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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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Predicting solutions of large-scale optimization problems via machine learning : a case study in blood supply chain management
Abbasi, Babak; Babaei, Toktam; Hosseinifard, Zahra; … - In: Computers & operations research : and their … 119 (2020), pp. 1-20
Persistent link: https://www.econbiz.de/10012236824
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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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A systematic classification of database solutions for data mining to support tasks in supply chains
Hunker, Joachim; Scheidler, Anne Antonia; Rabe, Markus - In: Data science and innovation in supply chain management …, (pp. 395-425). 2020
Purpose: Our research shows that considering well suited NoSQL databases is beneficial for logistics tasks. For … these issues. Methodology: This paper discusses Data Mining in the context of Supply Chain Management tasks in logistics and … in logistics is a very promising approach. The research is based on a case study, whose core element is the analysis of …
Persistent link: https://www.econbiz.de/10012388130
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Emergent technologies for supply chain risk and disruption management
Tripathi, Prateek Kumar; Deshmukh, Arun Kumar; Nath, … - In: Supply Chain Risk and Disruption Management : Latest …, (pp. 73-94). 2023
Persistent link: https://www.econbiz.de/10014314320
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The potential of emergent disruptive technologies for humanitarian supply chains : the integration of blockchain, Artificial Intelligence and 3D printing
Rodríguez-Espíndola, Oscar; Chowdhury, Soumyadeb; … - In: International journal of production research 58 (2020) 15, pp. 4610-4630
Persistent link: https://www.econbiz.de/10012266072
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Identification and analysis of adoption barriers of disruptive technologies in the logistics industry
Rathore, Bhawana; Gupta, Rohit; Biswas, Baidyanath; … - In: The international journal of logistics management 33 (2022) 5, pp. 136-169
Persistent link: https://www.econbiz.de/10013552737
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Extracting supply chain maps from news articles using deep neural networks
Wichmann, Pascal; Brintrup, Alexandra; Baker, Simon; … - In: International journal of production research 58 (2020) 17, pp. 5320-5336
Persistent link: https://www.econbiz.de/10012266346
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Using machine learning to detect misstatements
Bertomeu, Jeremy; Cheynel, Edwige; Floyd, Eric; Pan, … - In: Review of accounting studies 26 (2021) 2, pp. 468-519
Persistent link: https://www.econbiz.de/10012548986