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Food supply chain management: systems, implementations, and future research
KTH, School of Industrial Engineering and Management (ITM), Production Engineering.ORCID iD: 0000-0001-8679-8049
2017 (English)In: Industrial management + data systems, ISSN 0263-5577, E-ISSN 1758-5783, Vol. 117, no 9, 2085-2114 p.Article, review/survey (Refereed) Published
Abstract [en]

Purpose - The purpose of this paper is to review the food supply chain management (FSCM) in terms of systems and implementations so that observations and lessons from this research could be useful for academia and industrial practitioners in the future. Design/methodology/approach - A systematical and hierarchical framework is proposed in this paper to review the literature. Categorizations and classifications are identified to organize this paper. Findings - This paper reviews total 192 articles related to the data-driven systems for FSCM. Currently, there is a dramatic increase of research papers related to this topic. Looking at the general interests on FSCM, research on this topic can be expected to increase in the future. Research limitations/implications - This paper only selected limited number of papers which are published in leading journals or with high citations. For simplicity without generality, key findings and observations are significant from this research. Practical implications - Some ideas from this paper could be expanded into other possible domains so that involved parties are able to be inspired for enriching the FSCM. Future implementations are useful for practitioners to conduct IT-based solutions for FSCM. Social implications - As the increasing of digital devices in FSCM, large number of data will be used for decision-makings. Data-driven systems for FSCM will be the future for a more sustainable food supply chain. Originality/value - This is the first attempt to provide a comprehensive review on FSCM from the view of data-driven IT systems.

Place, publisher, year, edition, pages
2017. Vol. 117, no 9, 2085-2114 p.
Keyword [en]
Case studies, Food supply chain management, Review, Data-driven systems, Implementations, IT systems
National Category
Production Engineering, Human Work Science and Ergonomics
Identifiers
URN: urn:nbn:se:kth:diva-220309DOI: 10.1108/IMDS-09-2016-0391ISI: 000416732500017Scopus ID: 2-s2.0-85031307480OAI: oai:DiVA.org:kth-220309DiVA: diva2:1168821
Note

QC 20171221

Available from: 2017-12-21 Created: 2017-12-21 Last updated: 2017-12-21Bibliographically approved

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Wang, Lihui

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