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Developing a framework to support strategic supply chain segmentation decisions : a case study
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Kharlamov, Alexander A., Ferreira, Luís Miguel D. F. and Godsell, Janet (2020) Developing a framework to support strategic supply chain segmentation decisions : a case study. Production Planning & Control . doi:10.1080/09537287.2019.1707896 (In Press)
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WRAP-developing-framework-support-strategic-supply-chain-segmentation-decisions-Godsell-2019.pdf - Accepted Version Embargoed item. Restricted access to Repository staff only until 2 January 2021. Contact author directly, specifying your specific needs. - Requires a PDF viewer. Download (1724Kb) |
Official URL: http://dx.doi.org/10.1080/09537287.2019.1707896
Abstract
There is a huge opportunity in mining operational data in the supply chain (SC) to support strategic segmentation decisions. This research has the objective of developing a framework to support strategic supply chain segmentation decisions. This research is exploratory in nature, with the methodology based on action research combined with a single empirical study in a large Portuguese multinational company. A data-mining project, based on the CRISP-DM methodology, is adopted to develop the product segmentation framework. The company had the strategic objective to move beyond a single make to order strategy towards a segmented SC strategy. By applying the framework, the most relevant criteria were identified (demand volume, demand variability, order corrections, delivery time window and delivery frequency). These were then used to identify four relevant segments each with a tailored SC strategy.
| Item Type: | Journal Article | ||||||
|---|---|---|---|---|---|---|---|
| Subjects: | H Social Sciences > HD Industries. Land use. Labor H Social Sciences > HF Commerce Q Science > QA Mathematics Z Bibliography. Library Science. Information Resources > ZA Information resources |
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| Divisions: | Faculty of Science > WMG (Formerly the Warwick Manufacturing Group) | ||||||
| Library of Congress Subject Headings (LCSH): | Business logistics -- Case studies, Market segmentation, Web usage mining, Data mining -- Portugal | ||||||
| Journal or Publication Title: | Production Planning & Control | ||||||
| Publisher: | Taylor & Francis Ltd. | ||||||
| ISSN: | 0953-7287 | ||||||
| Official Date: | 2 January 2020 | ||||||
| Dates: |
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| Date of first compliant deposit: | 7 January 2020 | ||||||
| DOI: | 10.1080/09537287.2019.1707896 | ||||||
| Status: | Peer Reviewed | ||||||
| Publication Status: | In Press | ||||||
| Access rights to Published version: | Restricted or Subscription Access |
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