The Multi-Dimensional Dependencies Among Shared Mobility Service Users

This seminar focuses on the multi-dimensional dependencies that affect the usage of shared mobility services and the frequency of using car-sharing and ride-hailing services. A generalized heterogeneous data model (GHDM) framework that incorporates multi-dimensional dependencies among decision-makers is presented for the Puget Sound Region. The results show that social dependency effects arising from similarities in attitudes and preferences are significant in explaining shared mobility service usage. Ignoring such effects may lead to erroneous estimates of the adoption and usage of future transportation technologies and mobility services.

About the Speaker:

Dr. Chandra R. Bhat is the Director of the Data-Supported Transportation Operations and Planning USDOT Center and the Joe J. King Endowed Chair Professor in Engineering at The University of Texas at Austin, where he has a joint appointment between the Department of Civil, Architectural and Environmental Engineering (CAEE) and the Department of Economics. Bhat is a world-renowned expert in the area of transportation and urban policy design, with far reaching implications for public health, energy dependence, greenhouse gas emissions, and societal quality of life. Methodologically, he has been a pioneer in the formulation and use of statistical and econometric methods to analyze human choice behavior. His current research includes the social and environmental aspects of transportation, planning implications of connected and automated smart transportation systems (CASTS), and data science and predictive analytics. He is a recipient of many awards, including the 2017 Council of University Transportation Center (CUTC) Lifetime Achievement Award in Transportation Research and Education, the 2015 ASCE Frank Masters Award, and the 2013 German Humboldt Award. He was recently listed as the top ten transportation thought leaders in academia by the Eno Foundation. He is also a top-cited transportation engineering researcher, and was listed in the most cited researchers in civil engineering by Shanghai Ranking's global ranking of academic subjects 2016 by Elsevier.