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Supply Chain Planning in the food industry
Citation Link: https://doi.org/10.15480/882.3135
Publikationstyp
Conference Paper
Publikationsdatum
2020-09-23
Sprache
English
Herausgeber*innen
TORE-URI
First published in
Number in series
29
Start Page
317
End Page
353
Citation
Hamburg International Conference of Logistics (HICL) 29 : 317-353 (2020)
Contribution to Conference
Publisher
epubli
Purpose: Advanced Planning Systems (APS) can contribute to improved decision-making and enhanced efficiency along complex food supply chains. This paper pre-sents a systematic literature review of supply chain planning (SCP) in the food indus-try. In particular, the literature on three increasingly important planning tasks sup-ported by APS is examined, namely Supply Chain Network Design, Sales & Opera-tions Planning and Production Planning & Scheduling. Methodology: A literature review is conducted by systematically collecting the ex-isting literature published between 1998 and 2020 and classifying it based on three planning tasks supported by APS modules (Supply Chain Network Design, Sales & Operations Planning and Production Planning & Scheduling). Furthermore, research papers are categorized according to the product under consideration, geographic re-gion and method. Findings: Multiple models for SCP practices have been developed. The modelling lit-erature is fragmented around specific challenges faced in food supply chains. Empir-ical literature including case studies on the implementation of APS is sparse. The findings suggest that developed models for the three examined planning tasks are only implemented to a limited extent in practice. Originality: This paper focuses on three planning tasks that are of increasing rele-vance for the food industry. The literature review can help practitioners within the food industry to get insights regarding the opportunities offered by the three soft-ware modules examined in this paper. Further research should be conducted in these areas to make literature on SCP more practically relevant for managers.
Schlagworte
Logistics
Industry 4.0
Digitalization
Innovation
Supply Chain Management
Artificial Intelligence
Data Science
DDC Class
330: Wirtschaft
380: Handel, Kommunikation, Verkehr
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Stueve et al. (2020) - Supply Chain Planning in the food industry.pdf
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