Establishing new relations with new customers and managing customers’ relations with the existing ones is important and considered challenges for each firm nowadays. Thus, studying and understanding different psychological factors like consumers’ emotions and happiness, motivates and attitudes are important while it helps in how to do more business with customers and push them to stay longer especially when adopting e-government mobile applications. This study used a quantitative research approach with survey data collection from different users of government mobile applications (GMA). The sample is around 340 from different backgrounds and levels of using different government services mobile apps. The results revealed the standardized regression and coefficients interpret the direct association between the study variables, hence confirmed the hypothesized model that included several factors such as perceived usefulness, perceived ease of use, perceived skills readiness, and perceived security toward attitudes to GMA and use of GMA effects on customer happiness and positive emotion. Moreover, the conclusion and implications confirmed the literature of this research field and elucidated most of the stated factors that significantly influence the customers’ emotion and happiness. For further study, research directions are given to expand the extant understanding of new different factors with other outcomes of mobile applications use.

The current study aimed to examine marketing cyber-security (DDoS Attacks, Cross-Site Scripting, SQL Attacks, and passwords attacks) in the digital age by presenting evidence from digital marketing platforms. Depending on the quantitative approach and utilizing a questionnaire as a tool, (133) marketing managers in digital marketing companies in Jordan responded to an online questionnaire. SPSS was used to screen and analyze the gathered data. Results of the study accepted the main hypothesis, and it appeared that marketing cyber-security has a statistically positive influence on marketing platforms, in addition to that, it appeared that the highest influence of sub-variables was for the benefit of Structured Query Language (SQL) Attacks explaining 35.8% of the variation. This result meant that SQL attacks-security does have a statistically positive influence on marketing platforms. This hypothesis could be tested through various methodologies, for example, surveys, interviews, focus groups, and/or experiments. The study recommended that marketers should use role-based access to limit the data employees can access and regularly review their permissions. Further recommendations were presented in the study.

Active Queue Management (AQM) techniques are crucial for managing packet transmission efficiently, maintaining network performance, and preventing congestion in routers. However, achieving these objectives demands precise traffic modeling and simulations in extreme and unstable conditions. The internet traffic has distinct characteristics, such as aggregation, burstiness, and correlation. This paper presents an innovative approach for modeling internet traffic, addressing the limitations of conventional modeling and conventional AQM methods' development, which are primarily designed to stabilize the network traffic. The proposed model leverages the power of multiple Markov Modulated Bernoulli Processes (MMBPs) to tackle the challenges of traffic modeling and AQM development. Multiple states with varying probabilities are used to model packet arrivals, thus capturing the burstiness inherent in internet traffic. Yet, the overall probability is maintained identical, irrespective of the number of states (one, two, or four), by solving linear equations with multiple variables. Random Early Detection (RED) was used as a case study method with different packet arrival probabilities based on MMBPs with one, two, and four states. The results showed that the proposed model influences the outcomes of AQM methods. Furthermore, it was found that RED might not effectively address network burstiness due to its relatively slow reaction time. As a result, it can be concluded that RED performs optimally only with a single-state model.

This research attempts to better understand how students in Saudi Arabia benefit from narrative and story aspects in gamified learning environments. Data from a sample of 500 persons with varying levels of education are analyzed using quantitative methods such as descriptive statistics, correlation analysis, and multiple regression analysis. The findings point to strong positive correlations between the use of gamification in education, the influence of storytelling, narrative variables, and the acquisition of new skills. There has been a significant shift toward the use of narrative variables as measures of mastery in gamified classrooms. This study's results show that using gamified learning with story elements may increase students' interest, motivation, and knowledge retention. Efforts are now being made by Saudi Arabia to update its educational system and provide its youth with the tools they'll need to succeed in the country's emerging knowledge-based economy. The use of game-based learning and narrative-rich experiences has promising results in this setting.

This study empirically examines the impact of strategic thinking on organizational excellence in Jordan's Information and Communication Technology (ICT) sector. Adopting a quantitative methodology, this study surveys a sample of 270 individuals drawn from various ICT companies across Jordan. Utilizing Structural Equation Modeling (SEM) with Partial Least Squares (PLS) for analysis, the study investigates the effects of different dimensions of strategic thinking on organizational excellence. The findings reveal that among the dimensions studied, dynamic and systematic thinking significantly and positively influenced organizational excellence. These results underscore the critical role that adaptive and methodical approaches to strategic thought play in enhancing organizational performance and competitiveness within the fast-paced ICT sector. The study not only contributes to the theoretical understanding of strategic thinking's relevance in organizational success but also offers practical insights for ICT companies aiming to achieve excellence in a dynamic business environment.

The rapid growth of electronic transactions has transformed the landscape of many industries, especially in the banking sector. This digitalization growth has brought about the need to understand the impact of the adoption of electronic banking in rural banks on the financial performance of rural banks in Indonesia. The aim of this research is to analyze the extent to which the adoption of e-banking influences consumer electronic trust (e-trust) and financial performance. The research method used is quantitative, involving data collection through questionnaires. Respondents in this study are managers of rural banks in West Java, Indonesia. The sample size used is 200 participants. Data collection took place over two months from May to June 2023. Data analysis was performed using Structural Equation Modeling (SEM) through SmartPLS 4 software. The research results indicate that the adoption of e-banking has a positive and significant impact on consumer e-trust and financial performance. Consumer e-trust has also been proven to mediate the relationship between e-banking adoption and financial performance. These findings provide profound insights into how e-banking plays a key role in building consumer e-trust and enhancing the financial performance of banking institutions. This research makes a significant contribution in the context of developing e-banking strategies in the banking sector. The implications of these findings can guide policies, strategies, and innovations in the banking sector to optimize the benefits of electronic banking, build consumer e-trust, and enhance financial performance in this digital era.

Time series data clusters are being researched thoroughly. The distance metric drives the development of the clustering time series. The ARIMA model is one of the models that can be employed in model-based clustering, although differing model selection criteria can lead to uncertainty in the model. In this investigation, we created a technique for ensemble distance-based time series data clustering. To express the distance between two series, five distances based on the five model selection criteria are utilized. The average of the five distances reflects the distance of two time series data. According to the simulation results, the ensemble distance method could boost clustering accuracy by more than 11%. Based on the pattern of rainfall levels, we applied our methods to find clusters of locations in the Province of West Java (Indonesia). The findings indicate that the rainfall pattern in the same cluster is similar. The cluster model is effective and feasible for representing individual models in a cluster.

The current research paper aims to pinpoint the determinants that impact consumers' perceived ease and perceived usefulness of digital wallet usage in Jordan. To accomplish this, the Technology Acceptance Model (TAM) has been used, which encompasses additional dimensions like the perceived risk of COVID-19, social influence, government support, promotional benefits, perceived value, and personal innovativeness. A quantitative research approach was employed in this paper; an online survey was applied to gather data from a total of 401 participants. The gathered data underwent analysis using a two-step PLS-SEM method. The study outcomes show that digital wallet users' perception of promotional benefits and perceived value significantly and positively affect the digital wallet's perceived usefulness. However, governmental support and social influence do not have a significant impact on digital wallets' perceived usefulness.

The English language for English Instructed Class students as the end-users of Higher Education is an integral part of the sustainability of globalization in Indonesia. The research investigates the relationship between brand image, price, web quality, and student satisfaction in conducting English-instructed classes. The data was obtained via an online inquiry form 105 respondents and analyzed using Partial Least Square (PLS). The findings show that the influence of the brand image on student satisfaction, price towards student satisfaction, and web quality on student satisfaction are significant. The results illustrate that English-instructed class students' happiness depends on how the institution creates the brand image, offers competitive tuition, and develops web quality to attract prospective English-instructed class students.

Higher education is currently facing a myriad of complex and diverse challenges. Increasing global competition, rapid developments in educational technology, and mounting pressures related to cost management and financing are factors that can significantly impact the higher education landscape. The aim of this research is to analyze the extent to which social media use can enhance organizational performance, ultimately influencing the organization's ability to foster innovation. This study employs a quantitative approach, collecting data through a questionnaire distributed to 205 respondents, consisting of faculty members working in private universities in Bandung, Indonesia. The questionnaire is designed using a 7-point Likert scale and distributed through an online survey platform. The research findings indicate that social media use has a positive and significant relationship with organizational performance and innovation performance in higher education. These findings are reinforced by the mediating role of organizational performance, explaining a significant portion of the positive influence of social media on innovation performance. The implications of these findings provide a foundation for universities to optimize the use of social media as a strategic tool in achieving performance goals and fostering innovation in the higher education environment.