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

Abstract

Cluster 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.