This study investigated the relationship between the digital gap and the intention of Jordanians towards e-government usage. It focused on three components of the digital divide namely access, skills, and innovativeness. In addition, the research investigated how socio-demographic factors influence this connection. Data comprised 620 valid replies to questionnaires issued to 700 Jordanian citizens aged 22 and older who resided in urban and rural areas. Statistical Package for the Social Sciences (SPSS) version 26 and Analysis of Moment Structures (AMOS) version 24 were employed in data analyses and hypotheses testing. The results showed that all three aspects of the digital divide had a significant influence (access, skills, and innovativeness) on the intent of Jordanian citizens to utilize e-government, and the dimension of access imparted the strongest impact, followed by the dimension of skills and then the dimension of innovativeness. Additionally, it was discovered that gender, age, and education were the socio-demographic factors that could weaken the impact of the digital divide on the intentions of user to access e-government services. Contrariwise, the factor of income did not show a similar impact. Furthermore, perceived security significantly impacted the propensity towards e-government usage. Trust played a significant role in mediating the link between perceived security and the intention to engage in e-government.

The present study attempted to determine the elements affecting users' opinions about using electronic auctions in Jordan. The study's target audience was Jordanian university students. We randomly selected 600 students from three public universities in Jordan after 600 users from each of the three universities responded to the surveys. The primary data for this study were gathered using a specially created questionnaire that was based on earlier research. SEM software (smart PLS 4.0.8.3) was employed in the evaluation of data. This study looked into the factors that led Jordanians to use electronic auctions and found four indirect significant relationships and ten direct significant relationships. First, user attitudes and independent variables (usefulness, awareness, ease of use, and techno trust) are directly significant antecedents of utilizing e-auctions in Jordan. The use of e-auctions is related to the independent variable in five direct and significant ways: usefulness, awareness, ease of use, digital divide, and techno trust. Thirdly, there are direct and statistically significant correlations between user attitudes and the independent variables (usefulness, awareness, ease of use, and techno trust). Fourthly, there appears to be a clear and significant link between user attitudes and the intention to use e-auctions. Fifth, there are four mediated meaningful indirect correlations between the intention to use e-auctions and the independent variable. The findings of the current study are based on a number of factors that affect the demand for e-commerce in Jordan. They also include some recommendations for academics and decision-makers in e-marketing affairs. The current study also contributes in identifying challenges and suggestions that would overcome obstacles related to shopping operations through e-auctions. The factors examined in this study have been the subject of prior research. The data gathered in this study are valuable to Jordanian decision-makers and web developers, as the data can be used to create efficient policies and strategies to launch work on electronic auction platforms.

The present research endeavors to comprehend the determinants that impact the inclination to utilize financial technology within the context of Islamic banking clientele. The study undertakes an examination of various determinants that may exert an influence on the consumer's intention. These determinants encompass financial risk, legal risk, security risk, operational risk, consumer innovativeness, perceived ease of use, and perceived usefulness. The technology acceptance model is employed as the theoretical framework for the research. The requisite data for hypothesis testing is collected through the administration of an online survey to consumers of Islamic banks who possess a high degree of adaptability and proficiency in utilizing financial technology. The study employs the methodology of structural equation modelling with partial least squares to assess the proposed relationships among a sample of 399 participants. The results indicate that the acceptance of Islamic Financial technology services is contingent upon the perceived ease of use, perceived usefulness, and consumer innovativeness. In contrast, it is observed that various other factors, namely financial risk, legal risk, security risk, and operational risk, do not hold significant sway in shaping the level of acceptance of Islamic Financial technology among users of Islamic banking services. The concept of Technology Acceptance Model (TAM) is expanded within the realm of Islamic financial technology, and it is utilized to examine the impact of a novel factor, specifically consumer innovativeness. The untested nature of consumer innovativeness makes this paper a valuable resource for policymakers, academics, and researchers in the future.

IoT devices with weak security designs are a serious threat to organizations. They are the building blocks of Botnets, the platforms that launch organized attacks that are capable of shutting down an entire infrastructure. Researchers have been developing IDS solutions that can counter such threats, often by employing innovation from other disciplines like artificial intelligence and machine learning. One of the issues that may be encountered when machine learning is used is dataset purity. Since they are not captured from perfect environments, datasets may contain data that could affect the machine learning process, negatively. Algorithms already exist for such problems. Repeated Edited Nearest Neighbor (RENN), Encoding Length (Explore), and Decremental Reduction Optimization Procedure 5 (DROP5) algorithm can filter noises out of datasets. They also provide other benefits such as instance reduction which could help reduce larger Botnet datasets, without sacrificing their quality. Three datasets were chosen in this study to construct an IDS: IoTID20, N-BaIoT and MedBIoT. The filtering algorithms, RENN, Explore, and DROP5 were used on them to filter noise and reduce instances. Noise was also injected and filtered again to assess the resilience of these filters. Then feature optimizations were used to shrink the dataset features. Finally, machine learning was applied on the processed dataset and the resulting IDS was evaluated with the standard supervised learning metrics: Accuracy, Precision, Recall, Specificity, F-Score and G-Mean. Results showed that RENN and DROP5 filtering delivered excellent results. DROP5, in particular, managed to reduce the dataset substantially without sacrificing accuracy. However, when noise got injected, the DROP5 accuracy went down and could not keep up. Of the three dataset, N-BaIoT delivers the best accuracy overall across the learning techniques.

During Covid-19, organizations, particularly hospitals, encountered difficulties in providing services. Telemedicine has shown to be an alternative in service provision during these times. Based on this, acceptance of telemedicine in Jordanian public hospitals has become a very important issue to increase the attention of the health care organization toward it. A conceptual model was constructed based on previous literature. The model includes government policy, the capacity of external suppliers, and the capacity of the project team, top management support, as independent variables where their influence on the acceptance of telemedicine in Jordanian public hospitals as a dependent variable is examined. Respondents were chosen using a Purposive sampling technique. Questionnaires were delivered to 320 respondents using Google Forms. SEM was used for statistical analysis. The findings revealed that all the proposed factors including government policy, external supplier capacity, project team capacity, and top management support have a significant influence toward accepting telemedicine. The results of this study may aid Jordanian public hospitals in making the best use of the proposed factors to increase the acceptance of telemedicine in Jordanian public hospitals.

Technological advancements affect everyday life; they benefited our daily routines, habits, and activities. Underwater diving is one of the most interesting and attractive activities for tourists worldwide but could be risky and challenging. When paths are not clear, diving might take additional time and effort leading to some health problems. Thus, providing divers with proper direction information to surf underwater can be useful and helpful. Also, monitoring diverse health statuses and alerting them in case of any undesirable condition can increase their safety. Smart devices such as mobiles, watches, sensor devices, cellular networks along with the Internet of Things (IoT) can all provide location-based services. Such services can help in providing the best path for the divers and monitor their health status during diving. This paper proposes a new underwater routing approach, called Underwater Routing for Smart Diving “URSD”, which provides divers with routing information to visit underwater cultural or natural resources and monitors their health status during the diving period. The URSD approach was simulated and compared with the shortest path. Results showed that the URSD helped divers to route within paths that have a larger number of nodes, furthermore, it could enhance and improve divers experience and help them mitigate underwater risks.

The current manuscript aimed to explain the impact of big data on the financial reporting quality of the industrial sector in Jordan. To achieve the manuscript goals and validate hypotheses, a field study was conducted by distributing a questionnaire to 325 financial managers in industrial companies listed on the Amman Stock Exchange during a specific period. Gathered data were analyzed using structural equation modeling (SEM). The manuscript concluded that the big data dimensions, including variety, volume, and velocity, had a positive impact on financial reporting quality. Therefore, a set of recommendations were provided to managers of the industrial companies in Jordan to put in place an extensive data governance system to as-sure data quality, security, privacy, and compliance. To ensure the integrity and dependability of financial reporting, define data ownership, create data quality standards, and develop processes for data access, use, and preservation.

This study examined the perception of investors toward the factors of Artificial Intelligence (AI) that impact behavioral intention of AI adoption. TAM was used with the addition of three factors of subjective norms, trust in service and service provider, and training. Jordanian stock market investors with basic investment knowledge were selected as the study participants using a convenience sampling method. The analyzed data were obtained from 610 responses. Results demonstrated the significant impact of trust in service and subjective norms on AI. Attitudes, perceived ease of use and perceived usefulness showed statistical significance toward intention to use AI. Results also showed significant impact of training on perceived ease of use.

The study aimed to investigate the impact of creative thinking on marketing ideas and their influence on the structure of modern Jordanian advertisements for telecommunications companies. The methodology involved developing a survey instrument with four independent variables and one dependent variable. The independent variables were Creative Marketing (CM), Marketing Strategy (MS), Online Marketing (OM), and Social Media Marketing (SMM). The dependent variable was the Structure of the Modern Jordanian Advertisement (SMJA). The study population is customers of Jordanian telecommunications companies who reside in Jordan. A sample size of 270 respondents was selected through a convenience sampling method. The data were analyzed using statistical software, such as SPSS and AMOS 27 version, to test the research hypotheses. The results indicate that all four paths are statistically significant. The first hypothesis, which relates to creative marketing, has the highest estimated result of 0.62, while the second, third and the fourth hypotheses have estimated results of 0.152, 0.133, and 0.111, respectively. Overall, the results support the hypothesis that all four marketing domains have a significant impact on SMJA.

The purpose of the current research is to explore the impact of Instagram pages on consumers’ purchasing intentions among millennials in the fashion industry in Jordan. This study uses a quantitative, cause-effect, and cross-sectional approach. Online surveys were used to collect data from 212 respondents through different social media tools. The collected data was analyzed by SPSS software and Smart PLS to test the research hypothesis. Results show that bloggers’ recommendations significantly affect eWOM and engagement; usefulness information significantly affects eWOM and engagement; while trust insignificantly affects eWOM and engagement; brand familiarity insignificantly affects eWOM and engagement; participation and socialization insignificantly affect eWOM and engagement. Finally, useful information, eWOM, and engagement significantly affect consumers buying intention on Instagram. The study gives new information about the influence of Instagram pages on consumers' intentions. Therefore, this research expands the knowledge about factors that affect customers’ buying intentions. Since the study is a quantitative cross-sectional conducted on fashion industry Instagram users through an online survey in Jordan, which may limit its generalization to other industries and countries, therefore, the study suggests applying similar studies to online users of different ages, industries, and countries. Marketers can use Instagram to contact, promote, advertise, and sell their products by developing strong relationships with their customers through different social media tools. Using social media tools for marketing and selling reduces paperwork, printed advertisement, and transportation, which positively affects corporate social responsibility and reduces the consumption of energy and pollution.