The effects of big data analytics and workplace pressures on productivity

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 impact of digital marketing, social media, and digital transformation on the development of digital leadership abilities and the enhancement of employee performance: A case study of the Amman Stock Exchange

This study seeks to analyze the impact of digital marketing, social media, and digital transformation on the development of digital leadership abilities and the resulting enhancement of employee performance. The research examines the complex connections between digital elements and their influence on organizational dynamics, using a case study done at the Amman Stock Exchange as a basis for analysis. The inquiry explores the impact of digital marketing strategies on leadership skills, the use of social media platforms to promote digital leadership, and the transforming influence of digital initiatives on employee performance. In addition, the study evaluates the interaction of these characteristics and their combined impact on organizational success. Evidence suggests that digital methods have a complex and wide-ranging effect on leadership and performance, including factors such as adaptation, communication, and strategic decision-making. The study highlights the capacity of companies, specifically within the framework of the Amman Stock Exchange, to utilize digital tools for the purpose of developing leadership skills and improving performance. The findings obtained from this study provide important insights for enhancing digital ecosystems in comparable organizational contexts, highlighting the importance of a thorough comprehension and strategic integration of digital components in order to attain long-lasting success

Utilizing business intelligence and digital transformation and leadership to enhance employee job satisfaction and business added value in greater Amman municipality

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 effect of groups’ reference, usefulness perception, and products quality on intention to buy and online shopping decision

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

New double stage ranked set sampling for estimating the population mean

In environmental and many other areas, the main focus of survey is to measureelements using an efficient and cost-effective sampling technique. One way to reach that isby using Ranked set sampling (RSS). RSS is an alternative sampling technique that canimprove the efficiency of estimators when measuring the variable of interest is eithercostly or time-consuming but ranking its elements in a small set is easy. The purpose of thisarticle is to introduce a new modification of RSS to estimate the mean of the targetpopulation. This proposed technique is a double-stage approach that combines median RSS(MRSS) and MiniMax RSS (MMRSS). The performance of the empirical mean and varianceestimators based on the proposed technique are compared with their counterparts inMMRSS, RSS and simple random sampling (SRS) via Monte Carlo simulation. Simulationresults revealed that this new modification is always more efficient than their counterpartsusing MMRSS and SRS, while it is more efficient than RSS is many cases especially when thedistribution is asymmetric

New double stage ranked set sampling for estimating the population mean

In environmental and many other areas, the main focus of survey is to measureelements using an efficient and cost-effective sampling technique. One way to reach that isby using Ranked set sampling (RSS). RSS is an alternative sampling technique that canimprove the efficiency of estimators when measuring the variable of interest is eithercostly or time-consuming but ranking its elements in a small set is easy. The purpose of thisarticle is to introduce a new modification of RSS to estimate the mean of the targetpopulation. This proposed technique is a double-stage approach that combines median RSS(MRSS) and MiniMax RSS (MMRSS). The performance of the empirical mean and varianceestimators based on the proposed technique are compared with their counterparts inMMRSS, RSS and simple random sampling (SRS) via Monte Carlo simulation. Simulationresults revealed that this new modification is always more efficient than their counterpartsusing MMRSS and SRS, while it is more efficient than RSS is many cases especially when thedistribution is asymmetric

E-marketing, EWOM, and social media influencers' effects on Intention to purchase and custom-er’s happiness at Amman Stock Exchange

The goal of this study was to measure the main effects of e-marketing, e-WOM, and social media influencers on increasing the intention to purchase and enhancing customers’ happiness in the Amman stock exchange. 285 samples represented the research study samples which have been collected, analyzed, and used to discuss the research hypotheses. The research study gave results which showed that e-marketing, e-WOM, and social media influencers’ effects positively on increasing customers’ intention to buy and enhancing customers’ satisfaction and happiness. This research represented each main research variable through its main keys, this research represented e-marketing through internet usage benefits received, simple use with low cost, and behavior and action. The second main variable is the e-WOM, and it is represented in this research through: satisfaction, dissatisfaction and perceived novelty. The third main variable is the social media influencers and it’s represented by: expertise, trustworthiness, and attractiveness. The main output of this study is represented that using digital marketing channels, with knowing peoples’ opinion, and following social media influencers can give customers ability to decide which product have to buy in the way which they can get the maximum benefits. The novelty of this study lies in giving more details about the effects of e-marketing, e-WOM, and social media influencers which are still new fields, and it needs more research for discovering all dimensions. Also, this research is useful and innovative based on choosing the field of this study and it is the Amman stock exchange which can help people to know useful information about the nature of stock investment

The usage of social media technology and customer relationship management in increasing innovation performance within the firm

This study discus the use of social media technology and it is contributes on improving the innovation performance for employees through the firm using social customer relationship management (CRM). Based on the literature in the strategic of management, marketing management, and information systems, the first main goal of this study is investigating and summarizing the capabilities of social media technology and customer relationship management. The second main goal is studying how the capabilities of CRM are affected by using social media technologies. This research chose the using of social media technology because of its effects on increasing and improving the capabilities and performance for employees in the case of the positive relation between developing the firm performance and the usage of customer relationship management performance. This study has been collected information and data from 15 organizations in Jordan by using the structural equation modelling approach

The effects of social media (Facebook, Twitter) on improving consumers behavior’s creating, contributing, and consuming

The strong competition between firms and the global pressures such as globalization are driving the business firms, and the role of social media (Facebook, Twitter) becomes effective as a marketing tool which gathered the firm with its consumers. The aim of this study is to make a deeply study about the relationship and the effects of social media (Facebook, Twitter) on consumer’s behaviours in the field of social media (Facebook, Twitter). The research study is represent a study which aim to investigate the relationship between social media (Facebook, Twitter) and how it effects positively on the enhancing the capabilities of consume behaviour. The main goal for this study is investigating and giving more information about how social media (Facebook, Twitter) represented by (Facebook, twitter) can effect on the behaviour of consumer which represented by (Creating, Contributing, and Consuming). Focusing on previous variables came from studying and clarifying the main effects of social media (Facebook, Twitter) in todays, and providing more information about tis effects on consumers. The research study collected all the needed information based on study interviews designed by Yes/No questions