The security of smart grids is seriously threatened by false data injection (FDI) attacks. Falsified data is maliciously injected into the grid's measurement and control systems as part of these attacks, which might seriously disrupt the power supply and jeopardize system integrity. In the context of smart grids, it is also imperative to address the issue of consumer privacy and the protection of their sensitive data. The main objective of this work is to provide a collaborative framework based on federated learning to detect various FDI dangers while protecting SG's resources and privacy. We have implemented several technologies that provide a good solution in order to accomplish this goal. Using a dataset designed to replicate attacks on the power system environment, we used federated learning to locally train models using the data stored on the sensors. The best model should then be chosen by comparing the outcomes. These outcomes demonstrate the potential of our framework, which has used mixed models to repel attacks, short-circuit faults, and maintain lines with a 98% accuracy rate during the federated learning phase.

This study aims to examine the factors affecting Jordanian Islamic banks’ customers’ adoption of electronic banks. The study relied on quantitative methods, where the study designed a questionnaire based on the Technology Acceptance Model (TAM) which derived from the Theory of Reasoned Action (TRA). The study sample consisted of 470 respondents. The study applied the Partial Least Squares Structural Equation Modeling (PLS-SEM), where the results of the Chi-square test and the standardized root mean square residual (SRMR) test showed the validity of the model for analysis. The results showed that usefulness, privacy, and awareness affect the adoption of e-banking, and that ease to use and electronic skills affect the adoption of e-banking through usefulness. The results also show that Infrastructure does not affect the adoption of e-banking, and Convenience does not affect the adoption of e-banking through Intention to use e-banking. The study advises Islamic banks to spread awareness about the importance of electronic banking and design easy-to-use electronic services that enjoy privacy and security.

This quantitative study examined the relationships between privacy, trust and level of service quality, and customer satisfaction. Jordanian firm employees involved in CRM technology were the study samples. Data from 620 completed questionnaires were analyzed utilizing AMOS software version 23. The study hypotheses were tested through Structural Equation Modelling (SEM). The causal relationships among the study’s main variables were examined as well. Results showed a positive impact of trust, privacy, and level of service quality on customer satisfaction. Managers and practitioners could pursue this study results in their CRM systems implementation. Additionally, the relations between privacy, trust and level of service quality, and customer satisfaction could be examined further as these relations in CRM systems have not been adequately examined, especially in emergent industries of developing countries.

This article will examine the impact of e-service quality management dimensions on decision-making agility at private universities in Jordan. The e-service quality model was extended by adding more dimensions and applying them in a pure service environment. The study used five dimensions to measure the impact of e-services quality management, including efficiency, fulfillment, privacy, responsiveness, and contact on decision-making agility. During the spring semester of 2021, an online questionnaire was distributed randomly at 12 private universities in Jordan. A total of 300 respondents completed and submitted the questionnaire. The results show that the five dimensions of e-service quality have a significant impact on decision-making agility at private universities in Jordan. The result indicates that contact was the most influential factor in decision-making agility. This confirms the importance of having advanced information technology systems and strategies to enhance communication effectiveness. University management can employ these results to enhance existing policies and procedures to improve the quality of e-services provided to boost and maintain competitiveness and distinction. We can anticipate that a university with a high level of decision-making agility can have a better change management cycle and be more flexible in response to market challenges.

The rapid digitalization in recent years has opened up many technological possibilities, gradually transforming various sectors and society as a whole. This digital shift has enabled advancements in a number of fields, leading to improved resource efficiency, systems and processes. The Internet of Things (IoT) refers to a system of interconnected devices that share information that exchange information with one another via the internet. IoT devices are now everywhere, found in applications ranging from unmanned aerial vehicles to smart home environments, from the Industrial Internet of Things to the Internet of Medical Things. The core concept of IoT revolves around establishing a seamless and intelligent communication ecosystem, facilitating interactions between devices over the internet. This is anticipated to create new opportunities for enhancing services in various societal sectors, such as transportation, farming and smart cities. However, IoT-based networks face limitations and challenges that hinder the realization of their full potential. This paper outlines these challenges and proposes solutions, emphasizing the importance of collaboration and innovation. The paper also anticipates future trends in IoT, particularly the integration of 5G connectivity, cloud computing and AI, and identifies areas for future research to address current challenges and explore new applications.

This paper addresses the conceptual exploration of various issues that form an integral part of the ethical dimensions surrounding the use of artificial intelligence (AI) in the field of marketing. We critically review some of the main ethical challenges AI poses to humanity: privacy, data security, bias, transparency, and accountability. Therefore, we will discuss the delicate balance between exploiting the transformation potential of AI for personally designed marketing strategies and ethical imperatives to safeguard the rights of consumers to retain trust. Then, the present regulatory landscape responding to these ethical challenges will be assessed by building on effective regulation, like the GDPR, existing proposed legislative frameworks, and industry guidelines. To underscore the role of an ongoing dialogue between marketers, technologists, ethicists, and regulators for developing a responsible AI ecosystem in marketing. Further, strategic recommendations for implementing company-based ethical AI marketing practices. The further strong guidelines provide enhancement transparency to consumers and investment in research to remove biases from algorithms. It also underscores principal scopes of further research and development, focusing on the need for new-age solutions to guide the ethical quagmires that AI-led marketing throws up. We suggest that integration should be done proactively and collaboratively. Thus, if attention is paid more to ethics and multidisciplinary dialogue, only such hyperbolic promises can be realized by AI-driven marketing. There are promises through which AI-driven marketing will meet business goals and be huge at societies' values.

This study investigates the factors that influence the sharing of information on social media platforms and examines the effects of perceived security, perceived privacy, and user awareness on users' trust in social media platforms, as well as the moderating effects of age, gender, educational attainment, and internet proficiency on information sharing. The study collected data from 837 social media users in Jordan and analyzed them using structural equation modeling (SEM), confirmatory factor analysis (CFA), and machine learning (ML) methods. The findings of the study indicate that perceived security, perceived privacy, and user awareness all have a significant impact on users' trust in social media platforms. Trust, in turn, has a significant impact on the amount of information shared on these platforms. Also, the findings of this study provide valuable insights into the dynamics of information sharing on social networks. This knowledge will be of interest to managers, policymakers, and developers of social media platforms. In addition, the findings of the study also have implications for the privacy and security of social media users. For example, social media users can be more careful about the information they share on social media platforms, and they can take steps to protect their privacy.

The Internet of Things (IoT) is an innovative technology that has the potential to help public hospitals better meet the demands of hospitalization. However, only a small portion of the research looked at patients' behavioural intentions (BI) to utilise IoT healthcare devices (IoTHD). This study intends to investigate the variables that influence the BI's use of IoTHD. The research suggests that the BI may be explained by factors of UTATU. The patients of public hospitals make up the population. A questionnaire was used to obtain the data using convenience sampling. Participants in this research totalled 161. Smart Partial Least Square results demonstrated that social influence (SI) has an impact on performance expectancy (PE). Technological complexity (TC) and playfulness (PP) had an impact on effort expectancy (EE). Additionally, the BI to adopt IoTHD was impacted by PE, EE, perceived security (PS), and perceived privacy (PV). The impact of PE and EE on BI to use IoTHD was not moderated by the facilitating conditions (FC). In order to improve patients' perceptions of IoTHD usage in public health organisations, simple process and more positive word of mouth is required.