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Dissertations / Theses on the topic 'Predictive Analytics in Supply Chain'

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Published: 7 June 2025
Last updated: 2 August 2025

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1

Schmidt, Rachel Marie S. M. Sloan School of Management. "Using predictive analytics to address risk in complex supply chains." Thesis, Massachusetts Institute of Technology, 2018. http://hdl.handle.net/1721.1/117964.

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Thesis: M.B.A., Massachusetts Institute of Technology, Sloan School of Management, in conjunction with the Leaders for Global Operations Program at MIT, 2018.<br>Thesis: S.M., Massachusetts Institute of Technology, Department of Mechanical Engineering, in conjunction with the Leaders for Global Operations Program at MIT, 2018.<br>Cataloged from PDF version of thesis.<br>Includes bibliographical references (pages 68-69).<br>Li & Fung (LF) is a global supply chain manager for consumer product brands and retailers. Worldwide, LF contracts with over 13,000 factories. Frequently, these factories ex
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2

Rodriguez, Pellière Lineth Arelys. "A qualitative analysis to investigate the enablers of big data analytics that impacts sustainable supply chain." Thesis, Ecole centrale de Nantes, 2019. http://www.theses.fr/2019ECDN0019/document.

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Les académiques et les professionnels ont déjà montré que le Big Data et l'analyse prédictive, également connus dans la littérature sous le nom de BDPA, peuvent jouer un rôle fondamental dans la transformation et l'amélioration des fonctions de l'analyse de la chaîne d'approvisionnement durable (SSCA). Cependant, les connaissances sur la meilleure manière d'utiliser la BDPA pour augmenter simultanément les performances sociales, environnementale et financière. Par conséquent, avec les connaissances tirées de la littérature sur la SSCA, il semble que les entreprises peinent encore à mettre en o
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Faber, Andreas D. [Verfasser], Stefan [Gutachter] Spinler, and Arnd [Gutachter] Huchzermeier. "Data analytics in supply chain planning : applications in intermittent demand forecasting, partial defection prediction and price discrimination / Andreas D. Faber ; Gutachter: Stefan Spinler, Arnd Huchzermeier." Vallendar : WHU - Otto Beisheim School of Management, 2021. http://d-nb.info/1240764359/34.

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4

Bohle, Alexander, and Liam Johnson. "Supply Chain Analytics implications for designing Supply Chain Networks : Linking Descriptive Analytics to operational Supply Chain Analytics applications to derive strategic Supply Chain Network Decisions." Thesis, Internationella Handelshögskolan, Högskolan i Jönköping, IHH, Centre of Logistics and Supply Chain Management (CeLS), 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:hj:diva-44120.

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Today’s dynamic and increasingly competitive market had expanded complexities for global businesses pressuring companies to start leveraging on Big Data solutions in order to sustain the global competitions by becoming more data-driven in managing their supply chains.The main purpose of this study is twofold, 1) to explore the implications of applying analytics designing supply chain networks, 2) to investigate the link between operational and strategic management levels when making strategic decisions using Analytics.Qualitative methods have been applied for this study to gain a greater under
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Zubar, Tymofiy, Тимофій Андрійович Зубар, Olena Volovyk, and Олена Іванівна Воловик. "Big data in logistics: last mile application." Thesis, National Aviation University, 2021. https://er.nau.edu.ua/handle/NAU/50494.

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1. 3PL Survey - https://www.3plstudy.com/ 2. 5 Examples of How Big Data in Logistics Can Transform The Supply Chain - https://www.datapine.com/blog/how-big-data-logistics-transform-supply-chain<br>Big data is revolutionizing many business areas, including logistics and business processes in it. The complexity and dynamics of logistics, coupled with the reliance on many movable parts, can cause bottlenecks at any point in the supply chain, making big data application a vital element of effectiveness in logistical processes design and management. For example, big data logistics can be used to o
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Herden, Tino T. [Verfasser], Frank [Gutachter] Straube, and André [Gutachter] Ludwig. "Managing supply chain analytics - guiding organizations to execute analytics initiatives in logistics and supply chain management / Tino T. Herden ; Gutachter: Frank Straube, André Ludwig." Berlin : Technische Universität Berlin, 2020. http://d-nb.info/1213348587/34.

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7

Budnichenko, M. "It’s time for a new generation of supply chain analytics!" Thesis, National Aviation University, 2009. https://er.nau.edu.ua/handle/NAU/46700.

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Nearly every enterprise has a high-level strategic initiative focused on analytics—and is applying advanced technologies to measure, manage and ultimately improve its overall performance. The result is an explosion of business-intelligence efforts, with Forrester Research recently estimating that large enterprises may have 5–15 reporting and analysis solutions, with some companies using at least 20 separate products.
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CHALAKKAL, VARGHESE KISHORE. "Application of Model Predictive Control in Supply Chain Processes." Doctoral thesis, Università Politecnica delle Marche, 2020. http://hdl.handle.net/11566/273217.

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Questa tesi esamina la pianificazione del fabbisogno di materiali Material (Requirements Planning MRP) da una diversa prospettiva, quella delle matrici. L'intero processo viene infatti sviluppato utilizzando una serie di matrici che si evolvono nel tempo in un approccio basato sul sistema tempo-variante. Invece di iterare lungo i livelli della distinta base (materiali), calcoleremo pertanto, simultaneamente, tutti i requisiti dei materiali per tutti i prodotti in un dato momento. Il vantaggio principale di questo approccio è la velocità: possiamo calcolare MPS (Piano Principale di Produzione M
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9

Cao, Lizhong (Lizhong Lilly). "Predictive modeling of fulfillment supply chain for delivery performance improvement." Thesis, Massachusetts Institute of Technology, 2017. http://hdl.handle.net/1721.1/112039.

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Thesis: M.B.A., Massachusetts Institute of Technology, Sloan School of Management, in conjunction with the Leaders for Global Operations Program at MIT, 2017.<br>S.M. in Engineering Systems Massachusetts Institute of Technology, School of Engineering, Institute for Data, Systems, and Society, in conjunction with the Leaders for Global Operations Program at MIT 2017<br>Cataloged from PDF version of thesis.<br>Includes bibliographical references (pages 51-52).<br>NIKE, Inc. Direct-To-Consumer (DTC) represents sales from NIKE-owned retail stores and internet websites. DTC is experiencing tremendo
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10

Pinheiro, Éder Vasco. "An application of distributed model predictive control to supply chain management." reponame:Repositório Institucional da UFSC, 2017. https://repositorio.ufsc.br/handle/123456789/190880.

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Dissertação (mestrado) - Universidade Federal de Santa Catarina, Centro Tecnológico, Programa de Pós-Graduação em Engenharia de Produção, Florianópolis 2017.<br>Os produtos e serviços não apresentam valor até que eles literalmente estejam no lugar e no instante que os consumidores precisam. O conjunto de princípios e técnicas que busca garantir esses valores baseados no tempo e na localização é atribuído a definição de logística. Portanto, sempre que houver um processo incluem o planejamento, a implementação e o controle de fluxos de informações e de bens ou serviços entre origem ofertantes e
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11

Yau, Darryl (Chun Him). "Improving supply chain planning with advanced analytics : analyzing lead time as a case study." Thesis, Massachusetts Institute of Technology, 2018. http://hdl.handle.net/1721.1/117925.

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Thesis: M. Eng. in Supply Chain Management, Massachusetts Institute of Technology, Supply Chain Management Program, 2018.<br>Cataloged from PDF version of thesis.<br>Includes bibliographical references (pages 72-74).<br>Over the years, supply chain management has continued to change and evolve to become a major component in competitive strategy to enhance organizational productivity and profitability. While considerable research has been done in formulating accurate and robust demand forecasts, many areas for improvement remain in supply chain planning. In particular, many planning parameters
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12

Kobor, Hans P. "Closed loop supply chain waste reduction through predictive modelling and process analysis." Thesis, Massachusetts Institute of Technology, 2019. https://hdl.handle.net/1721.1/122573.

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Thesis: M.B.A., Massachusetts Institute of Technology, Sloan School of Management, 2019, In conjunction with the Leaders for Global Operations Program at MIT<br>Thesis: S.M., Massachusetts Institute of Technology, Department of Mechanical Engineering, 2019, In conjunction with the Leaders for Global Operations Program at MIT<br>Cataloged from PDF version of thesis.<br>Includes bibliographical references (pages 59-60).<br>Verizon distributes Customer Premises Equipment (CPE) such as set top boxes, broadband routers, and WiFi extenders to Fios customers via a variety of paths; for example: direc
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13

ADAMASHVILI, NINO. "Big data analytics tools for improving the decision-making process in agrifood supply chain." Doctoral thesis, Università di Foggia, 2021. https://hdl.handle.net/11369/425167.

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Introduzione: Nell'interesse di garantire una sicurezza alimentare a lungo termine di fronte a circostanze mutevoli, è necessario comprendere e considerare gli aspetti ambientali, sociali ed economici del processo di produzione. Inoltre, a causa della globalizzazione, sono stati sollevati i problemi delle lunghe filiere agroalimentari, l'asimmetria informativa, la contraffazione, la difficoltà di tracciare e rintracciare l'origine dei prodotti e le numerose questioni correlate quali il benessere dei consumatori e i costi sanitari. Le tecnologie emergenti guidano verso il raggiungimento di nuov
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14

Zangrando, Giorgia <1992&gt. "Supply Chain Optimization and Analytics in the Mining Industry. A case study from Australia." Master's Degree Thesis, Università Ca' Foscari Venezia, 2016. http://hdl.handle.net/10579/9134.

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This thesis discusses supply chain optimization and analytics trends in the mining industry. A case study is presented from one of the world’s biggest companies, explaining how an integrated system could dramatically increase communication, support decision-making process and eventually improve the overall profitability of the firm.
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15

Hassanzadeh, Alborz. "Three Essays on Assortment, Omnichannel Inventory, and Drone-Enabled Health Supply Chain Optimization." Electronic Thesis or Diss., Cergy-Pontoise, Ecole supérieure des sciences économiques et commerciales, 2023. http://www.theses.fr/2023ESEC0007.

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Cette thèse étudie de nouveaux défis et perspectives dans deux domaines d’application de l’analyse prescriptive: la vente au détail et les opérations de services de santé. Dans le secteur du commerce de détail, nous apportons plusieurs contributions méthodologiques et analytiques. Nous étudions la conception d’un portefeuille optimal de produits dans un environnement concurrentiel permettant de maximiser le revenu de l’entreprise. Cet enjeu est devenu majeur avec l’avènement du commerce électronique. L’objectif est de fournir des modèles et méthodes pour concevoir rapidement un assortiment opt
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16

Baitalmal, Mohammad Hamza. "A Grounded Theory Model of the Relationship between Big Data and an Analytics-Driven Supply Chain Competitive Strategy." Thesis, University of North Texas, 2012. https://digital.library.unt.edu/ark:/67531/metadc1404511/.

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The technology for storing and using big data is evolving rapidly and those that can keep pace are likely to garner additional competitive advantages. One approach to uncovering existing practice in a manner that provides insights for building theory is the use of grounded theory. The current research employs qualitative research following a grounded theory approach to explore gap in understanding the relationship between big data (BD) and the supply chain (SC). In this study eight constructs emerged: Organizational and environmental factors, big data and supply chain analytics, alignment, dat
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17

Kache, Florian [Verfasser]. "Dealing with digital information richness in supply chain management.A review and a Big Data Analytics approach / Florian Kache." Kassel : Kassel University Press, 2015. http://d-nb.info/1080152946/34.

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Baitalmal, Mohammad Hamza. "A Grounded Theory Model of the Relationship between Big Data and an Analytics Driven Supply Chain Competitive Strategy." Thesis, University of North Texas, 2018. https://digital.library.unt.edu/ark:/67531/metadc1404511/.

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The technology for storing and using big data is evolving rapidly and those that can keep pace are likely to garner additional competitive advantages. One approach to uncovering existing practice in a manner that provides insights for building theory is the use of grounded theory. The current research employs qualitative research following a grounded theory approach to explore gap in understanding the relationship between big data (BD) and the supply chain (SC). In this study eight constructs emerged: Organizational and environmental factors, big data and supply chain analytics, alignment, dat
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19

Kharlamov, Alexander Alexandrovitch. "The use of visual analytics in decision making in operations and supply chain management : a systematic literature review." Thesis, Cranfield University, 2013. http://dspace.lib.cranfield.ac.uk/handle/1826/12468.

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The field of Operations & Supply Chain Management (O&SCM) deals with large and complex structures. Evidence from practice suggests that management still runs in silos and decisions are often focused on specific functions as the totality of the problem and the impact on the broader organisation is not always understood. To manage such structures, managers have been investing in information technology to improve data availability and quality. Finally, good data is available with potential to enable holistic decision-making (DM). The field of analytics answers the need to transform data into info
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20

Kosovic, Alexandra, and Jeanna Peebo. "A Review of Artificial Intelligence used in Assortment Planning : A Suggested Approach Applied in the Fast Fashion Industry." Thesis, KTH, Industriell ekonomi och organisation (Inst.), 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-300183.

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The short life cycles and highly variable demand in the fast fashion market causes various challenges in a retailer’s supply chain management processes. The essential task at hand is to provide the right product, at the right time, and at the right place. Due to this inherent difficulty, the bullwhip effect is a major issue in the fashion supply chain. To enhance customer satisfaction and increase the alignment between the supply and market place demand, companies have been pushed towards exploiting big data, supply chain analytics and AI techniques for better business decision making. One suc
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21

"Modeling Frameworks for Supply Chain Analytics." Doctoral diss., 2012. http://hdl.handle.net/2286/R.I.14578.

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abstract: Supply chains are increasingly complex as companies branch out into newer products and markets. In many cases, multiple products with moderate differences in performance and price compete for the same unit of demand. Simultaneous occurrences of multiple scenarios (competitive, disruptive, regulatory, economic, etc.), coupled with business decisions (pricing, product introduction, etc.) can drastically change demand structures within a short period of time. Furthermore, product obsolescence and cannibalization are real concerns due to short product life cycles. Analytical tools that c
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Hassen, Abdurahman, and Bowen Chen. "Big Data Analytics for Agriculture Input Supply Chain in Ethiopia : Supply Chain Management Professionals Perspective." Thesis, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:lnu:diva-97011.

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In Ethiopia, agriculture accounts for 85% of the total employment, and the country’s export entirely relies on agricultural commodities. The country is continuously affected by chronic food shortage. In the last 40 years, the country’s population have almost tripled; and more agricultural productivity is required to support the livelihood of millions of citizens. As reported by various research, Ethiopia needs to address a number of policy and strategic priorities to improve agriculture; however, in-efficient agriculture supply chain for the supply of input is identified as one of the signific
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23

HUANG, PO-CHU, and 黃柏駒. "Knowledge Discovery For Food Supply Chain Management: Unstructured Data Analytics." Thesis, 2017. http://ndltd.ncl.edu.tw/handle/92903337216804303170.

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碩士<br>逢甲大學<br>運輸科技與管理學系<br>105<br>Sustainability gradually plays a crucial role in food supply chains. Nevertheless, lack of studies have been explored the business knowledge of food supply chain from huge text data. Hence, the purpose of this study is to develop a framework of text mining analytics for exploring the crucial rules to tackle sustainability issues of food supply chains. First, this study collects the unstructured data from websites which associated with supply chain management, then further conduct the text-preprocessing. Second, this research uses topic discovery to explore the
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Barkman, Grant. "Predictive assessment methods and tools for supply chain optimization." 2009. http://hdl.handle.net/1993/21373.

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WU, WAN-CHI, and 吳婉琪. "Examining Supply Chain Transparency and Big Data Analytics Use Impact on Service innovation －Supply Chain Agility as a Mediator." Thesis, 2018. http://ndltd.ncl.edu.tw/handle/kwr7zt.

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碩士<br>國立雲林科技大學<br>資訊管理系<br>106<br>This study examines the impact of supply chain transparency and big data analytics use on service innovation－supply chain agility as a mediator. Service innovation is the key indicator to which enterprises and markets nowadays pay more and more attention. In this study, we examine how supply chain transparency affects big data analytics and supply chain agility, and how big data analytics and supply chain agility affect service innovation. This study presents a research model that includes five research hypotheses and four major constructs. Data were collected
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Su, Yi-Ru, and 蘇怡如. "A Study of Demand Predictive Control Model for Supply Chain Management." Thesis, 2005. http://ndltd.ncl.edu.tw/handle/96377547246914505521.

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碩士<br>逢甲大學<br>交通工程與管理所<br>93<br>In the global competition, Supply Chain Management (SCM) plays an important role in enterprise operations and management. SCM is developed to coordinate organizational operations, which encompassing raw materials, manufacturing, sales and service to serve customers. There are lots of uncertainties exist in the Supply chain due to the violent market environment Among these uncertainties, demand uncertainty is originated from the customer''s demand. Therefore, demand forecasting is an important factor in SCM. Recently, lots of researches focus on applying Mod
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27

Hoppe, Magnus Tilmar. "Machine learning in supply chain management." Master's thesis, 2019. http://hdl.handle.net/10362/69191.

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Almost every day newspapers and online media publish articles about the ongoing development of machine learning and related applications. Eventually, the practical use cases seem infinite and the potential especially for the efficient organization of supply chains is difficult to determine. This paper examines different applications as well as the underlying operating principles of self-learning algorithms in order to derive implications for supply chain management. Furthermore, an outlook for the prospective development of machine learning and the related further establishment of cognitive au
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Chen, Ming-Kai, and 陳銘凱. "Reducing the Bullwhip Effect in a Supply Chain - A Model Predictive Concrol Approach." Thesis, 2005. http://ndltd.ncl.edu.tw/handle/39762931235550474173.

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碩士<br>國立雲林科技大學<br>工業工程與管理研究所碩士班<br>93<br>The Bullwhip effect is a perplex problem in supply chain management. This effect denoted that the demand variance will amplify due to ordering policy in the supply chain. It will cause the inventory increase in up-stream element and wasted the production resource. There are many researches denoted that the information share is the best solution of bullwhip effect. But they are also presented that information share can not eliminate the bullwhip effect. So, developing a technology or tool to control the order variance is an important target. In this rese
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Sommerin, Henrik Svankjær. "Big data and its implication on supply chain management." Master's thesis, 2019. http://hdl.handle.net/10362/69213.

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Chiu, Wan-Ting, and 邱琬婷. "Model Predictive Control for Multiple Objective Supply Chain Management – A Case Study of Bicycle Manufacturer." Thesis, 2009. http://ndltd.ncl.edu.tw/handle/50680204898775809267.

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碩士<br>國立嘉義大學<br>運輸與物流工程研究所<br>97<br>A typical supply chain echelon includes suppliers, manufacturers, distributors, retailers, and end customers. Each echelon in a supply chain is connected through the flow of products, information, and funds, and thus there exist a lot of issues for the collaboration and integration of whole supply chain. Among those issues, business objectives and end customer demand uncertainty are essential. This study proposes a multi-objective programming model for supply chain optimization of profit maximum and customer satisfaction. Since end customer demand is an
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31

Manai, Nedra. "Delays prediction using data mining techniques for supply chain risk management company." Master's thesis, 2019. http://hdl.handle.net/10362/57155.

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Project Work presented as the partial requirement for obtaining a Master's degree in Information Management, specialization in Knowledge Management and Business Intelligence<br>Globalization makes competition in supply chain management more intense. Pressure on improving the efficiency, guarantee that goods arrive on time and reduce the cost of shipment became higher. Shipment passes through different continents and cultures, dispersed around the world and encounter different conditions and risks. These risks are unexpected events that might disrupt the flow of materials or the planned ope
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Carvalho, Joana Ferreira da Silva Vasques de. "Engineer for Zero Hunger: Data Analytics Visualization to Scan Humanitarian Supply Chain Vulnerabilities in the Middle East Context." Master's thesis, 2018. https://repositorio-aberto.up.pt/handle/10216/113316.

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Carvalho, Joana Ferreira da Silva Vasques de. "Engineer for Zero Hunger: Data Analytics Visualization to Scan Humanitarian Supply Chain Vulnerabilities in the Middle East Context." Dissertação, 2018. https://repositorio-aberto.up.pt/handle/10216/113316.

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Lee, ChangLu, and 李昶律. "Stabilizing the materials input and inventory in the semiconductor supply chain with changeable characteristics by model predictive control." Thesis, 2012. http://ndltd.ncl.edu.tw/handle/51383073472882217334.

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碩士<br>國立交通大學<br>交通運輸研究所<br>100<br>As semiconductor industry faces more and more fierce competition, the competition originally between companies gradually is changed between supply chains. Actually, Supply chain management (SCM) in Semicondctor industry is an essential way to keep companies to keep their competitioness. Especially for Integrated Device Manufacteur (IDM), there are multiple manufacteuring stages of semiconductor manufacturing process. And IDM need to monitor their performance in different stages. Supply chain in semiconductor manufacturing is characterized by integrating dynami
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Ziaee, Maryam. "Big Data Analytics Adoption in Pharmaceutical Supply Chain Management and its Impact on SCOR Processes: A Qualitative Study of the Australian Pharmaceutical Industry." Thesis, 2019. https://vuir.vu.edu.au/41812/.

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Big Data Analytics (BDA) in supply chain management has recently drawn the attention of academics and practitioners. Big data refers to a massive amount of data from different sources, in different formats, generated at high speed through voluminous of transactions in business environments as well as within supply chain networks. Traditional statistical tools and techniques find it difficult to analyse this massive data. Modern applications, in the form of BDA, assist organisations to capture, store, and analyse data specifically in the field of supply chain. Although there is an increasing tr
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Береженко, Тетяна Богданівна, та Tetiana Bohdanivna Berezhenko. "Впровадження Big Data аналітики в e-Commerce для управління поставками товарів". Master's thesis, 2021. http://elartu.tntu.edu.ua/handle/lib/36842.

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Кваліфікаційна робота присвячена аналізу впровадження Big Data аналітики в e-Commerce для управління поставками товарів. В першому розділі кваліфікаційної роботи описані можливості аналітики Big Data. Висвітлено методи аналітики. Розглянуто застосування Big Data в різних областях. Проаналізовано використання аналітики Big Data в e-Commerce. В другому розділі кваліфікаційної роботи розглянуто ланцюг поставок та його аналітику в управлінні. Досліджено інструменти для аналітики Big Data в e-Commerce. В третьому розділі кваліфікаційної роботи описано узагальнення результатів впливу аналітики Big
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