Constructing the Criteria in Determining the Product Groups for Agriculture 4.0 Applications

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dc.contributor.authorErdogan, Melike
dc.contributor.authorKonurhan, Zekeriya
dc.contributor.authorYucesan, Melih
dc.contributor.authorGul, Muhammet
dc.date.accessioned2025-10-11T20:45:19Z
dc.date.available2025-10-11T20:45:19Z
dc.date.issued2024
dc.departmentDüzce Üniversitesien_US
dc.description2nd International Conference on Science -- Engineering Management and Information Technology -- SEMIT 2023 -- Ankara -- AX6318919en_US
dc.description.abstractWith Agriculture 4.0, the use of techniques such as sensors, robots, artificial intelligence, and machine learning in agriculture has started. It is aimed to increase productivity in agriculture by reducing food loss and waste through Agriculture 4.0. It is a critical decision to determine which products should be handled first for Turkey to benefit from the advantages of Agriculture 4.0 as soon as possible compared to developed countries in the field of agriculture. At this point, the problem of which factors should be addressed in the determination of product & product groups arises. To handle this, in this study, a multi-criteria analysis has been applied to prioritize the factors that should be considered in the determination of the critical fruit and vegetable group for export, which should be considered as a priority within the scope of Agriculture 4.0. In this context, a multi-criteria analysis has been carried out by adopting the Bayesian Best Worst Method BWM (B-BWM), which is an improved version of a pairwise comparison-based BWM method and applied to group decisions. As a result of the analysis, the most important and least important criteria to be used in determining which products or product groups are more suitable for Agriculture 4.0 applications in Turkey and which should be invested in priority have been determined. © 2024 Elsevier B.V., All rights reserved.en_US
dc.identifier.doi10.1007/978-3-031-72284-4_1
dc.identifier.endpage17en_US
dc.identifier.isbn9789819671748
dc.identifier.isbn9789819664610
dc.identifier.isbn9783032026743
dc.identifier.isbn9783032008831
dc.identifier.isbn9783032026712
dc.identifier.isbn9789819671779
dc.identifier.isbn9783031949425
dc.identifier.isbn9789819666874
dc.identifier.isbn9783031936968
dc.identifier.isbn9783031941207
dc.identifier.issn1865-0937
dc.identifier.issn1865-0929
dc.identifier.scopus2-s2.0-85205096891en_US
dc.identifier.scopusqualityQ3en_US
dc.identifier.startpage3en_US
dc.identifier.urihttps://doi.org/10.1007/978-3-031-72284-4_1
dc.identifier.urihttps://hdl.handle.net/20.500.12684/21264
dc.identifier.volume2198 CCISen_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherSpringer Science and Business Media Deutschland GmbHen_US
dc.relation.ispartofCommunications in Computer and Information Scienceen_US
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.snmzKA_Scopus_20250911
dc.subjectAgriculture 4.0en_US
dc.subjectBayesian Best Worst Methoden_US
dc.subjectEvaluation Criteriaen_US
dc.subjectMcdmen_US
dc.subjectAgriculture 4.0en_US
dc.subjectArtificial Intelligence Learningen_US
dc.subjectBad Methodsen_US
dc.subjectBayesianen_US
dc.subjectBayesian Best Bad Methoden_US
dc.subjectEvaluation Criteriaen_US
dc.subjectMachine-learningen_US
dc.subjectMcdmen_US
dc.subjectMulticriteria Analysisen_US
dc.subjectProduct Groupsen_US
dc.titleConstructing the Criteria in Determining the Product Groups for Agriculture 4.0 Applicationsen_US
dc.typeConference Objecten_US

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