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The empirical evaluation of complex decision support systems is often limited to the self-reported satisfaction of the systems’ users.

Such an approach is problematic due to the conflation of the user's satisfaction related to the decision support system and the decision making process and its outcomes.

In addition, it bears limitations that are common among most techniques that solicit participant-stated feedback.

In this talk, based on data that was gathered by a web-based participatory system for transportation planning in the Puget Sound region, I present analytical methods for the empirical evaluation of decision support systems based on human-computer interaction. In addition, I discuss the extent to which self-centered and selfless decision making expressed itself in the transportation project choices of the users of the participatory system.

The observed behavioral patterns suggest predominately self-centered choice making behavior of layman participants in online transportation planning.

Martin Swobodzinski is an assistant professor of geography, and director of the Center for Spatial Research and Analysis (CSAR) at Portland State University. He has a Ph.D. from UC-Santa Barbara & San Diego State University, California. His research interests are human-computer interaction, individual choice-making behavior, virtual reality, participatory decision making, knowledge discovery and data mining, exploratory data analysis, spatial decision support, and transportation.