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.

The purpose of this research is to investigate the impact of total JIT practices (JIT purchasing, JIT operations, and JIT selling) on operational performance (quality, delivery, and cost) of local fast-food restaurants in Jordan. The study is quantitative and covers 43 out of 142 local fast-food restaurants in Amman. Data were collected by questionnaires from 101 managers and supervisors. After confirming normality, validity, reliability, and relationships between variables, multiple regressions were conducted to test the hypothesis. Results indicate that there are strong relationships among total JIT sub-variables, very strong relationships among operational performance dimensions, and a very strong relationship between JIT and operational performance. Finally, results show that total JIT practices have a positive significant effect on the operational performance of Jordanian local fast-food restaurants.

The purpose of this study is to investigate the moderating role of digital marketing strategies on innovation through Artificial Intelligence (AI) mediating impact in Small and Medium Enterprises within Saudi Arabia. Advanced analytics tools analyzed data from KSA SMEs to establish the role of AI, customer behavior, and experiences in product and process innovation. Artificial intelligence boosts product and process innovation with unconventional customer knowledge. Integrating AI combined with digital marketing to improve decisions and efficiency, to increase understanding of customer dynamics for sustaining growth and promoting collaborations. Using AI-empowered digital marketing strengthens Saudi SMEs advancement by promptly reacting to market motions. Sustainability practices attract the environmentally conscious consumer. This research provides actionable insights for SMEs who want to employ digital marketing and AI strategies and contribute to building an economic environment in Saudi Arabia.

This study explores the factors affecting CliQ payment service adoption in Jordan as it represents a major shift in the Jordanian market to Fintech and mobile marketing. This study presented a distinctive model by integrating the “unified theory of acceptance” and the “technology acceptance model” TAM with the “use of technology UTAUT” to measure the behavioral intention of consumers and the satisfaction of the users towards utilizing the CliQ service. The study measured the linkage between four predictors (perceived usefulness, social influence, perceived ease of use, and financial risk) as well as both utilizers’ intention to CliQ service usage and utilizers’ satisfaction with using the service, along with observing the association between these predictors to determine their contribution to the users’ satisfaction mediated by the users’ intention to utilize the service mentioned above. A survey instrument was distributed to 604 respondents, and it was developed and validated by academics, as a pilot test. As well as a pre-test. Hypotheses were tested with multiple linear regression analysis using SmartPLS software to interpret path coefficients, and reliability and validity within the outer model were tested through correlation analysis. Additionally, internal consistency was explored by applying Cronbach’s alpha. The outcomes proved that the predictors significantly affect both utilizers’ behavioral attitudes and satisfaction with using the CliQ service, except for financial risk. The data analysis also indicated a significant indirect influence of all the independent variables on utilizers’ satisfaction through behavioral intention to utilize the CliQ service, except for financial risk, which had an insignificant indirect influence on utilizers’ satisfaction through behavioral intention for service usage. The findings of the current article close the gap found in the literature concerning measuring usability to enhance user satisfaction and adoption of Fintech services. Therefore, bank managers and policy planners can find insights for developing and improving mobile banking apps.

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.