E-Collaboration Systems: Identification of System Classes using Cluster Analysis

E-Collaboration Systems: Identification of System Classes using Cluster Analysis

Kai Riemer (The University of Sydney, Australia)
Copyright: © 2009 |Pages: 24
DOI: 10.4018/jec.2009070101
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Abstract

E-Collaboration systems have become the backbone infrastructure to support virtual work in and across organizations. Fuelled by recent technology trends the market today offers an abundance of systems that often support a wide range of communication and collaboration features. In this article I present a study that aims to shed light on the market for E-Collaboration systems by structuring the range of available systems into meaningful classes. To this end, a sample of 94 E-Collaboration systems were characterized using a classification approach. A cluster analysis led to the identification of five system classes and a range of sub classes. I describe the system classes and discuss trends of systems integration and convergence. The results should be equally helpful for researchers who deal with E-Collaboration systems as their objects of interest, as well as for business executives, who need to gather information to support buying decisions.

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