting of two constructs of operations flexibility structures: external flexibility and internal robustness is examined to measure health operations flexibility elements in service sectors. Respondents are the health leaders (managers, middle manager, top manager and others) who were working in health service sectors in the United Arab Emirate. The underlying constructs of operations flexibility are empirically verified and validated through Reliability Analysis Procedure, Exploratory Factor Analysis (EFA), First and Second Confirmatory Factor Analysis, and Construct Validity Procedures, Structural Equation Modeling (SEM) was employed to test the model, drawing on a sample of 250. The findings revealed that the model of the UAE health service sector consists of two latent's operations flexibility dimensions namely external flexibility and internal robustness, each dimension consisting of four items. Further research should be considered to validate these findings in the other firms. The two dimensions of health operations flexibility represent a valid instrument to measure the operations flexibility in the services sector in the United Arab Emirate. This research is important for one to understand the main topics of health operations flexibility in the health services sector.

Artificial intelligence is user-friendly and incorporates a useful number of characteristics that are common across the various services that are provided. By enhancing inventive engagement, artificial intelligence (AI) applications enable a more participatory setting in government agencies. The objective of this research is to find out how the UAE consumers feel about using AI in educational settings. Included in the framework are the characteristics of acceptance, which are: perceived compatibility, trialability, relative advantage, ease of doing business, and technology export. 466 questionnaires from various universities have been gathered. The research model was examined using machine learning algorithms (ML) and partial least squares-structural equation modeling (PLS-SEM), which centered on the student's questionnaire responses. The IPMA is also used in this research to evaluate performance and importance of the variables. The theoretical framework of the research links the qualities of the individual variables and those of the technology which makes it new. The findings indicate that the diffusion theory factors outperform the other two factors of ease of doing business and technology export. It ought to be mentioned that when it pertains to the estimated value of the dependent factor, the J48 classifier largely outperformed other classifiers. This study’s findings can guide educational institutions in the UAE to recognize the importance of each acceptance factor in the successful integration of AI technologies. Institutions can use these insights to tailor their strategies, enhancing AI adoption among students and faculty alike. Specifically, the results suggest prioritizing factors from diffusion theory in educational AI implementations, ensuring these technologies are perceived as advantageous and compatible with existing practices. Furthermore, the superiority of the J48 classifier suggests that similar analytical techniques could be employed by educational institutions to continually assess and improve their AI initiatives. The dominance of diffusion theory factors invites further exploration into how these elements specifically influence AI acceptance in other sectors or regions. Additionally, the comparative underperformance of ease of doing business and technology export as factors suggests a need for deeper investigation into how these dimensions can be better leveraged in the context of AI in education. Future research could also explore longitudinal studies to assess the sustainability of AI acceptance over time and experiment with integrating new machine learning algorithms to compare their predictive power against the J48 classifier in different educational settings.

In this digital age, fraudulent practices are among the most challenging that organizations must be aware of due to the increasing use of online transactions. This also applies to the banking sector whose business has become more complex with the recent developments in information and communication technology, which has changed the nature of bank fraud requiring advanced prevention measures. From this perspective, this paper aims to determine how cybersecurity affects fraud prevention for Jordanian commercial banks. A five-dimensional NIST cybersecurity framework was used. The research data was collected from 173 information technology managers in commercial banks listed on the Amman Stock Exchange. Structural equation modeling (SEM) was applied to investigate research hypotheses. The results of the research demonstrated the significant impact of cybersecurity in fraud prevention, especially detect function which had the largest impact among the dimensions of cybersecurity. Therefore, a set of recommendations were formulated for policymakers in Jordanian commercial banks, the most important of which is the adoption of multi-factor authentication (MFA) approaches for customer accounts, employee access, and biometric systems that add an additional layer of protection and make access to sensitive information to unauthorized individuals more difficult.

Recent technological advancements are endless and have had a profound influence on everyone in every part of life throughout the preceding decades. Artificial intelligence is one such invention that has the potential to change the world. Now, artificial intelligence is being used in almost all commercial operations. Hence, this research attempted to investigate the impact of artificial intelligence dimensions, including natural language processing, machine learning, expert systems, and computer vision on the financial decisions of pharmaceutical companies in Jordan. A cross-sectional approach was used through a comprehensive survey to collect research data from 148 accountants and financial managers in pharmaceutical companies listed on the Amman Stock Exchange with a response rate of 81.3%. The research hypotheses were examined using structural equation modeling of the collected quantitative data. The results indicated that the dimensions of artificial intelligence positively impact financial decisions. Accordingly, companies should spend on building strong artificial intelligence infrastructure and skills. Access to modern artificial intelligence technology, data analysis tools and cloud computing resources are also essential to rationalizing financial decision-making. Besides, Jordan's pharmaceutical sector can overcome these limitations and realize the full potential of artificial intelligence in financial decision-making by solving data privacy issues, encouraging ethical AI re-search, investing in artificial intelligence expertise, and enhancing collaboration.

Web 2.0 has changed the way consumers access information. This study aims to investigate the relationship between social media (Watsons’ Facebook page) content and consumers repurchase intention. In addition, it determined whether E-WOM and interactivity can act as the mediating variables between the social media content and repurchase decision. The data were collected through online and offline questionnaires. A total of 146 valid questionnaires were obtained and analyzed using Partial Least Square Structural Equation Modeling (PLS-SEM) through the SMART-PLS 3.3.9 software. The findings support the direct effect of social media content on E-WOM, interactivity, and repurchase intention. Moreover, the results confirmed the mediating role of interactivity between social media content and repurchase intention, however, E-WOM does not mediate between social media content and repurchase intention. The present study suggests some managerial implications for beauty brand retailers and provides fundamental strategies related to their social media.

Social media influencers have become a more effective modern marketing approach used by businesses to influence consumers' intention and attitude. This study explores this influence by involving several factors of influencer’s characteristics on both consumers’ attitude and intention. Also, a moderation role of vloggers as a new emerging marketing tool is also examined in this research. To conduct this research and achieve its key objective, the study uses a quantitative research method to collect data from TikTok users which has also become a more worldwide favorable web device for short videos. PLS-SEM method is conducted in the phase of analysis and the results show a significant influence of the hypothesized research model except the influence of source relatability on consumer attitude and the moderating role of vloggers on consumer intention. The research findings provided unsurprisingly implications and supported the existing related literature in this field but contribute to cover the research knowledge gap through the integrated new model including numerous variables that have not been examined previously together in a unique framework.