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dc.contributor.authorAdeyemi, Oluseyi
dc.contributor.authorPotticary, Martin
dc.contributor.authorSunmola, Funlade
dc.contributor.authorIdris, Musibaudeen Olatunde
dc.contributor.authorAdeyemi, Esther Onoge
dc.contributor.authorRaji, Ibrahim Oluwole
dc.date.accessioned2024-04-25T17:45:01Z
dc.date.available2024-04-25T17:45:01Z
dc.date.issued2024-03-20
dc.identifier.citationAdeyemi , O , Potticary , M , Sunmola , F , Idris , M O , Adeyemi , E O & Raji , I O 2024 , ' A Comparative analysis of service supply chain performance using analytic hierarchy process methodology ' , Procedia Computer Science , vol. 232 , pp. 3102-3111 . https://doi.org/10.1016/j.procs.2024.02.126
dc.identifier.issn1877-0509
dc.identifier.urihttp://hdl.handle.net/2299/27804
dc.description© 2024 The Author(s). . Published by ELSEVIER B.V. This is an open access article under the Creative Commons Attribution-NonCommercial-NoDerivatives CC BY-NC-ND licence, https://creativecommons.org/licenses/by-nc-nd/4.0/
dc.description.abstractThe study aims to provide a comprehensive analysis of the service supply chain (SSC) of small and medium scale enterprises (SMEs) and to offer insights to improve its supply chain performance. The study employs mixed methods, to analyse the data collected from SMEs. The findings highlight several key metrics of effective supply chain management in a service firm such as utilisation and flexibility of service capacity, inventory, order lead times, relationships between the organisation, its suppliers and customers, the importance of effective demand forecasting and inventory management as valuable attributes to improve the supply chain performance of service firms. Inventory lead time is presented as a fundamental metric useful in determining the service supply chain performance of SMEs.en
dc.format.extent10
dc.format.extent630224
dc.language.isoeng
dc.relation.ispartofProcedia Computer Science
dc.subjectSupply Chain
dc.subjectPerformance
dc.subjectService company
dc.subjectMetrics
dc.subjectAHP
dc.titleA Comparative analysis of service supply chain performance using analytic hierarchy process methodologyen
dc.contributor.institutionSchool of Physics, Engineering & Computer Science
dc.contributor.institutionDepartment of Engineering and Technology
dc.contributor.institutionCentre for Future Societies Research
dc.contributor.institutionMaterials and Structures
dc.contributor.institutionCentre for Engineering Research
dc.description.statusPeer reviewed
rioxxterms.versionofrecord10.1016/j.procs.2024.02.126
rioxxterms.typeOther
herts.preservation.rarelyaccessedtrue


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