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dc.contributor.authorIslam, S
dc.contributor.authorManning, L
dc.contributor.authorCullen, Jonathan
dc.date.accessioned2021-10-07T23:30:15Z
dc.date.available2021-10-07T23:30:15Z
dc.date.issued2021-08
dc.identifier.issn2071-1050
dc.identifier.urihttps://www.repository.cam.ac.uk/handle/1810/329108
dc.description.abstract<jats:p>Traceability technologies have great potential to improve sustainable performance in cold food supply chains by reducing food loss. In existing approaches, traceability technologies are selected either intuitively or through a random approach, that neither considers the trade-off between multiple cost–benefit technology criteria nor systematically translates user requirements for traceability systems into the selection process. This paper presents a hybrid approach combining the fuzzy Analytic Hierarchy Process (AHP) and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) with integer linear programming to select the optimum traceability technologies for improving sustainable performance in cold food supply chains. The proposed methodology is applied in four case studies utilising data collected from literature and expert interviews. The proposed approach can assist decision-makers, e.g., food business operators and technology companies, to identify what combination of technologies best suits a given food supply chain scenario and reduces food loss at minimum cost.</jats:p>
dc.description.sponsorshipCambridge Trust and Commonwealth Scholarship Commissions
dc.publisherMDPI AG
dc.rightsAttribution 4.0 International
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.titleA hybrid traceability technology selection approach for sustainable food supply chains
dc.typeArticle
prism.issueIdentifier16
prism.publicationDate2021
prism.publicationNameSustainability (Switzerland)
prism.volume13
dc.identifier.doi10.17863/CAM.76554
dcterms.dateAccepted2021-08-10
rioxxterms.versionofrecord10.3390/su13169385
rioxxterms.versionVoR
rioxxterms.licenseref.urihttp://www.rioxx.net/licenses/all-rights-reserved
rioxxterms.licenseref.startdate2021-08-02
dc.contributor.orcidCullen, Jonathan [0000-0003-4347-5025]
dc.identifier.eissn2071-1050
rioxxterms.typeJournal Article/Review
cam.issuedOnline2021-08-21


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Attribution 4.0 International
Except where otherwise noted, this item's licence is described as Attribution 4.0 International