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.

The basic aim of the ongoing article is to examine the impact of social corporate responsibilities on the financial reporting quality of Jordanian manufacturing firms. For this purpose, data has been extracted from the top fifteen manufacturing companies by using corporate reports along with the Amman Stock Exchange from 2010 to 2020. The random effect model along with the generalized method of moment (GMM) has been executed for analysis purposes. The results revealed that social corporate responsibilities have positively impacted on the financial reporting quality of the Jordanian manufacturing firms. These findings have been guided to the regulators that they should provide the focus on the social corporate responsibilities that enhance the quality of financial reporting of the firm. The findings of the current study may be helpful for the manufacturing firm who wants to produce better quality of financial reporting along with the upcoming studies who want to investigate this area in their studies.

Adopting the Supply Chain Operations Reference (SCOR) model, this study aims at investigating the impact of big data (volume, velocity, variety, veracity, and value) on supply chain performance through the mediating role of supply chain management (plan, source, make, deliver, and return) assuming four hypotheses. Data were collected using a questionnaire from managers of food processing companies. The results showed that big data affected supply chain management significantly and positively, which in turn affected supply chain performance significantly and positively. In addition, big data exerted a significant and positive impact on supply chain performance. Based on these links, it was found that supply chain management mediated significantly the effect of big data on supply chain performance. The study contributes to the literature showing that big data plays a pivotal role in improving supply chain performance and supply chain performance from the SCOR model perspective is critical for the relationship between these two constructs.

The aim of this research is to examine the impact of supply chain management through social media on competitiveness of the private hospitals in Jordan. The population of the study includes managers in various administrative disciplines. Therefore, the complete census method was used in this research to collect the primary data, where the total responses were 438 responses were used for analysis. The questionnaire was used as a basic instrument in the current research, as it was designed electronically through Google Forms and sent to the research sample via email. AMOS software was used to test the research hypotheses. The results showed that all dimensions of supply chain management through social media had a positive impact on competitiveness; the greatest effect was for strategic relations with suppliers. Based on the study results; managers at the examined companies should enhance their usage of social media with suppliers, according to the report, in order to support strategic connections with them.

The goal of the study was to determine the influence of green supply chain management strategies on performance in Jordanian industrial enterprises using just in time. All of Jordan's manufacturing enterprises were included in the analysis. A total of 218 companies were selected from the manufacturing industry. The study hypotheses were tested using Path Analysis. The results showed that green supply chain practices had a significant indirect effect on performance through JIT. Based on the study findings, the researchers recommend individuals and decision-makers to improve the expected results of green supply chain practices in the performance of economic and social business through just in time production and increasing the interest in logistics services as one of managing green supply chains practices in these companies.

The researchers used positivism to study the effects of artificial intelligence (AI) applications on human resource (HR) productivity through employee technical expertise. This study targeted employees in the health care sector in Jordan. This research used a self-reported questionnaire as the primary data collection tool. We developed this questionnaire by reviewing relevant literature and designed it electronically using Google Forms. The procedures followed in analyzing the initial research data included a series of procedures employing SPSS and AMOS software. The study results indicate that Artificial intelligence applications (AIA) produce a positive effect on HR productivity challenges (HRP) by interplaying the mediating role of employees' technical expertise (ETE) in the sector of the service industry. HR productivity challenges were the essential purpose of investigating the impact of Artificial intelligence applications through employees' technical expertise to decrease challenges and find a balance between the employees' skills and AI Apps implementation instead of replacing HR skills.

As the workforce worldwide goes through a transformative shift towards remote work, this paper discusses the positive effects of this quite flexible work arrangement on team’s innovation performance (TIP) in multinational, non-governmental organizations (NGOs). Adopting cross-sectional, quantitative research design, empirical data were collected through a survey of 268 employees of multinational NGOs operating in Jordan. The collected data were, then, analyzed using structural equation modeling. The results of the analysis showed that remote work has significant, positive effects on TIP in NGOs. Of the various remote work features investigated, spatial flexibility has the highest effect. The study results contribute to the ongoing discourse on the future of the work styles and have implications for leaders, policymakers, and practitioners who seek promoting innovation in multinational NGOs.

The growing significance of Artificial Intelligence (AI) across different fields highlights the essential role of user acceptance, as the success of this technology largely depends on its adoption and practical use by individuals. This research aims to examine how perceived cybersecurity, novelty value, and perceived trust affect students' willingness to accept AI in educational settings. The study's theoretical basis is the AI Device Use Acceptance (AIDUA) model. Using structural equation modeling, the study tested hypothesized relationships using data from 526 students at Jordanian universities. The results showed that social influence is positively associated with performance expectancy, while perceived cybersecurity is positively related to both performance and effort expectancy. Novelty value is positively associated with performance expectancy but a negative one with effort expectancy. Additionally, effort and performance expectancy significantly influence perceived trust and the willingness to accept AI. Moreover, perceived trust has a notable positive effect on the willingness to accept AI in education. These findings provide valuable guidance for the creation and improvement of AI-driven educational systems in universities, contributing to the broader understanding of AI technology acceptance in the educational field.

This research examined how virtual reality technology affects the marketing performance of the fashion industry in Jordan. Based on a sample composed of 528 online customers, structural equation modeling (SEM) was utilized as a statistical approach for hypothesis testing. The research findings demonstrated that virtual reality technology had a positive significant impact on marketing performance. This examination provides many implications that managers in the fashion industry in Jordan could recognize, the most notable was encouraging them to focus on increased product demos utilizing virtual reality technology in order to improve customers' comprehension of the product and boost their confidence when making purchase decisions.

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.