Article ID: | iaor20112311 |
Volume: | 8 |
Issue: | 2 |
Start Page Number: | 167 |
End Page Number: | 182 |
Publication Date: | Feb 2011 |
Journal: | International Journal of Logistics Systems and Management |
Authors: | McLaren Tim S, Manatsa Priscilla R |
Keywords: | datamining |
Selecting a Supply Chain Management (SCM) software package is difficult due to the complexity and apparent similarities of the software. This paper uses text mining tools to analyse documentation covering the seven most popular supply chain software packages. The resulting concept maps reveal that any distinguishing features are deeply buried in the documentation, while at a superficial level all seven vendors would appear to address the same concepts. This paper contributes a more precise understanding of the similarities and differences between SCM software packages. Guidelines for using this knowledge to make more rational and informed software selection decisions are discussed.