The primary objective of this article is to present the findings of an experimental study on the use of a human-like “naturalistic” avatar (of both genders) for information presentations. The primary goal is to investigate how users' frame of mind, purchasing behavior, and satisfaction are affected by being presented with information by a naturalistic avatar that lacks expressive capabilities. Two different types of information presentations were developed and empirically tested on 48 participants, namely: (i) two dimensional static graphical and textual information presentation and (ii) non-expressive naturalistic avatar. For this comparative research study, a simplified version of the user experience model that was used in our earlier research (the EUX-DM) was selected to serve as the measurement model. Participants' perceived values of the measured qualities were found to be independent of both their own and the naturalistic avatar's gender, and the non-expressive avatar had a positive effect and a stronger encouragement on participants' intention to purchase, usage attitude, and satisfaction than other types of information presentations.

The current study aims at examining the differences between umbrella branding and house of brands on organizational market share. Various variables are adopted including reach, efficiency, image and ambiguity. A sample of 98 marketing managers or their representatives within the chemical industry sector in Jordan, SPSS is employed to screen and analyze gathered data. Results of study indicate that umbrella branding has a bigger and much deeper influence on market share compared to house of brands which is attributed to many factors including that umbrella branding has a wider reach, it is more efficient and more able to shed the light and increase the focus on organization's image, meaning that in umbrella marketing the focus is more on the marketing organization more than manufacturing organization which increases its reputation and market share. The study recommends the necessity for each brand to have a specific purpose to avoid overlapping or disintegration of brands.

The purpose of this study is to identify the key macroeconomic variables that affected stock price fluctuations in Amman Stock Exchange during the period 1980-2018. Using Augmented Dickey-fuller (ADF) test, it was found that the variables did not have the same degree of integration. According to Breusch-Pagan-Godfrey test, the residuals violated the constant variance assumption under Ordinary Least Square (OLS) model. Therefore, the study employed Generalized Autoregressive Conditional Heteroskedasticity (GARCH) methodology to analyze the model after taking the first difference of natural logarithm for all variables to be stationary at the same level and to show the fluctuation in the variables. It was found that fluctuations in portfolio investment and in industrial production index are statically significant to lead fluctuations in the stock price index in Amman Stock Exchange and they follow the same direction, whereas fluctuations in real effective exchange rate, real interest rate, and Brent crude oil prices were statically significant to lead fluctuations in the stock price index but in the opposite direction.

The study examines the technological factors influencing the adoption of artificial intelligence (AI) technology. In addition, this study examines the mediating role of accounting automation on AI adoption in a small and medium-sized enterprise (SMEs) context. The owners and managers of SMEs were surveyed online using a convenience sampling technique. The proposed model was tested using SEM. The findings confirmed the relationships between the predictive variables and AI adoption. The results showed that accounting automation partially mediated the relationship between predictive variables and the adoption of AI. The results contribute to the TOE model by incorporating accounting automation into the TOE framework as a mediating variable. The study also contributed to the literature by including new variables in the model, such as saving time and efficiency-improving.

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.

It is argued that excessive social media use can lead to an addiction. This study compares two proposed research models. The first model examines how social media addiction, narcissism, and self-esteem affect tourism addiction. Whilst the second model studies the impact of narcissism and self-esteem on social media and tourist addiction. There were also two research models proposed here. Data collection was obtained in Jakarta, with 214 participants chosen by using the convenient sampling method. Exploratory factor analysis and structural equation models were used to process the data. Social media addiction and narcissism affect self-esteem, while social media addiction and tourist addiction affect self-esteem. This research combines the study of addiction, modern media, and cyber marketing.

The purpose of this study is to determine the impact of cloud-based solutions on the digital transformation of human resource (HR) practices in Jordan. The study is quantitative in nature and the data was gathered from primary sources by gathering the responses from 346 respondents. The SEM technique was used for the purpose of determining the direct effect. The study found that infrastructure as a service, performance as a service and software as a service had significant and positive impact on the digital transformation of the HR practices. The information gathered from the secondary sources was provided with reference and was also well paraphrased to avoid the issue of similarity. The study focused on the public sector which restricts the results of this study to this sector only. On the other hand, only one country was considered in this study i.e., Jordan. The research is considered as the first attempt to examine the impact of cloud-based solutions on the digital transformation of HR practices in a developing country such as Jordan.

Of all the current challenges faced by Jordan, the most severe is the inadequacy of the water supply. The country is almost entirely reliant on rainfall, whose pattern, however, is highly variable in terms of its frequency, regularity, and quantity. Evidently, therefore, the ability to anticipate rainfall accurately is critically important for the effective planning and management of water resources in Jordan, and particularly in agricultural areas. Influenced by a range of factors such as temperature, relative humidity, and wind speed, rainfall is a stochastic process. This paper suggests the use of a fuzzy model that draws upon data gathered at 26 stations situated in a range of locations throughout Jordan. The model is capable of forecasting seasonal rainfall relating to a specific station. Its ability to deliver predictions with an acceptable degree of accuracy has been demonstrated, and it can be concluded from this that the fuzzy technique can provide a model that is capable of efficiently forecasting seasonal rainfall.

In this study, (72) financial managers and managers of the accounting department within the pharmaceutical industry in Jordan during the fiscal year 2019-2020 were exposed to a questionnaire in order to examine the influence of AIS applications on the outcomes of accounting corporate governance. Researcher adopted accounting governance variables from different studies and included Control, Commitment to Accounting Standards, Performance Evaluation and Add Confidence and Credibility to the survey. Results of study indicated an influence of all given variables of accounting governance on the outcomes of corporate governance which is attributed to the quality of accounting information and making sure that all information given are based on the standards of accounting. Some recommendations were presented with the study later on.

The study aimed to identify the impact of the credit query in reducing credit risks from the viewpoint of workers in Jordanian banks, and to achieve the goal of the study, the researchers adopted the descriptive analytical approach, where a questionnaire is designed and distributed to a sample of (176) individuals within the upper and middle administrative levels in Jordanian banks. The study reached a set of results, the most important of which is the existence of a negative correlation between the level of use of the credit query system and each of the financial, administrative and legal credit risks, in addition a statistically significant effect of using the credit query system in reducing the financial, administrative and legal credit risks. The study recommended that Jordanian banks should continue to use the credit system because of its positive effects on the efficiency and effectiveness of granting credit to business organizations or individuals alike.