James Heyman joined the faculty in 2005. He teaches in both the undergraduate and M.B.A. programs. Heyman's general research analyzes how individuals make judgments when they only have a small amount of information. His current focus is on combining algorithmic complexity and information theory to develop a cost/benefit measure for different forms of survey methods. He has published articles in Psychological Science, Journal of Interactive Marketing, American Behavioral Scientist, Journal of Marketing Communications, Motivation and Emotion, and Assessment & Evaluation in Higher Education. He papers have also been published in the Handbook of Consumer Psychology and Recent Developments in Behavioral Economics.