This research investigated how data privacy practices may impact reverse logistics in the automotive engineering sector, particularly by examining whether environmental efficiency plays a mediating role. This research uses the Resource-Based View (RBV) and Dynamic Capabilities Theory (DCT) to understand how data privacy-driven processes support environmental practices and reverse logistics optimization. Primary research is done through structured questionnaires of automotive engineering professionals. The partial least squares structural equation modeling (PLS-SEM) approach tested the relationships amongst data privacy, environmental efficiency, and reverse logistics. However, the results further clarify how key intermediate outcomes, after all, improved environmental efficiency, affected by robust data privacy practices, may enhance reverse logistics processes. The nexus of data privacy and environmental efficiency highlights the critical need to embed respect for private sector information into logistics strategies that achieve superior business performance and also protect corporate sustainability. The findings suggested that environmental consequences must be considered in the flexibility of data-privacy measures with important strategic implications for firms operating in a complex and more environmentally conscious market. This study makes a novel contribution to the extant literature by empirically detecting how environmental efficiency mediates data privacy practices and reverse logistics. These findings will be useful for industry practitioners to use data privacy to enable sustainable logistics management of business operations within automotive engineering.

This paper aims to explore the influence of digital supply chain flexibility in five-star Hotels on smart quality systems together with its mediating effect through sustainable procurement practices within KSA. The methodology used is quantitative, based on data collected from a sample of five-star Hotels in KSA. Based on the above findings, this study argues about an integral part of DSCF (Digital Supply Chain Flexibility), SP and SQS for adopting theoretical framework. In this study, partial least squares-structural equation modelling (PLS-SEM) was used to validate the hypotheses. Digital supply chain flexibility has a significant positive relationship with sustainable procurement practices and smart quality systems in five-star Hotels. This means that actions such as fostering sustainable procurement practices could act on the ability of digital supply chain flexibility to boost smart quality systems, which play a role in enhancing operational efficiency and service quality. This paper contributes to the examination of various strategies for digital supply chains with sustainable procurement practices and creative quality systems within the hospitality sector; particularly focusing on KSA. Although the research findings are constrained to five-star Hotels from KSA they offer important directions for future research in different hospitality settings. These results provide practical information for hotels managers and policymakers on how digital supply chain flexibility, and sustainable procurement practices combined would contribute to the high-quality service provision as well as operational resilience of five-star Hotels. While these lessons have been drawn from the KSA market, they are also relevant to other hospitality markets with hospitality markets worldwide. This is the first study to examine Mediating Role of Sustainable Procurement and Digital Supply Chain Flexibility Impact on Smart Quality Systems Study in Five-Star Hospitals in KSA.

The aim of this study is to investigate the influence of logistics and distribution processes on business process reengineering by adopting green innovation for sustainable transformation. Guided by the Resource-Based View (RBV), the study examines logistics and distribution processes in relation to business process reengineering (BPR), through green innovation adoption, towards achieving sustainability goals. Drawing on a conceptual framework based in supply chain management and BPR theories, the study uses Structural Equation Modeling-Partial Least Squares to analyze data collected from respondents within the target industries. The results show that streamlined logistics and distribution processes help to ensure the success of Green Innovation as part of BPR, strengthening the trend towards sustainable transformation. The study accentuates the importance of logistics management in enabling environmental stewardship and enhanced operational efficiency, providing some key ideas for improving both theoretical developments and future directions as well on practice ground to adopt sustainable supply chain trends.

This research study investigates the feasibility of applying supply chain finance (SCF) in both small and medium enterprises (SMEs) in the Jordanian marketplace. It focuses on patterns of collaboration, factors of adoption, and challenges, tracing the significance of custom-tailored SCFs that specifically involve technological restrictions and governmental complications. Applying a mixed methodology of interviews and AMOS analysis that aims at collecting reliable data from financial and inventory managers in Jordan, this research indicates that the most considerable elements in developing supply chain finance in Jordan are credibility and sustainability. Guaranteeing fair access to funds and contentious innovation has proven to be a complete policy. Moreover, the results conclude that balancing regulatory support is related to simplicity, collaboration, and endorsement of worldwide access to technology. For further research within the same domain, this research recommends developing a customized SCF program and emerging inclusive policies that can pave the way for future research as a comparative analysis of diverse businesses and the study of its permanent effect, devising the integration of technology strategies and mentoring the effectiveness of financial policies.

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 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.

This research examines the synergistic influence of inventory competition, artificial intelligence (AI) adoption, and digital marketing intensity on quality improvement decisions within contemporary supply chains. With a focus on enhancing product and service quality, we investigate the intricate relationships among these variables. A quantitative approach involving 380 supply chain professionals reveals that heightened inventory competition, increased AI adoption, and robust digital marketing significantly contribute to quality enhancement initiatives. The study builds upon prior research by empirically validating these connections and offers practical insights for supply chain practitioners. The findings underscore the strategic imperative of organizations to strategically balance these factors to optimize their quality management strategies, fostering customer satisfaction and competitiveness. While offering valuable contributions, the study acknowledges limitations in terms of self-reported data and a specific respondent group. Future research could extend this investigation to diverse industries and geographical contexts. In the end, this study sheds light on the complex interplay that exists between inventory competition, the use of AI, digital marketing, and judgments about quality improvement. As a result, a road map has been provided for efficient quality management of supply chains in the digital age.

The global supply networks have been disrupted and weak connections exposed to an extent that few people have ever seen in their lifetime due to the COVID-19 epidemic. As a result of the severity of the crisis, every country and industry is feeling the effects, and the massive shifts in demand and supply that have happened throughout the epidemic are easily distinguishable from the effects of previous crises. We looked into the adaptability of alliance management and AI-driven supply chain analytics in the context of an ever-changing external environment. We examined four hypotheses in this area using survey data from the American auto components manufacturing industry. To do the analysis, we used Smart PLS. Alliance management capabilities, mediated by AI-powered supply chain analytics capacity, have been found to increase an organization's operational and financial performance. We also discovered, with environmental dynamics as a moderating factor, that alliance management capability has a substantial impact on AI-powered supply chain analytics capabilities. Based on our findings, we have a deep appreciation for the interplay between dynamic capacities and the relational view of organization. Finally, we pointed up the limitations of our study and offered a number of directions for future investigation that might help address some of the concerns that our results raise.

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.