TY - GEN
T1 - Plug-in Electric Vehicle (PEV) Adoption in U.S. Transport for Policy
AU - Wang, Yiyi
AU - Hewitt, Elizabeth L.
N1 - Publisher Copyright: © 2019 IEEE.
PY - 2019/10
Y1 - 2019/10
N2 - Despite a noteworthy uptake of Plug-in Electric Vehicles (PEV s) in a short time frame and governmental strategies to encourage use, the adoption of PEV s is still a challenge. This study views the adoption of PEVs as one pathway towards more sustainable transportation and lower Greenhouse Gas (GHG) emissions, and explores demographic factors that can be attributed to household-level PEV adoption. An aim of this study is to estimate nationwide adoption patterns in the U.S. and explore public sector strategies and innovation policies to accelerate PEV adoption. Multiple Logistic Regression Analysis is applied to the 2015 Residential Energy Consumption Survey (RECS) dataset. The model explored a broad set of variables including electricity consumption choices, participation in energy-efficiency programs, and demographic characteristics to explore the relationships between PEV adoption and potentially influential factors. Findings indicated that PEV adoption is correlated with a household's income level, the use of home solar technology, and the electricity consumption from backup generator. A better understanding of individual adopter characteristics that are correlated with PEV adoption can inform policy for optimizing feasible strategies to accelerate PEV adoption in the U.S. Keywords: Plug-in Electric Vehicle Adoption, RECS, Demographic characteristics.
AB - Despite a noteworthy uptake of Plug-in Electric Vehicles (PEV s) in a short time frame and governmental strategies to encourage use, the adoption of PEV s is still a challenge. This study views the adoption of PEVs as one pathway towards more sustainable transportation and lower Greenhouse Gas (GHG) emissions, and explores demographic factors that can be attributed to household-level PEV adoption. An aim of this study is to estimate nationwide adoption patterns in the U.S. and explore public sector strategies and innovation policies to accelerate PEV adoption. Multiple Logistic Regression Analysis is applied to the 2015 Residential Energy Consumption Survey (RECS) dataset. The model explored a broad set of variables including electricity consumption choices, participation in energy-efficiency programs, and demographic characteristics to explore the relationships between PEV adoption and potentially influential factors. Findings indicated that PEV adoption is correlated with a household's income level, the use of home solar technology, and the electricity consumption from backup generator. A better understanding of individual adopter characteristics that are correlated with PEV adoption can inform policy for optimizing feasible strategies to accelerate PEV adoption in the U.S. Keywords: Plug-in Electric Vehicle Adoption, RECS, Demographic characteristics.
UR - https://www.scopus.com/pages/publications/85082464048
U2 - 10.1109/IESC47067.2019.8976770
DO - 10.1109/IESC47067.2019.8976770
M3 - Conference contribution
T3 - 2019 International Energy and Sustainability Conference, IESC 2019
BT - 2019 International Energy and Sustainability Conference, IESC 2019
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2019 International Energy and Sustainability Conference, IESC 2019
Y2 - 17 October 2019 through 18 October 2019
ER -