A taxonomy of highly interdependent, supply chain relationships: The use of cluster analysis

dc.contributor.authorHumphries, Andrew-
dc.contributor.authorTowriss, John-
dc.contributor.authorWilding, Richard D.-
dc.date.accessioned2011-09-08T10:34:03Z
dc.date.available2011-09-08T10:34:03Z
dc.date.issued2007-01-01T00:00:00Z-
dc.description.abstractCluster analysis provides a statistical method whereby unknown groupings of similar attributes can be identified from a mass of data and is well-known within marketing and a wide range of other disciplines. This paper seeks to describe the use of cluster analysis in an unusual setting to classify a large sample of dyadic, highly interdependent, supply chain relationships based upon the quality of their interactions. This paper aims to show how careful attention to the detail of research design and the use of combined methods leads to results that both are useful to managers and make a contribution to knowledge.en_UK
dc.identifier.citationAndrew S. Humphries, John Towriss, Richard Wilding; A taxonomy of highly interdependent, supply chain relationships: The use of cluster analysis, International Journal of Logistics Management, 2007, Volume:18, Issue:3, Page:385-401.-
dc.identifier.issn0957-4093-
dc.identifier.urihttp://dx.doi.org/10.1108/09574090710835129-
dc.identifier.urihttp://dspace.lib.cranfield.ac.uk/handle/1826/2734
dc.publisherMcben_UK
dc.subjectCluster Analysisen_UK
dc.subjectRelationship marketingen_UK
dc.subjectSupply chain managementen_UK
dc.titleA taxonomy of highly interdependent, supply chain relationships: The use of cluster analysisen_UK
dc.typeArticle-

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