The Use of Supply Chain Metrics in Lebanon

One standard in measuring supply chain management success is that established by the SCOR model. The SCOR model was created by a management consulting firm of the Supply Chain Council which relies on specific performance measures that are related to the five-core process building blocks: Plan, Sourc...

وصف كامل

محفوظ في:
التفاصيل البيبلوغرافية
المؤلف الرئيسي: Huballah, Zeina (author)
التنسيق: masterThesis
منشور في: 2020
الموضوعات:
الوصول للمادة أونلاين:http://hdl.handle.net/10725/13524
https://doi.org/10.26756/th.2022.279
http://libraries.lau.edu.lb/research/laur/terms-of-use/thesis.php
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author Huballah, Zeina
author_facet Huballah, Zeina
author_role author
dc.creator.none.fl_str_mv Huballah, Zeina
dc.date.none.fl_str_mv 2020
2020-05-01
2022-04-28T11:43:04Z
2022-04-28T11:43:04Z
dc.identifier.none.fl_str_mv http://hdl.handle.net/10725/13524
https://doi.org/10.26756/th.2022.279
http://libraries.lau.edu.lb/research/laur/terms-of-use/thesis.php
dc.language.none.fl_str_mv en
dc.publisher.none.fl_str_mv Lebanese American University
dc.rights.*.fl_str_mv info:eu-repo/semantics/openAccess
dc.subject.none.fl_str_mv Business logistics -- Lebanon
Business logistics -- Developing countries
Business logistics -- Management
Lebanese American University -- Dissertations
Dissertations, Academic
dc.title.none.fl_str_mv The Use of Supply Chain Metrics in Lebanon
A Study of SCOR Applicability
dc.type.none.fl_str_mv Thesis
info:eu-repo/semantics/publishedVersion
info:eu-repo/semantics/masterThesis
description One standard in measuring supply chain management success is that established by the SCOR model. The SCOR model was created by a management consulting firm of the Supply Chain Council which relies on specific performance measures that are related to the five-core process building blocks: Plan, Source, Make, Deliver, and Return with a sixth block of “Enable” added later. With its origins in Western/Developed Countries, there is some question about the applicability of the same metric system in Low- and Middle-Income Countries. This thesis relies on a survey methodology to explore the extent to which companies across multiple industries are measuring the SCOR Level 1 and Level 2 metrics in Lebanon and the MENA region. The results of the survey are analyzed via two machine learning techniques – an unsupervised clustering technique (kMeans) to identify companies with similar behavior relative to the SCOR metrics and a supervised learning technique (Classification Trees) to ascertain which company demographics (ie industry, age, size, age of employees, and SCOR familiarity) dictate cluster membership.
eu_rights_str_mv openAccess
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language_invalid_str_mv en
network_acronym_str LAURepo
network_name_str Lebanese American University repository
oai_identifier_str oai:laur.lau.edu.lb:10725/13524
publishDate 2020
publisher.none.fl_str_mv Lebanese American University
repository.mail.fl_str_mv
repository.name.fl_str_mv
repository_id_str
spelling The Use of Supply Chain Metrics in LebanonA Study of SCOR ApplicabilityHuballah, ZeinaBusiness logistics -- LebanonBusiness logistics -- Developing countriesBusiness logistics -- ManagementLebanese American University -- DissertationsDissertations, AcademicOne standard in measuring supply chain management success is that established by the SCOR model. The SCOR model was created by a management consulting firm of the Supply Chain Council which relies on specific performance measures that are related to the five-core process building blocks: Plan, Source, Make, Deliver, and Return with a sixth block of “Enable” added later. With its origins in Western/Developed Countries, there is some question about the applicability of the same metric system in Low- and Middle-Income Countries. This thesis relies on a survey methodology to explore the extent to which companies across multiple industries are measuring the SCOR Level 1 and Level 2 metrics in Lebanon and the MENA region. The results of the survey are analyzed via two machine learning techniques – an unsupervised clustering technique (kMeans) to identify companies with similar behavior relative to the SCOR metrics and a supervised learning technique (Classification Trees) to ascertain which company demographics (ie industry, age, size, age of employees, and SCOR familiarity) dictate cluster membership.1 online resource (ix, 66 leaves) : ill. (chiefly col.)Bibliography: leaf 50-52.Lebanese American University2022-04-28T11:43:04Z2022-04-28T11:43:04Z20202020-05-01Thesisinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesishttp://hdl.handle.net/10725/13524https://doi.org/10.26756/th.2022.279http://libraries.lau.edu.lb/research/laur/terms-of-use/thesis.phpeninfo:eu-repo/semantics/openAccessoai:laur.lau.edu.lb:10725/135242022-07-07T09:25:22Z
spellingShingle The Use of Supply Chain Metrics in Lebanon
Huballah, Zeina
Business logistics -- Lebanon
Business logistics -- Developing countries
Business logistics -- Management
Lebanese American University -- Dissertations
Dissertations, Academic
status_str publishedVersion
title The Use of Supply Chain Metrics in Lebanon
title_full The Use of Supply Chain Metrics in Lebanon
title_fullStr The Use of Supply Chain Metrics in Lebanon
title_full_unstemmed The Use of Supply Chain Metrics in Lebanon
title_short The Use of Supply Chain Metrics in Lebanon
title_sort The Use of Supply Chain Metrics in Lebanon
topic Business logistics -- Lebanon
Business logistics -- Developing countries
Business logistics -- Management
Lebanese American University -- Dissertations
Dissertations, Academic
url http://hdl.handle.net/10725/13524
https://doi.org/10.26756/th.2022.279
http://libraries.lau.edu.lb/research/laur/terms-of-use/thesis.php