This research investigates how social media content marketing impacts customer engagement and it gives more weight to consumer cognition as an intermediary means. According to the study, digital communication has transformed significantly in our modern era, from simple communicative and content-sharing platforms to social media networks evolved into major marketing platforms. Organizations now fundamentally bring about transformations in their interaction with consumers depending on how they choose to use these public forums. As well, this paper begins to provide a comprehensive review of the social media content marketing literature, with topics such as augmented reality, credibility of content, user-generated content, and customer perceptions. The paper has a survey sample of 350 managers from relevant organizations, selected to provide a broad representative range across fields and industries. This study, under the Technology Acceptance Model, aims to understand better, how consumers accept and employ social media content marketing. Research questions to be addressed in this forthcoming paper include an investigation into how consumer belief serves to mediate the relation between social media content marketing and customer engagement Additionally, it aims to investigate the extent to which consumer cognition intervenes in this link, and whether consumers' beliefs moderate results of an interaction with social media platform contents source (such as reading a blog or watching a video). With this theoretical framework and the related literature, the project aims to provide significant insights and make a more successful marketing practice.

In the ever-evolving landscape of supply chain management, the quest for efficiency has become paramount. This abstract explores a groundbreaking solution that combines the power of permissioned blockchain technology with innovative data reduction strategies to redefine how supply chains operate. Traditional supply chain systems often grapple with data overload, causing delays, inaccuracies, and operational inefficiencies. However, this abstract presents a promising approach that unleashes efficiency by harnessing the capabilities of a permissioned blockchain. Through data reduction techniques tailored to the needs of supply chain management, this approach streamlines the flow of information while maintaining security and trust among participants. This paper seeks into the technical foundations of permissioned blockchains, highlighting their suitability for supply applications where confidentiality and controlled access are imperative. Furthermore, it examines various data reduction methodologies, emphasizing their role in minimizing redundant data, optimizing communication, and enabling real-time decision-making. The impact of this innovative approach on supply chain stakeholders is profound. It reduces data related bottlenecks, enhances transparencies, and fosters collaboration among participants. Additionally, it provides a scalable framework adaptable to diverse supply chain ecosystems. As supply chain efficiency becomes increasingly important in our interconnected world, this permissioned blockchain-driven data reduction strategy offers a compelling vision for the future. It promises to unlock a new era of streamlined operations, cost savings, and improved customer satisfaction, ultimately shaping the next generation of supply chain management.

This study provides an analytical view of the correlation between several factors that influence the credibility of information available through various sources on the Internet. The most critical factors include information quality, source credibility, argument strength, message credibility, and average credibility. Additionally, the study explores the impact of gender and years of experience as demographic variables on the nature and size of these relationships. The study relied on a critical review of previous related literature. In addition, it adopted an analytical approach using a sample of 300 Internet users through a questionnaire designed based on the study hypotheses. Most of these relationships were found to be at an average level, except for the relationship between source credibility and information credibility. No statistical indicators were observed. Consequently, the researchers acknowledge the need for caution when generalizing these results to society. The study also found that the gender of the recipient and the number of years of experience did not necessarily play a mediating role in the relationship between the tested factors and the credibility of information received via the Internet.

The current study aims to determine the role of artificial intelligence (AI) in developing the accounting system (AS) in Jordanian Islamic banks. Currently, Islamic banks in Jordan are included in the research population. Using a quantitative research approach, 128 workers of Islamic banks in Jordan were chosen as a sample for this study. The study used a survey questionnaire instrument that was created based on past relevant literature and studies to collect the required data. The results indicated that there is an influence of AI (big data, intelligent agents, expert systems and automation processes) on the development of the AS in Jordanian Islamic banks. Accordingly, the study recommends that to improve AS tasks and reduce associated costs, accountants and accounting companies should always increase their understanding of artificial intelligence.

Breakthroughs and advances in translation technology by virtue of AI-powered MT tools and techniques contributed significantly to providing near-perfect translation. This study aims to evaluate the accuracy of three translation technologies (Google Translate, Gemini, and ChatGPT) in translating multidisciplinary Arabic research titles in the Humanities and Social Sciences into English. A corpus of 163 titles of Arabic research articles from various disciplines, including media studies, literature, linguistics, education, and political science, was extracted from a Scopus-indexed journal, namely Dirasat: Human and Social Sciences Series. The research methodology in the present study lends itself largely to Koponen’s (2010) translation error strategy framework. Based on the data analysis, the findings showed that the renditions provided by these programs were categorically marked with either sense or syntax errors, which often rendered the translations inaccurate. Many polysemous terms with multiple related senses were mistranslated. The results showed that the Gemini translations contained the least errors. In contrast, the human translations contained the least mistranslation and diction errors. Google Translate and ChatGPT, on the other hand, contained the highest number of equivalence-based errors. Unexpectedly, the human translations contained the highest number of syntactic errors, reflecting a lack of target language proficiency. The study's conclusions and findings would be beneficial to translators, students, and scholars who may consider translating their Arabic study research titles and abstracts through the most commonly used AI tools.

A large-scale cloud data center must have a low failure incidence rate and great service dependability and availability. However, due to several issues, such as hardware and software malfunctions that regularly cause task and job failure, large-scale cloud data centers still have high failure rates. These mistakes can have a substantial impact on cloud service dependability and need a large resource allocation to recover from failures. Therefore, it is important to have an efficient management of data recovery to protect organizations data from loss. This paper aims to study some factors that may improve the management of data recovery by using quantitative research design as a methodology. The results of hypothesis testing give strong evidence supporting the positive and significant correlations between the proposed hypotheses and the efficiency of data management recovery. This study finds that the presence of a data center in an organization demands the development of a solid plan for the most effective usage of a software program to handle data recovery.

The concept of the “Metaverse” is a three-dimensional virtual world that relies on simulations of reality to represent real-life experiences, and it can be classified as the next generation in using the Internet. In this research, we will examine the factors that may influence user acceptance of metaverse and the relationships between these variables highlight how different factors can be examined. The goal of understanding these factors is to determine how Metaverse developers can improve this technology to meet user expectations and enable users to better interact with this technology. To achieve this goal, a sample of 312 students’ participants from different age groups was selected to respond to an online Likert scale questionnaire ranging from) strongly disagree equal) to (strongly agree equal 5). The study found that perceived enjoyment significantly positively influences technology metaverse application. Moreover, perceived curiosity and perceived self-efficacy positively influence technology application metaverse transitions. In addition, perceived ease of use (PEOU) and perceived usefulness (PU) positively influence the attitude toward using the Metaverse technology/application, which means that all the previous factors have an overall positive effect on the attitude toward using the Metaverse technology application.
The concept of the “Metaverse” is a three-dimensional virtual world that relies on simulations of reality to represent real-life experiences, and it can be classified as the next generation in using the Internet. In this research, we will examine the factors that may influence user acceptance of metaverse and the relationships between these variables highlight how different factors can be examined. The goal of understanding these factors is to determine how Metaverse developers can improve this technology to meet user expectations and enable users to better interact with this technology. To achieve this goal, a sample of 312 students’ participants from different age groups was selected to respond to an online Likert scale questionnaire ranging from) strongly disagree equal) to (strongly agree equal 5). The study found that perceived enjoyment significantly positively influences technology metaverse application. Moreover, perceived curiosity and perceived self-efficacy positively influence technology application metaverse transitions. In addition, perceived ease of use (PEOU) and perceived usefulness (PU) positively influence the attitude toward using the Metaverse technology/application, which means that all the previous factors have an overall positive effect on the attitude toward using the Metaverse technology application.

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 research investigates the link between technology, organization, and environment, and the uptake of artificial intelligence among SMEs in Jordan. The objective is to get a deeper understanding of the factors that promote or hinder enterprises' use of artificial intelligence during the recruitment of leaders. A total of 295 participants, who were owners or managers in several SME sectors, manufacturing, including services, construction, and agriculture, were selected via judgmental sampling. Data collection was conducted utilizing a survey instrument, and the collected data was processed employing Smart PLS. The findings demonstrated a substantial correlation between attitude toward artificial intelligence uptake and factors such as relative advantage, complexity, top management commitment, and organizational preparedness. Nevertheless, factors like competitive pressure, external assistance, a favorable regulatory environment, compatibility, and staff flexibility do not significantly influence the attitude toward the uptake of artificial intelligence. In summary, these findings provide valuable insights for decision-making and resource distribution. They underscore the significance of factors such as relative advantage, complexity, top management commitment, and organizational readiness in achieving goals in the field of artificial intelligence. Additionally, they identify areas where efforts may not result in significant effects. The practical ramifications and future study paths are emphasized according to current technological needs.

The study aimed to evaluate how cloud technology implementation would affect Jordanian industrial businesses' financial statements' integrity across a range of variables (financial condition, income, cash flow, owners' equity). The investigation involved employees from financial and internal audit departments, including various job titles. A random sample of 150 questionnaires was distributed among the study population, with a 96% response rate (145 retrieved). Respondents were scored using a Likert five-point scale on the 44-paragraph questionnaire. To accomplish its goals, the study used a descriptive-analytical methodology and statistical techniques such as path analysis (using AMOS) and simple linear regression analysis (using SPSS). According to the study, the implementation of cloud accounting has a statistically significant effect on the quality of financial statements by Dimension (statement of financial position, income statement, statement of cash flows, and list of equity), according to the study. Applying cloud accounting has a statistically significant effect on the internal control system, and the internal control system has a statistically significant impact on the accuracy of financial statements. Furthermore, cloud accounting has a statistically significant impact on the quality of financial statements in Jordanian industrial companies through the internal control system as an intermediate variable. The study made several recommendations in light of the earlier findings, the most significant of which are: determining the internal control system's current state both before and after cloud accounting was implemented; creating and executing a robust internal control system compliant with international accounting standards; and assessing the suitability of cloud accounting solutions through thorough evaluations. The report also emphasized how crucial it is to set up ongoing audit and internal control systems to evaluate how well the internal control and cloud accounting systems are working together.