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  • Search: isPartOf:"Science and innovation"
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Year of publication
Subject
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Innovation 29 Artificial Intelligence 28 Artificial intelligence 28 Data Science 28 Digitalisierung 28 Digitalization 28 Digitization 28 Industry 4.0 28 Künstliche Intelligenz 28 Lieferkette 28 Logistics 28 Logistik 28 Supply Chain Management 28 Supply chain 28 Industrie 4.0 12 Logistics provider 12 Logistikunternehmen 12 Big Data 4 Big data 4 E-commerce 3 Electronic Commerce 3 Automation 2 Automatisierung 2 Blockchain 2 Business process management 2 Business start-up 2 Data Mining 2 Data mining 2 Deutschland 2 Germany 2 Product life cycle 2 Produktlebenszyklus 2 Prozessmanagement 2 Unternehmensgründung 2 Aerospace industry 1 Beschaffung 1 Binnenschifffahrt 1 Business model 1 Classification 1 Data quality 1
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Online availability
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Free 30 CC license 28
Type of publication
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Article 28 Book / Working Paper 1 Journal 1
Type of publication (narrower categories)
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Aufsatz im Buch 28 Book section 28 Conference paper 28 Konferenzbeitrag 28 Graue Literatur 1 Non-commercial literature 1 Statistics 1 Statistik 1
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Language
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English 30 French 1
Author
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Kersten, Wolfgang 2 Klumpp, Matthias 2 Verbeet, Richard 2 Agha, Mouhamad Shaker Ali 1 Ahmed, Mohamed 1 Bartsch, Devis 1 Baumgärtel, Hartwig 1 Beckmann, Anne 1 Bouzeghoub, Amel 1 Brunner, Uwe 1 Brylowski, Martin 1 Chabridon, Sophie 1 Dirnberger, Johannes 1 Dumitrescu, Roman 1 Feldmann, Carsten 1 Feldt, Julia 1 Gabriel, Stefan 1 Gast, Johannes 1 Gürpinar, Tan 1 Haas, Jonas 1 Haasis, Hans-Dietrich 1 Harre, Sophie 1 Haße, Hendrik 1 Held, Tobias 1 Henke, Michael 1 Herlyn, Wilmjakob 1 Hinkka, Ville 1 Hobscheidt, Daniela 1 Hunker, Joachim 1 Jahn, Carlos 1 Kaupe, Victor 1 Kleineidam, Julia 1 Klöver, Steffen 1 Kontny, Henning 1 Kretschmann, Lutz 1 Krol, Felix 1 Kuusijärvi, Jarkko 1 König, Sandra 1 Kühn, Arno 1 Lange, Kerstin 1
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Institution
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OECD 1
Published in...
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Data science and innovation in supply chain management : how data transforms the value chain 28 2001: Science and innovation 1 Swiss Science and Innovation Council Secretariat Working Paper 3/2015 1
Source
All
ECONIS (ZBW) 30
Showing 1 - 10 of 30
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Product modularization in integrated supply chains : a product life-cycle phase specific concept for effect allocation
Brylowski, Martin; Ludwig, Maximilian; Kersten, Wolfgang; … - In: Data science and innovation in supply chain management …, (pp. 25-76). 2020
Purpose: Product modularization and supply chain integration have establishedthemselves as efficient methods for complexity management, but a holistic view oftheir effects has rarely been studied. For this reason, we demonstrate a conceptwhich presents these effects along the product life-cycle...
Persistent link: https://www.econbiz.de/10012387162
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Enhancing B2B supply chain traceability using smart contracts and IoT
Ahmed, Mohamed; Taconet, Chantal; Ould, Mohamed; … - In: Data science and innovation in supply chain management …, (pp. 559-589). 2020
Purpose: The management of B2B supply chains that involve many stakeholders re-quires traceability processes. Those processes need to be secured. Furthermore, quality traceability data has to be transparently shared among the stakeholders. In order to improve the traceability process, we propose...
Persistent link: https://www.econbiz.de/10012387382
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Blockchain technology in Germany : an excerpt of real use cases in logistics industry
Bartsch, Devis; Winkler, Herwig - In: Data science and innovation in supply chain management …, (pp. 699-735). 2020
Purpose: Due to the large number of intermediaries in logistics networks there is avariety of possible failures, frictions and waste of time and money among the logisticsprocess chain. With the ability to provide data securely in near real-time, liketrack and tracing data of goods to every...
Persistent link: https://www.econbiz.de/10012387383
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Success factors for online food retail logistics
Beckmann, Anne; Kleineidam, Julia; Straube, Frank - In: Data science and innovation in supply chain management …, (pp. 852-873). 2020
Purpose: While e-commerce in general has been growing rapidly for years, food e-commerce is lagging behind in Germany. The common approach of using traditional logistics systems and fulfilment concepts does not lead to long-term success. Con-sidering this problem, success factors are needed as a...
Persistent link: https://www.econbiz.de/10012387384
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A holistic digitalization KPI framework for the aerospace industry
Krol, Felix; Saeed, Muhammad Amad; Kersten, Wolfgang - In: Data science and innovation in supply chain management …, (pp. 798-847). 2020
Purpose: The aerospace supply chain is characterized by a high degree of small andmedium-sized suppliers. To stay competitive, suppliers are facing high pressures todigitalize their business but have limited resources available. Furthermore, aerospacesuppliers lack a framework to measure their...
Persistent link: https://www.econbiz.de/10012387385
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Impact of notification time on risk mitigation in inland waterway transport
Gast, Johannes; Wehrle, Rebecca; Wiens, Marcus; … - In: Data science and innovation in supply chain management …, (pp. 247-278). 2020
Purpose: Transport infrastructures form the backbone of today's interconnected real economy. Interruptions in the availability of these critical infrastructures occur, among other things, due to maintenance operations. Since companies and Supply Chains are dependent on planning security, an...
Persistent link: https://www.econbiz.de/10012387386
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Blockchain technology : integration in supply chain processes
Gürpinar, Tan; Harre, Sophie; Henke, Michael; Saleh, Farah - In: Data science and innovation in supply chain management …, (pp. 153-185). 2020
Purpose: Supply chain networks face an increasing demand to integrate globally distributedcustomers and suppliers. As supply chain processes are deemed to lack sufficienttransparency and security, blockchain solutions are piloted to offer an IT infrastructurecovering these needs. This paper aims...
Persistent link: https://www.econbiz.de/10012387387
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Supply chain planning in the food industry
Stüve, David; Meer, Robert van der; Lütke Entrup, Matthias - In: Data science and innovation in supply chain management …, (pp. 317-353). 2020
Purpose: Advanced Planning Systems (APS) can contribute to improved decision-making and enhanced efficiency along complex food supply chains. This paper presents a systematic literature review of supply chain planning (SCP) in the food industry. In particular, the literature on three...
Persistent link: https://www.econbiz.de/10012387949
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Impacts of a smart factory on procurement logistics
Zander, Bennet; Lange, Kerstin; Haasis, Hans-Dietrich - In: Data science and innovation in supply chain management …, (pp. 459-485). 2020
Purpose: In order to keep up with the automation Smart Factories will bring into the market, procurement logistics has to be redesigned to ensure self-organizing production. The purpose of this paper is to examine the future changes of the procurement processes as well as the further role of...
Persistent link: https://www.econbiz.de/10012388001
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Evaluation of data quality in dimensioning capacity
Vliegen, Lea; Moroff, Nikolas Ulrich; Riehl, Katharina - In: Data science and innovation in supply chain management …, (pp. 355-394). 2020
Purpose: This paper aims to give an overview of the current state of research on measuring data quality. The identified methods will be applied to the task of dimensioning capacities (e.g. warehouse capacities) in the field of supply chain design (SCD) to further increase trust in decision...
Persistent link: https://www.econbiz.de/10012388018
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