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Artificial intelligence applied to supply chain operations management : a systematic literature review
Mendonça, Guilherme Dayrell; Lima, Orlando Fontes <Jr> - In: International journal of logistics systems and … 45 (2023) 1, pp. 1-30
Persistent link: https://www.econbiz.de/10014316909
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Towards Logistics 4.0 : an edge-cloud software framework for big data analytics in logistics processes
Stietencron, Moritz von; Hribernik, Karl; Lepenioti, … - In: International journal of production research 60 (2022) 19, pp. 5994-6012
Persistent link: https://www.econbiz.de/10013501007
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Product lifecycle optimization by application of process mining
Meßner, Marco; Dirnberger, Johannes - In: Data science and innovation in supply chain management …, (pp. 295-315). 2020
Purpose: Active product life cycle management contributes to supply chain optimization. However, in nowadays industry the high number of variants and backward loops complicate tracing the entire product lifecycle in an ERP system. Consequently, product lifecycle and corresponding...
Persistent link: https://www.econbiz.de/10012388084
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Click here for a data scientist : big data, predictive analytics, and theory development in the era of a maker movement supply chain
Fawcett, Stanley E.; Waller, Matthew A. - In: Journal of business logistics : JBL 34 (2013) 4, pp. 249-252
Persistent link: https://www.econbiz.de/10010243163
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Smart connected sensors, cyber-physical networks, and big data analytics systems in Internet of Things-based real-time production logistics
Moore, Kelly - In: Economics, management and financial markets 15 (2020) 2, pp. 16-22
Persistent link: https://www.econbiz.de/10012239724
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An exploration of big data practices in retail sector
Aktas, Emel; Meng, Yuwei - In: Logistics 1 (2017) 2, pp. 1-28
, we identify four themes for big data applications in retail logistics: availability, assortment, pricing, and layout …
Persistent link: https://www.econbiz.de/10012123327
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Big Data Analytics Based on Logistical Models
Nywlt, Johannes - 2015
Over the past years, a change of feedback data in terms of quantity, quality, and timeliness could be observed in production. The generation of high resolution production feedback data enables producing companies to apply big data analytics in order to create competitive advantages. This paper...
Persistent link: https://www.econbiz.de/10013015035
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Use of Big Data Analysis to identify possible sources of Supply Chain disruption through the DOTMLPFI method
Nagy, Judit; Foltin, Pavel; Ondryhal, Vojtech - In: LogForum : elektroniczne czasopismo naukowe z dziedziny … 18 (2022) 3, pp. 309-319
Persistent link: https://www.econbiz.de/10013450698
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Data science, predictive analytics, and big data : a revolution that will transform supply chain design and management
Waller, Matthew A.; Fawcett, Stanley E. - In: Journal of business logistics : JBL 34 (2013) 2, pp. 77-84
Persistent link: https://www.econbiz.de/10009766760
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IPSERA ONLINE 2021 Track on Purchasing and Supply : Big Data and Analytics Methods of artificial intelligence in procurement: A conceptual literature review
Spreitzenbarth, Jan Martin; Stuckenschmidt, Heiner; … - 2022
Artificial intelligence is a key technology for procurement and its usage is still in its infancy.This work builds upon literature reviews on big data analytics in supply chain management(Min, 2010, Waller and Fawcett, 2013, Souza, 2014, Gunasekaran et al., 2017, Nguyen et al.,2017) focusing on...
Persistent link: https://www.econbiz.de/10014240544