Early bird pricing now available for the Analytics & Insights Summit 2024!Details
March 28, 2024
1:00 PM ET
Join us on March 28th as we chat with long-time Stanford professor Seenu Srinivasan, who together with the late Paul Green coined the term conjoint analysis in their influential 1978 review paper that became a widely cited classic. Seenu first met Paul in 1970 while Seenu was a PhD student at Carnegie Mellon. At that time, Seenu was working with fellow doctoral student Allan Shocker on a linear programming algorithm, called LINMAP, for estimating utility scores for multi-attribute preference models from paired comparisons. After their 1978 conjoint analysis paper collaboration, Paul and Seenu joint taught a course in Europe on conjoint analysis and MDS scaling in 1979. They followed that up with a second review article in 1990 further describing and critiquing the advances in conjoint analysis in industry. Seenu is the Adams Distinguished Professor of Management, Emeritus at the Stanford Graduate School of Business. He received his undergraduate degree in mechanical engineering in India prior to joining Carnegie Mellon University in the USA where he received both his masters and PhD. His primary research interest in marketing has been in the measurement of customer preferences and its role in product planning and pricing. Seenu was an associate editor of Marketing Science, Journal of Marketing Research, and Management Science. He received the Parlin Award for outstanding contributions to marketing research, the Churchill Award for lifetime achievement in marketing research, the Converse Award for outstanding contributions to the development of the science of marketing, and the Buck Weaver Award for lifetime contributions to the advancement of theory and practice in marketing science. He has received ten best research paper of the year awards. A long-time friend of Sawtooth Software, Seenu has frequently corresponded with us and also presented at a past Sawtooth Software conference on a clever, adaptive online survey-based approach to the scaling of items called ASEMAP (developed with Oded Netzer).