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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, 31 (16). pp. 1349-1362. doi:10.1080/09537287.2019.1707896 ISSN 0953-7287.

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Official URL: http://dx.doi.org/10.1080/09537287.2019.1707896

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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
Divisions: Faculty of Science, Engineering and Medicine > Engineering > 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:
DateEvent
2 January 2020Published
30 November 2019Accepted
Volume: 31
Number: 16
Page Range: pp. 1349-1362
DOI: 10.1080/09537287.2019.1707896
Status: Peer Reviewed
Publication Status: Published
Access rights to Published version: Restricted or Subscription Access
Date of first compliant deposit: 7 January 2020
Date of first compliant Open Access: 2 January 2021

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