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Erscheinungsjahr: 
2020
Quellenangabe: 
[Editor:] Kersten, Wolfgang [Editor:] Blecker, Thorsten [Editor:] Ringle, Christian M. [Title:] Data Science and Innovation in Supply Chain Management: How Data Transforms the Value Chain. Proceedings of the Hamburg International Conference of Logistics (HICL), Vol. 29 [ISBN:] 978-3-7531-2346-2 [Publisher:] epubli GmbH [Place:] Berlin [Year:] 2020 [Pages:] 851-873
Verlag: 
epubli GmbH, Berlin
Zusammenfassung: 
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 guideline for developing effec-tive fulfilment concepts for online food supply chains in the future. Methodology: Based on industry performance indexes as well as an extensive search via the google search engine about 20 case studies on online food fulfilment con-cepts are identified. The case studies are evaluated using a performance measure-ment concept. Information from the highest performing companies is used to deduct success factors for good practices in online food fulfilment. Findings: Three main groups of suppliers were identified: Full-range provider, niche suppliers (selective assortment with a specific focus) and supplier of cooking boxes. The fulfilment concept of online grocery retailers is described using thirteen catego-ries. Three success factors could be derived: Reduction of complexity, focus on online fulfilment, and offering a unique product-service mix. Originality: This paper contributes to the research areas of e-commerce and of lo-gistics and supply chain management, especially online food supply chains. In this area only little original scientific research exists. Also, the approach of using second-ary case studies is relatively new in this area of research and has yielded interesting results.
Schlagwörter: 
Logistics
Industry 4.0
Digitalization
Innovation
Supply Chain Management
Artificial Intelligence
Data Science
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