This paper focuses on five-star hotels in Jordan to investigate the impact of influencer marketing on overall brand equity. The mediating role played by brand awareness and customer brand engagement between influencer marketing and overall brand equity is tested. The survey method is employed to conduct this research, and data is collected from 300 respondents. The proposed hypotheses are tested using structural equation modeling. The results indicate that influencer marketing directly influenced overall brand equity, brand awareness and customer brand engagement partially mediate the relationship between influencer marketing and overall brand equity.

In this paper, a homogeneous continuous time Markov chain (CTMC) is used to model information diffusion or dissemination, also to determine influencers on Twitter dynamically. The tweeting process can be modeled with a homogeneous CTMC since the properties of Markov chains are fulfilled. In this case, the tweets that are received by followers only depend on the tweets from the previous followers. Knowledge Discovery in Database (KDD) in Data Mining is used to be research methodology including pre-processing, data mining process using homogeneous CTMC, and post-processing to get the influencers using visualization that predicts the number of affected users. We assume the number of affected users follows a logarithmic function. Our study examines the Indonesian Twitter data users with tweets about covid19 vaccination resulted in dynamic influencer rankings over time. From these results, it can also be seen that the users with the highest number of followers are not necessarily the top influencer.

There are various reasons why vaccine fear has resulted in public rejection. Students have raised concerns about vaccine effectiveness, leading to hesitation when it comes to vaccination. Vaccination apprehension impacts students' perceptions, which has an impact on the acceptability of an e-learning platform. As a result, the goal of this study is to look at the post-acceptance of an e-learning platform using a conceptual model with several factors. Every variable makes a unique contribution to the e-learning platform's post-acceptance. In the current study, TAM variables were combined with additional external factors such as fear of vaccination, perceived routine use, perceived enjoyment, perceived critical mass, and self- efficacy, all of which are directly associated with post-acceptance of an e-learning platform. Here, a hybrid conceptual model was used to evaluate the newly widespread use of e-learning platforms in this area in this study in the UAE. In the past, empirical investigations primarily used Structural Equation Modeling (SEM) analysis; however, this study used a developing hybrid analysis approach that combines SEM with deep learning–based Artificial Neural Networks (ANN). This study also employed the Importance–Performance Map Analysis (IPMA) to determine the significance and performance of each element. Through the findings, it was found that fear of vaccination, perceived ease of use, perceived usefulness, perceived routine use, perceived enjoyment, perceived critical mass, and self-efficiency all had a significant impact on students' behavioral intention to use the e-learning platform for educational purposes. It was also shown in the analysis of ANN as well as IPMA that the perceived ease of use of the e-learning platform is the most important indicator of post-acceptance. The proposed model, in theory, provides appropriate explanations for the elements that influence post-acceptance of the e-learning platform in terms of internet service factors at the individual level. In the practical sense, these findings will help decision-makers and practitioners in higher education institutions identify the factors that should be given extra care and plan their policies accordingly. The ability of the deep ANN architecture to identify the non-linear relationships between the factors involved in the theoretical model has been determined in this research. The implication offers extensive information about taking effective steps to decrease the fear of vaccination among people and increase vaccination confidence among teachers and educators and students, consequently impacting society.

This study is to analyze the influence of the quality of information on the decision to choose CNNIndonesia.com media either directly or through the mediation of trust variables. The tremendous growth of cyber media in Indonesia, followed by the development of online media, has made people more careful in choosing online media. Meanwhile, the use and gratification theory states that the most important role of media is to meet people's needs and motivations, how certain media are sought and selected to meet their needs. This study uses a survey method through a quantitative approach positivistic. The sample was determined by an accidental sampling technique with a sample of 115 respondents. Data analysis was performed using Partial Least Square analysis with the SmartPLS version 3 program. The data analysis shows that the quality of information has a significant effect on increasing trust in CNNIndonesia.com media, the quality of information has a significant effect in increasing the decision to choose CNNIndonesia.com media, and trust has a significant effect in increasing the decision to choose CNNIndonesia.com media. This study also found that the trust variable was able to mediate the effect of information quality on the decision to choose CNNIndonesia.com media.

The aim of the research is to test the impact of big data on the quality of decision making. The necessary data was collected from telecommunication companies operating in Jordan. Three companies provide telecommunications services in Jordan: Zain, Umniah, and Orange. Non-probability purposive sampling was used. Hence, the study instrument was distributed to managers at the senior and middle levels of these companies. The structured equation modeling (SEM) technique was employed to test the study hypotheses. The results confirmed that big data impacts decision quality. Besides, it was determined that the highest impact was on velocity. The researchers suggest that Jordanian telecom companies invest in information technology that allows them to provide data with accuracy, reliability, and high quality, as well as improve the qualifications of their employees.

The study aimed at investigating the effect of e-HRM use on employee flexibility based on Davis’ technology acceptance model. Seven hypotheses were proposed. Two external factors (HR department role and organizational readiness) were linked to e-HRM perceived usefulness and e-HRM ease of use. These two factors linked to the behavioral intention to use e-HRM, which in turn connected to employee flexibility. All these propositions were accepted through analyzing data collected via a questionnaire from a sample consisting of managers and employees of human resource departments in Islamic banks in Jordan. The study contributes to the literature through clarifying and extending the technology acceptance model of e-HRM, as identifying two of the external factors that significantly affect e-HRM perceived usefulness and e-HRM ease of use, as well as, and spreading the model to include employee flexibility.

Today, the use of technology has made education more enjoyable. Vocabulary retention becomes a challenging task for both teachers and learners. They may learn the vocabulary but may not retain it. Yet, the use of web-based games may assist them in maintaining words known for short and long-term retention. The current study was conducted to identify students' abilities in retaining words learned after they were assigned to play a web-based vocabulary learning game, namely OnVac. Both short and long-term retention were measured after they were required to play the game as a treatment. Also, the study investigated students' perceptions about the system operation of OnVac. The use of quantitative research design, particularly quasi-experimental research and survey showed gains in vocabulary retention among students for short and long-term retention. The study also found that OnVac can support vocabulary learning among students in their learning of the specialized vocabulary. In terms of the system operation, the participants reported that the tool could assist them in learning engineering and technology words as it was convenient to use. The study provided implications to the teaching pedagogy in that teachers need to be wise and analytical in developing the online game to assist learners in learning English specialized vocabulary.

The aim of this study is to determine stakeholder acceptance of the blockchain and to investigate a suitable model using a Technology Acceptance Model with specific reference to corporate governance through cryptography in solving decades of financial record-keeping problems. Stakeholders in corporate governance, namely customers, creditors, suppliers, communities, employees, owners, investors, trade unions and social activists, can benefit in different ways. Investors can benefit from buying equity at a lower price and selling it on a market with greater liquidity, but they will find it difficult to disguise their trades. This study argues that almost all aspects of corporate governance can be improved through the application of this technology, which results in greater transparency, increases liquidity, and lowers costs. Corporate governance will also be better because blockchain technology uses the concept of a distributed ledger which allows data to be distributed at every connected point in an efficient and accountable manner, so that all parties in the blockchain can exchange data in real time.

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.

Virtual reality (VR) is a new technology that has applications in a variety of sectors, including medical, education, gaming, psychology, and sociology. The application of VR in education is intriguing and warrants further examination, but research on the subject is currently restricted. VR can benefit education by allowing students to participate in memorable and engaging experiences that they would not otherwise be able to have. Traditional approaches are still used to teach students, which is an essential element of the curriculum for those who want to conceive problem-solving. As a result, there is a scarcity of study on VR deployment. In this paper, we investigated the factors affecting the adoption of VR in higher educational institutes. To this end, we extended the technology Acceptance Model (TAM) with four additional factors and formulated a set of hypotheses. The hypotheses are then evaluated using a dataset collected from 503 Jordanian students. The result shows that the factors perceived facilitating condition, perceived effort expectancy, and perceived compatibility significantly affected the intention to use VR systems and tools for educational purposes. We believe that this study will help decision makers to build sustainable learning and educational systems in Jordan universities.