The purpose of the present paper was to explore whether total quality management (TQM) mediated the influence of market orientation (MO) on organizational performance (OP). The study was conducted using a quantitative way of investigation with the help of the survey instrument as the primary tool for data collection. Firm ICT managers completed the survey, and the data collected was used to explore the pathways proposed. After having been collected, the data were screened using the SPSS 26 version, and the hypothesized correlations were tested using the same data. The results indicate that both MO and TQM had significant impacts on OP. Such a connection was also impacted by the implementation of TQM. The information and communication technology (ICT) industry is popular among developing countries and is considered as one of the most employers and tools that fasten economic progress. The results provide new insights into the relationships and impacts of MO and TQM on organizational performance to owners/managers, practitioners, and academicians in the ICT sector. The owners and managers can serve as the guidelines to make better decisions in implementing MO with TQM standards to outperform in all aspects and sustain market competition. The owners and managers are advised to develop better strategies to adopt MO and TQM plans into more effective and performance-oriented approaches. This study is the first to do empirical research on the connections between overall quality management, market orientation, and organizational performance in the ICT sector of an Arab developing country.

The study explores the combined influence of AI technology, supply chain collaboration, and information sharing on supply chain resilience. An integrated study model was developed and tested via smartPLS using a purposive sample of 542 respondents across different industries, to understand how information sharing mediates the collective impact of AI technology and collaborative practices on supply chain resilience. The experimental results demonstrate that AI technology paves the way for timely information and insights generation, which develops collaborative relationships among supply chain partners, facilitates trust and transparency, and thereby, information sharing to exchange pertinent data and insights across the supply chain network. The data were collected by surveying 542 managers from various industries and analyzed using SmartPLS. Relationships among technology adoption, supply chain collaboration, information sharing, and supply chain resilience were investigated. Structural equation modeling (SEM) was employed to observe the direct and mediating effects of information sharing between technology adoption, supply chain collaboration, and supply chain resilience. This study implies that practical information-sharing activities are essential for achieving supply chain resilience amid unpredictability and disturbances in solid market environments. It presents how technology adoption and supply chain collaboration are crucial to supply chain resilience. Information sharing, however, is shown to be an essential mediator, as clear communication and knowledge exchange amongst supply chain partners are fundamentally important in achieving supply chain resilience. Organizations need to invest in AI-driven technologies and develop collaborative ties with their supply chains to be resilient. This paper constitutes a valuable study of the primary drivers of supply chain resilience. It offers implications that organizations can use to persist and grow in the current ambiguous business setting.

The research aims to investigate the potential impact of Artificial Intelligence (AI) on the digital supply chain in light of extant literature on the Decision-Oriented Information (DOI) theory and the Technology-Oriented Enterprise (TOE) framework. The research further attempts to unpack the strategic implications of AI integration in supply chain management, and its association with operational excellence and business model innovation. The study is exploratory and employs a mixed-methods approach. We develop propositions that examine the decision-making processes within AI-enhanced supply chains based on an analysis of concepts central to the DOI theory. We also employ the TOE framework to develop further propositions regarding the technological infrastructure required for AI implementation. Empirical case studies encompassing AI applications in different industries (e.g. manufacturing, healthcare, and pharmaceuticals) are presented to gain a broad perspective of the impact of AI on the digital supply chain. AI technologies inherently make supply chains more agile, transparent, and responsive. Machine Learning algorithms allow for more accurate forecasting and demand management under conditions of supply chain risk and volatility. Robotics and automation, allow for greater flexibility and efficiency in executing operations and logistics. Additionally, the successful implementation of AI is heavily contingent on the organization’s current level of technological infrastructure and its alignment with its current and future business objectives. Furthermore, the DOI theory and TOE framework may serve as a blueprint for how one could evaluate AI implementation beyond the scope of supply chain management.

As supply networks become more complex and international, the task of controlling associated risks becomes more difficult. This article investigates the usefulness of risk alert technologies in supply chain management, with a focus on Big Data Analytics (BDA) and Artificial Intelligence (AI). The study investigates the impact of BDA capabilities, solid IT infrastructure, managerial views, and AI-apprehensions on the effectiveness of risk alert tools using a questionnaire-based survey of 420 managerial personnel and Structural Equation Modeling (SEM) via SMART PLS. The work proposes the concept of AI-Apprehensions as a moderating variable, which is a relatively unexplored field. According to the findings, while BDA capabilities and IT infrastructure considerably improve the effectiveness of risk alert tools, AI-apprehensions can negate these advantages. The study provides useful insights for policymakers and practitioners, emphasizing the importance of balancing technical and human components for effective risk management.

The paper aims to analyze the influence of the effectiveness of strategic decisions on organizational excellence, through employee empowerment, as an intermediate variable in Qatari commercial banks, where this study is quantitative and uses the descriptive cause-effect approach. The population of this study includes all directors, assistants, deputies, department managers, and branch managers in the six Qatari Commercial Banks, while the field survey method was used for this study. The population number was 336 participants from whom the researchers retrieved 270 questionnaires valid for statistical analysis. The study found that: the level of effectiveness of strategic decisions on organizational excellence and employee empowerment in Qatari commercial banks is high. The findings also showed that there was a significant effect of the effectiveness of strategic decisions on organizational excellence through employee empowerment as an intermediate variable. The study recommended the need for more studies to maintain the approach of the effectiveness of strategic decisions and employee empowerment in Qatari commercial banks, for their important role in organizational excellence, specifically giving freedom of action to employees to solve and encounter work problems.

Nowadays, the topic of preserving the environment and serving local communities is a hot issue. Hence, this study aims to explore how the green supply chain affects Jordan's pharmaceutical manufacturing industry's ability to compete globally. This study's research methodology is quantitative, descriptive, and cause-effect. Data was gathered from a sample of 124 managers selected randomly from a pool of 300 managers working in 10 out of 14 pharmaceutical manufacturing organizations. The study tool underwent evaluations for normality, validity, and reliability before the data were subjected to descriptive analysis and a correlation analysis was performed between variables. Finally, hypothesis testing was conducted through the application of multiple regression analysis. The findings show that green practices affect competitive strategy, where green operations were having the highest effect on competitive strategies, then green purchasing, and green selling, respectively. The study's conclusions show that the adoption of a green supply chain improves the competitiveness of the Jordanian pharmaceutical manufacturing sector. Accordingly, the study recommends that Jordanian pharmaceutical manufacturing companies should include green supply chain practices in their daily supply practices to increase the competitiveness of the organizations.

Digital transformation has emerged as a cornerstone of economic development, enhancing competitiveness and accelerating financial inclusion through technology-enabled systems. Fintech inclusion, in particular, is critical for broadening access to financial services and fostering industry growth through innovation. Drawing on growth theory and the principles of open innovation, this paper investigates the impact of digital transformation on Fintech inclusion and introduces inter-rationality as an organizational capability that shapes open innovation processes. While prior research underscores the importance of digital technologies and collaborative innovation, few empirical studies have examined these constructs within a unified analytical framework. Data were collected from 300 innovation managers, product development specialists, R&D directors, and senior executives from Fintech-enabled organizations. Hypothesized relationships were tested using Structural Equation Modeling via the PLS-SEM approach. Results indicate that digital transformation significantly increases Fintech inclusion (β = 0.366, p < 0.001), underscoring the role of robust digital infrastructures in enhancing the availability of technology-driven financial services. Entrepreneurial growth mechanisms similarly exhibit a substantial impact (β = 0.389, p < 0.001), confirming the importance of entrepreneurial renewal in financial innovation. Furthermore, open innovation dynamics positively influence Fintech inclusion (β = 0.412, p < 0.001), highlighting the value of cross-organizational collaboration in developing inclusive financial solutions. Inter-rationality, manifested through integrative thinking, cross-functional coordination, and collaborative decision-making, emerges as a potent moderator that amplifies the effects of digital transformation, growth, and open innovation on Fintech inclusion. This moderating role suggests that organizations with higher inter-rationality achieve greater alignment between digital capabilities and inclusive financial outcomes. The study offers strategic implications for managers, researchers, and policymakers. Firms are advised to invest in digital infrastructure, open innovation strategies, and cross-functional knowledge integration to advance Fintech inclusion. Policymakers can leverage these insights to cultivate enabling regulatory and technological environments that promote inclusive finance and innovation-driven economic development.

Nowadays, influencers play a crucial role in product and/or service promotion as well as in purchase intention and decision-making. Therefore, the present study aims to explore the effect of influencers on consumers' purchasing intention of Jordanian entrepreneurs' start-ups. The research paper uses a quantitative method, as well as the descriptive, cause-effect, and cross-sectional approaches has been used to actualize this study. The data was collected from 85 participants who were available and willing to answer the questionnaire by using a Google Form-based survey. The findings demonstrate that there is a significant influence of influencer marketing on purchase intentions, where Frequency / Consistency is rated the highest influence on purchase intentions, then content authenticity on purchase intentions, while the expertise of influencers shows no significance on purchase intentions. The contribution of this research was to clarify the influencer marketing effect on purchasing intentions and to identify whether content authenticity, expertise, and presence frequency could impact consumer-purchasing decisions. Finally, the study recommends investigating the effect of influencers' expertise to confirm or not the research results.

This research paper aims to test the effects of ChatGPT on students’ performance while using training to moderate this effect. The current paper uses a quantitative, descriptive, cause-effect approach. A cross-sectional sampling approach was used to collect the data online from 117 students in three Jordanian universities (Princess Sumaya University, University of Jordan, and German Jordanian University) by using a survey questionnaire. Data has been tested for its validity and reliability before testing hypotheses. The results indicated that the students agreed on the importance of ChatGPT (ease of use, accuracy, and plagiarism), however, most of the respondents did not agree on the importance of training on ChatGPT and they say it is easy and does not need training. The results also show that there are significant correlations among ChatGPT dimensions (ease of use, accuracy, and plagiarism). However, there is a significant correlation between training and plagiarism only, and there is an insignificance between training and both ease of use and accuracy, which supports the respondents' viewpoint that the training is not important. Finally, findings indicate that there is a significant strong correlation between all other variables (ease of Use, accuracy, and plagiarism) and students' performance, and a weak relationship with training. Finally, results show that there is a significant impact of ChatGPT (Accuracy, ease of use, and plagiarism) on students’ performance, where plagiarism has rated the highest significant effect, then accuracy, while ease of use has an insignificant effect. Moreover, results demonstrated that training has an insignificant moderation effect between ChatGPT and students’ performance.

The study aims to bridge this gap by examining how the credibility of information on SM influences educational decisions in higher education (HE) among students. The research questions addressed are: (1) how does SM information credibility influence education decision-making? (2) How often does informative information on SM have a kind with corresponding understanding from traditional sources to guide educational decisions? What difficulties are there in how students judge SM regarding the credibility of information? While social media (SM) has been argued to be an important stakeholder in our lives, its role in educational decision-making regarding information credibility is not explicated. This study, combining surveys and interviews in a mixed-methods approach, showed that providing authentic SM information appreciably increases students' ability to make an informed choice when choosing relevant courses, gain insight into possible learning aids, and assist them with their career plans. The findings highlight the importance of digital literacy for SM-content credibility evaluability in students. The study also outlined critical strategies for educators and institutions to support students in assessing the reliability of sources and train them in skills that accompany a responsible thumb online. The conclusion takeaway from the study is that credible information on SNS can impact and change educational decision-making.