Household Online Shopping Demand in the U.S.: A Machine Learning Approach and Comparative Investigation between 2009 and 2017

We leverage unique features from the two latest releases of the National Household Travel Survey (NHTS) data and a machine learning approach to predict household-level online shopping purchases in the US. The modeling and investigation are performed at the national level and for three of the largest cities (New York, Los Angeles, and Houston), with a number of insights obtained.

Speaker: Bo Zhou
Bo Zou is an associate professor in the Department of Civil and Materials Engineering at the University of Illinois at Chicago. He is also a faculty partner of the Center of Excellence for Airport Technology at the University of Illinois at Urbana-Champaign.