Speaker: Chandra Bhat, Ph.D., P.E. (The University of Texas at Austin)
Title: A Model of Electric Vehicle Adoption and Motivating Reasons for Adoption
Date: 19th March 2025
Time: 10:30
Place: EA409
Bio:
Dr. Chandra R. Bhat has been a pioneer in the formulation and use of statistical and econometric methods to analyze human choice behavior for transportation and urban policy design. He is a recipient of many awards, including the 2017 Council of University Transportation Centers (CUTC) Lifetime Achievement Award, the 2015 American Society of Civil Engineers (ASCE) Frank M. Masters Award, and the 2013 German Humboldt Award. He was listed in 2017 as one of the top ten transportation thought leaders in academia by the Eno Foundation. He received the 2022 Theodore Matson Memorial Award from the Institute of Transportation Engineers (ITE). More recently, he was awarded the 2024 W.N. Carey, Jr., Distinguished Service Award “for leadership and distinguished service to the Transportation Research Board (TRB)”. Chandra also has been ranked in the top three scientists globally in the subject area of transport and logistics. Dr. Bhat currently serves as the Editor-in-Chief of Transportation Research – Part B. He is the immediate past-President of the ASCE Transportation and Development Institute (T&DI).
Abstract:
Electric vehicles (EVs) have broad potential to mitigate climate change and can provide significant benefits for individual owners, but adoption rates have, thus far, remained relatively low. While there is interest in understanding adoption patterns through a study of actual individual-level adoption behaviors, the nascent stage of the EV market has made such investigations difficult. In particular, many existing EV adoption studies are confined to an examination stated adoption intentions rather than actual revealed adoption behaviors. Accordingly, we examine the ways that demographics, lifestyle preferences, and perceptions of EV characteristics impact revealed EV adoption behaviors. In addition to the binary EV adoption decision, using information elicited from a survey in California that asked current EV owners to rank the importance of a set of factors that influenced their adoption decision, we investigate the motivations for EV ownership. Our analytic approach, a first in the EV literature as well as (to our knowledge) in the broader econometric literature (where an outcome is rank-ordered with a binary selection mechanism), provides important insights for the implementation of EV incentive policies, the deployment of EVs, and the development of EV charging infrastructure.