TBD Center Director Chandra Bhat and TBD PhD student Dale Robbennolt have received the Andrew Daly Award for the Most Innovative Application of Choice Modelling at the 9th International Choice Modelling Conference (ICMC 2026), held July 20–22, 2026, on the Gold Coast, Australia. The award recognizes the conference paper judged to make the most innovative contribution to the application of choice modelling.
The award-winning paper, “A Flexible Multinomial YJ-Based Model with Non-Normal Random Coefficients and Non-Normal Kernel Error Terms,” which is based on research funded by the U.S. Department of Transportation through the National Center for Understanding Future Travel Behavior and Demand (TBD), develops a new and highly flexible way of modeling how people make choices when their preferences and decision-making patterns are considerably more varied and complex than conventional statistical models typically assume. The broader significance is that choice models underpin forecasts and policy analyses in a remarkable variety of fields, from how people travel and what products they buy to health-care decisions, environmental choices, energy use, and adoption of new technologies. If the models impose inappropriate assumptions about how preferences vary across people, the resulting behavioral conclusions, forecasts, and policy recommendations can be distorted. framework provides substantially greater flexibility for representing this heterogeneity while retaining a tractable modeling structure.
ICMC is the premier international conference dedicated to advances in choice modelling. An important aspect of the conference is its strongly interdisciplinary character. As choice modelling provides methods for understanding how people make decisions, the research presented at ICMC extends well beyond transportation. This year’s program included applications in health and health economics, medicine and public health, marketing and consumer behavior, environmental and climate policy, energy, tourism, economics, psychology and behavioral decision-making, urban and residential choice, transportation and mobility, and public policy, as well as advances involving artificial intelligence, machine learning, experimental design, and statistical and econometric methodology.
The paper is available on Dr. Bhat’s website:
Bhat, C.R., and D. Robbennolt (2026). A Flexible Multinomial YJ-Based Model with Non-Normal Random Coefficients and Non-Normal Kernel Error Terms.
📄 Paper (PDF): http://caee.webhost.utexas.edu/prof/bhat/ABSTRACTS/MNYJ.pdf