This paper examined technology information as the factor that drives productivity among Small and Medium Enterprises (SMEs), particularly the effect of innovation on the performance of SMEs and the effect of Customer Relationship Management (CRM) Technology on industrial performance. The mediation of CRM Technology on the effect of innovation on company performance was examined as well. Survey questionnaire was distributed online to 544 firms, and data were analyzed through structural equation models using Amos version 23. Results show that innovation increases productivity (performance) of small businesses and plays a positive role on information systems. However, innovation had an insignificant role on industrial Performance. Meanwhile, CRM Technology shows no mediation in the relationship between innovation and performance. Generally, results proved the significance of innovation in enhancing company performance.

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.

The study aimed to define the contribution of total quality management in relations with suppliers and customers in Jordanian pharmaceutical companies. The study population consisted of pharmaceutical companies in Jordan targeting individuals in supervisory positions in these companies. A total of 170 responses were received. The results of the study found that Jordanian pharmaceutical companies apply total quality management in terms of “commitment of senior management, employee empowerment, strategic planning for quality”, which had positive relationships with suppliers and customers. It indicates that total quality management and supply chain practices, especially the relationship with suppliers and customers, are among the basic concepts that work to improve supply chain performance. The study recommends devoting the necessary attention and care to empowering workers, and this is where the essential role-play for senior management is to create interest among employees in their work and jobs through training programs. However, developing methods of collective motivation, participating in setting goals, making decisions, and displaying the image of the work “Family” and forming problem-solving teams for the purpose of achieving empowerment is also important.

The aim of this study is to explore the impact of intellectual capital on the achievement of competitive advantage in organizations. It also aims to explore the mediating impact of innovation on the relationship between intellectual capital and the achievement of competitive advantage. To meet the study’s goals, the researchers reviewed the relevant literature. The researchers also provide definitions for intellectual capital and innovation. They also identified the dimensions of intellectual capital (i.e. structural, human and relational capital). The study identified the types of innovation (incremental and radical innovation) and found that intellectual capital significantly influences on the achievement of competitive advantage. Moreover, the study found that innovation has a mediating influence on the relationship between intellectual capital and the achievement of a competitive advantage.

The present study evaluated the relationships between IT application and KM practice adoption, and project performance. KM practice adoption as a mediator in the relationship between IT application and project performance, was ascertained. A research model was constructed and validated utilizing structural equation modeling (SEM). Results of analyses demonstrated a positive relationship between IT application levels and knowledge management levels of projects. Also, high-level knowledge management contributes to project outcomes. Full mediation of KM practice adoption on the effects of IT application on project performance was affirmed.

The increasing popularity of intelligence systems in accounting and auditing domains has led to the interest towards drivers of blockchain technology adoption. Consequently, this empirical study inspected the antecedent constructs with direct and indirect impact on blockchain technology adoption in the accounting domain. Data were gathered from 346 accountants employed in Information technology (IT) companies, through an online survey. Structural equation modeling with Smart PLS 4 was employed for research model testing. Out of thirteen proposed direct hypotheses, twelve were accepted. Mainly, the obtained empirical results confirmed effort expectancy impacting blockchain technology adoption the most. Furthermore, the obtained results also confirmed the mediation role of effort expectancy and performance expectancy.

This qualitative study examined the impact of social media characteristics on the attitude of users toward the use of e-services by the Department of Lands and Survey. The study population comprised users of Department of Lands and Survey e-service, while the study sample comprised 407 users. Data from respondents were analyzed using SEM run using Amos (23). Results showed reliability, security, website design, ease of use, awareness, and digital divide as direct significant antecedents of user attitude toward the use of e-services from the Department of Lands and Survey. Also, all antecedents showed direct significant relationships with user attitude. Results showed a direct significant relationship between user attitude and the use of e-services from the Department of Lands and Survey. Through mediation of user attitude, five indirect significant relationships between the antecedents and the use of e-services from the Department of Lands and Survey were found. The inclusion of new antecedents such as privacy and site content may enhance the understanding of how users use e-services provided by the Department of Lands and Survey.

This research investigates the adoption of Information and Communication Technology (ICT) by Micro, Small, and Medium-Sized Corporations (MSMEs) in Jordan. The research formulates and examines hypotheses on factors affecting ICT adoption morals via the Unified Theory of Acceptance and Use of Technology (UTAUT) and the Technology Acceptance Model (TAM). The suggested concept, which utilizes Structural Equation Modelling (ESM), highlights the critical responsibilities that social influence and perceived utility play in affecting choices to adopt ICT. It is noteworthy that MSMEs confront a multiple of obstacles when it comes to adopting ICT, encompassing restrictions in terms of infrastructure and resources, shortages of human capital, and hardships in the technology environment. Data were gathered from 305 MSMEs, and outcomes shed light on important factors to boost the impact of ICT integration in the special setting of Jordanian MSMEs.

This research uses Technology Acceptance Model to explore the elements influencing students' attitudes toward using Chat Generative Pre-Trained Transformer (ChatGPT), a recently developed artificial intelligence (AI) tool, for learning and educational purposes. Using Amos version 23 structural equation modelling and 880 student survey responses, the suggested model was empirically tested. According to the report, students think well of ChatGPT utilization in the classroom. Credibility, Usefulness and ease of use, all influence how positively people feel about using this technology in a classroom setting. The study's findings, however, did not support the notion that students' adoption and use of ChatGPT was insignificantly influenced by perceived enjoyment. Moreover, the results conclude that attitude mediates the relationship between usefulness and intention to use ChatGPT. The research will help businesses, educational institutions, and the global community by providing insight into how students view the ChatGPT service within a learning environment. Additionally, the application boosts learners' confidence and interest, which improves general awareness and literacy. Finally, the research will facilitate developers of AI in the betterment of their product and service delivery and regulators in regulating the use of AI-based bots. Owing to its recentness, there is not much study currently available on ChatGPT use in education. This research adds significantly to the extant knowledge on the adoption of advanced education technologies by examining the adoption characteristics of ChatGPT, a novel AI-based tool involving students. Additionally, there is a dearth of research in the literature on students' adoption of ChatGPT for educational purposes. Such a gap was filled as this study identified the factors affecting students' adoption of ChatGPT in the classroom.

Education is a fundamental sector in all countries, where in some countries students com-pete to get an educational grant due to its high cost. The incorporation of artificial intelli-gence in education holds great promise for the advancement of educational systems and pro-cesses. Educational data mining involves the analysis of data generated within educational environments to extract valuable insights into student performance and other factors that enhance teaching and learning. This paper aims to analyze the factors influencing students' performance and consequently, assist granting organizations in selecting suitable students in the Arab region (Jordan as a use case). The problem was addressed using a rule-based tech-nique to facilitate the utilization and implementation of a decision support system. To this end, three classical rule induction algorithms, namely PART, JRip, and RIDOR, were em-ployed. The data utilized in this study was collected from undergraduate students at the University of Jordan from 2010 to 2020. The constructed models were evaluated based on metrics such as accuracy, recall, precision, and f1-score. The findings indicate that the JRip algorithm outperformed PART and RIDOR in most of the datasets based on f1-score metric. The interpreted decision rules of the best models reveal that both features; the average study years and high school averages play vital roles in deciding which students should receive scholarships. The paper concludes with several suggested implications to support and en-hance the decision-making process of granting agencies in the realm of higher education.