The aim of this research was to investigate the impact of various work-related factors, such as task load, workers’ compensation, and organizational structure community on job success and the overall performance of the Jordan tourism board. The researchers conducted an analysis of 269 randomly selected samples from their study and discussed their findings to validate their hypotheses. The study revealed that factors like compensation levels, organizational structure, community, and task load significantly influence individual and organizational success. The first aspect examined was the task load, which was assessed by considering factors such as job completion rates, daily challenges faced, and the time required for tasks. Work-related compensation, encompassing factors like experience, skill, incentives, and rewards, emerged as the second most crucial factor after working hours. The third and most vital component to consider was the organization structure community, which includes communities of practice, collaborative efforts, and physical infrastructure. According to the research findings, improving employee performance can be achieved by reducing their task load, increasing work income, and developing the organization community that fosters teamwork and the formation of workgroups. These elements collectively impact overall productivity. The study provides valuable insights into an underexplored area, shedding light on how task load, compensation, and organizational structure community interplay. The research's focus on the Jordan tourism board is particularly significant, as it has the potential to help tourism companies enhance their operations and provide superior service to their customers.

The objective of this paper is to investigate the influence of supply chain integration (SCI) on customer satisfaction in the potash supply chain in Jordan. 320 samples are collected after completing the sample checking process. The research study uses partial least squares for processing of data. Study outcomes show a connection among the integration of supply chain and customer satisfaction. In addition, the study shows that enterprise resource planning (ERP) system, business strategy, and suppliers have impacts on the integration of supply chain and customer satisfaction.

The research is aiming to enter deeply into studying the implementation of enterprise resource planning (ERP) and measuring the effects on the integration of supply chain at Jordanian Nuqul Group Company. Defining the effects of applying ERP systems in human resource, and production management departments, and how the implementation process will be effective on the integration with suppliers, customers, and processes are representing the main objectives of this research. 185 research questionnaires distributed, collected, and 150 respondents were accepted for the research study analysis. Furthermore, this research used structural equation models with AMOS for testing research hypotheses. The research findings agreed with the result that applying enterprise resource planning systems could affect positively on the supply chain integration with suppliers, customers, and processes.

This study set out to find out on how big data analytics, workload, work wages, and organizational structure pressures affect employee job performance and overall business performance in the Jordan banking sector in the context of that country's banking sector. 292 samples from the research study were collected, analyzed, and debated to test the study's hypotheses. Employee and company success were found to be affected by workload, compensation, and organizational structure. Workload was reflected by job completion rate, average daily issues, and work completion time, while big data was reflected by external and internal, unique application, indexing, and source correctness. Work compensation, including employee compensation, employee experience and skill, and employee incentives and rewards, is the third primary factor. Communities of practice, group work, and physical infrastructure make up the fourth and last important factor, the organization's structure. The study finds that when dealing with large amounts of data, reducing the workload can improve employee performance, increasing employee motivation through higher wages and bonuses can improve performance, and having an organizational structure that promotes teamwork and work teams can improve employees' abilities to solve problems and improve work performance, which in turn affects overall productivity. This study contributes fresh information to an emerging field that requires more investigation to fully understand the interplay between big data, workload, work wages, and organizational structure pressures. The topic of this study, the Jordan banking sector, is both innovative and highly relevant because it may help financial institutions enhance their operations and provide superior customer service.

The goal of this study was to find out how business intelligence systems, AI, and digital leadership affect how satisfied employees are with their jobs and how much value they add to companies in the Greater Amman Municipality. After the study samples were taken and looked at, a total of 246 samples were approved to be used in the PLS software-based analysis. The results of this study showed that putting in place business intelligence tools, artificial intelligence, and digital leadership all made employees happier with their jobs and gave businesses more value. The research showed that there are four key parts to digital leadership: commander, communicator, collaborator, and co-creator. The main parts of business intelligence are Data Warehouse, Data Mining, Business Process Management, and Competitive Intelligence. Findings show that digital transformation is made up of three key parts: changing processes, developing business models, and changing domains. The results also show that an employee's level of job satisfaction, which includes things like business success, work commitment, and job thinking, is linked to how much value they add to the company. Intriguingly, the current results go against those of earlier studies, which said that the variables of interest have no effect on how happy employees are with their jobs or how much value companies add for their customers. When the results of this study are looked at as a whole, they say that businesses should start doing things that make employees happier at work and increase the value of the business. The current study is innovative because it focuses on the most important parts of business intelligence, artificial intelligence, and digital leadership in order to improve employee satisfaction at work and the quality of business learning with added value in Greater Amman Municipality.

The primary purpose of this study is to investigate how group reference, perceived usefulness, and product quality influence online shoppers' desire to purchase and final purchase decisions. Multiple methods of quantitative analysis and processing of data are used to evaluate and validate the study's hypotheses. Using a Structural Equation Model, the study's theories were tested and analyzed. Customers of digital market websites in Jordan participated in this study by responding to an online poll. Data was compiled from 220 study questionnaires using a systematic sampling strategy. Data analysis with the Structural Equation Model revealed significant favorable effects of group reference, perceived usefulness, and product quality on both purchase intent and final online purchase decisions. The authors chose to center their study around the perspectives, comments, attitudes, and impressions of groups of individuals. Perceived usefulness can be gauged along the aspects of experience, enjoyment, and subjective norm. The words customer expectations, real product specifications, and the quality of the service received all shed light on the product's quality. The originality of this study rests in the model that was created to explain the relationship between group reference, perceived usefulness of products, and product quality as they relate to purchase intent and digital market website use in Jordan.

This study sought to investigate the impacts of big data, artificial intelligence (AI), and business intelligence (BI) on Firms' e-learning and business performance at Jordanian telecommunications industry. After the samples were checked, a total of 269 were collected. All of the information gathered throughout the investigation was analyzed using the PLS software. The results show a network of interconnections can improve both e-learning and corporate effectiveness. This research concluded that the integration of big data, AI, and BI has a positive impact on e-learning infrastructure development and organizational efficiency. The findings indicate that big data has a positive and direct impact on business performance, including Big Data External and Internal, Innovative Usage, Indexing, and Sources Accuracy. In addition, Artificial intelligence positively affects business performance, including Data Accuracy, Data Transparency, Data Speed, and Creative Thinking and Learning. Moreover, business intelligence has a direct and positive impact on business performance, including Data Warehouse, Data Mining, Business Process Management, and Competitive Intelligence. In addition, the findings indicate that e-learning which represents system quality, information quality, and self-efficacy has a positive relationship on enhancing business performance. Interestingly, the present findings are inconsistent with those of previous studies showing the variables of interest which have no effect on e-learning and business performance. Taken together, the findings of this study suggest that firms should begin to apply processes related with applying e-learning and developing business performance. The novelty of the present study lies in highlighting the key dimensions of big data, artificial intelligence, and business intelligence when it comes to enhancing e-learning and business performance at Jordanian telecommunications industry.

The major purpose of this research is studying the impact of artificial intelligence, big data analytics and business intelligence on transforming capability and digital transformation in Jordanian telecommunication firms. 303 samples were gathered after the sample checking process was completed. The PLS program was utilized in the research study to process all the collected data. The findings of the research demonstrate a set of relationships and linkages that can enhance transforming capability and digital transformation. Finally, this study found that artificial intelligence, big data analytics and business intelligence have good effects on developing and enhancing the transforming capability and digital transformation.