Saudi Cultural Missions Theses & Dissertations
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Item Restricted IS THE CONCEPT OF BIG DATA RELEVANT IN SUPPLY CHAIN LOGISTICS? A REVIEW(Saudi Digital Library, 2023-11-30) Alharbi, Shaykhah; Marina, PapalexiIn this era of unprecedented digital data generation spanning the past two decades, the concept of Big Data (BD) has emerged as a powerful phenomenon. This paradigm shift extends to the healthcare sector, where a plethora of data originates from diverse sources, including electronic patient records and medical equipment. Despite the growing interest in applying big data analytics (BDA) to supply chain management (SCM) from both academia and industry, its exploration within the healthcare domain remains limited. Unlike its counterparts in business and manufacturing, the healthcare supply chain has yet to fully realize the potential of BDA, leading to performance disparities and the underutilization of best practices. In response, this review endeavors to delve into the existing literature concerning the application of big data in the healthcare supply chain, aiming to discern its pertinence. Through meticulous filtering, 56 primary studies were meticulously scrutinized and categorized from an initial pool of 5,626, in pursuit of addressing four key research inquiries. The findings underscore the transformative potential of big data within healthcare, with procurement, demand forecasting, inventory management, logistics, and quality assurance emerging as prominent applications. This potential is nurtured by a conducive environment shaped by various facilitating factors, although certain inhibitory elements are also evident. By offering a comprehensive analysis of the literature, this study not only highlights the focal points of ongoing research but also establishes a bridge between theoretical understanding and practical implementation. It serves as a foundation for future research endeavors, shedding light on pivotal areas and paving the way for a deeper comprehension of these domains in practice.22 0Item Restricted Factors Affecting Supply Chain Resilience in COVID-19 Pandemic.(Saudi Digital Library, 2023-12-06) Alqahtani, Amal; Hossein, SharifiThis study aims to explore the factors affecting SCR during the COVID-19 pandemic. The study adopted a qualitative research design and applied narrative analysis to evaluate secondary data. The study aimed to answer four key research questions using this methodology, i.e., the most sensitive area of the supply chain affected during the COVID-19 pandemic, suitable supply chain resilience strategies to manage similar events, such as pandemics in future, suitable supply chain risk management strategies to manage similar events, such as pandemics, in future and assessing how SCOR model be applied to implement agile supply chain management to enhance supply chain resilience and supply chain risk management in pandemics or similar crises. The study findings reveal that flexibility, adaptability, and awareness are significant factors affecting supply chain resilience, and the most suitable supply chain resilience-improving strategy is effective supply chain risk management. Supply chain risk management can be enhanced by integrating industry 4.0 waste technology, such as AI and blockchain, and these technologies are a must to map and model to establish an agile SC with a higher resilience level during disruptions and catastrophic event9 0Item Restricted How 4.0 Technologies Can Correct Behavioural/Cognitive Bias And Heuristics In Decision Making Within Scm And Om Areas(2022-09) Bashanfer, Hamza; beulen, ErikSupply chain management (SCM) and operation management (OM) have always triggered the need to establish a seamless system of information flow to achieve efficiency and accuracy. While the human resources have remained a significant aspect of the SCM and OM decisions, they have been found to be vulnerable to cognitive bias and heuristics which often affect how they execute critical supply chain needs. This dissertation sought to examine how I4.0 technologies can be used to mitigate the decision-making flaws expected from the human aspect of supply chain management. The study applied a qualitative study design and used purposive sampling to select nine primary and secondary sources of data. Textual analysis was applied to analyse the findings. The key findings of the study was that I4.0 technologies can be used to reduce cognitive bias and heuristics in SCM and OM decision-making because provide data used to justify the decisions reached. Unlike the human aspect of decision-making, I4.0 technologies such as big data corroborates crucial SCM and OM needs and aligns them with the desired outcomes. However, the study also established that it was impossible and not advisable to ignore the human aspect when making key decisions. The study demonstrated a key link between technology and how it can produce automated and reliable answers to key SCM and OM issues.23 0