Assessing GDSS empirical research

GDSS experiments can differ from one another in many important dimensions. To interpret the results of a particular experiment in the context of the literature, it is necessary to find similar experiments for comparison. In this paper the authors present a method for finding the appropriate peer experiments. This method involves defining a set of variables to classify experimental conditions, defining scales for each variable, capturing the difference between experiments by measuring the average distance between them, and by using multi-dimensional scaling as a way of representing the positioning of experiments graphically. The method is applied to experiments analyzed by Pinsonneault and Kraemer based on the classification scheme they propose. Detailed data and graphs are presented. The results show that the method is a robust way of identifying experiments that are similar and distinguishing among experiments that are fundamentally different from one another.