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Do I need to charge right now? Tailored choice architecture design can increase preferences for electric vehicle smart charging

Publikation: Beiträge in Zeitschriften › Zeitschriftenaufsätze › Forschung › begutachtet

Standard

Do I need to charge right now? Tailored choice architecture design can increase preferences for electric vehicle smart charging. / Lagomarsino, Maria; van der Kam, Mart; Parra, David et al.
in: Energy Policy, Jahrgang 162, 112818, 03.2022.

Publikation: Beiträge in Zeitschriften › Zeitschriftenaufsätze › Forschung › begutachtet

Harvard

Lagomarsino, M, van der Kam, M, Parra, D & Hahnel, UJJ 2022, 'Do I need to charge right now? Tailored choice architecture design can increase preferences for electric vehicle smart charging', Energy Policy, Jg. 162, 112818. https://doi.org/10.1016/j.enpol.2022.112818

APA

Lagomarsino, M., van der Kam, M., Parra, D., & Hahnel, U. J. J. (2022). Do I need to charge right now? Tailored choice architecture design can increase preferences for electric vehicle smart charging. Energy Policy, 162, Artikel 112818. https://doi.org/10.1016/j.enpol.2022.112818

Vancouver

Lagomarsino M, van der Kam M, Parra D, Hahnel UJJ. Do I need to charge right now? Tailored choice architecture design can increase preferences for electric vehicle smart charging. Energy Policy. 2022 Mär;162:112818. doi: 10.1016/j.enpol.2022.112818

Bibtex

@article{da3ffd93ca4d48139e9bfe810962ba46,
title = "Do I need to charge right now? Tailored choice architecture design can increase preferences for electric vehicle smart charging",
abstract = "The increasing diffusion of electric vehicles (EVs) can challenge the stability of distribution grids. Smart charging systems can reduce the stress of EV charging on the grid, but the potential of the technology depends on EV drivers' participation in smart charging schemes. To investigate this potential, we conducted an online randomised-controlled experiment with two waves (baseline and experimental phase, N = 222), in which we examined drivers' preferences for smart charging and tested a behavioral intervention to increase the number of smart charging choices. We translated state-of-charge (SoC) information from percentage of battery level into miles corresponding to the battery level and tailored information, i.e., the number of driving days covered by the actual SoC based on participants{\textquoteright} personal driving profiles. Participants preferred to use smart charging systems to decrease costs and to increase renewable energy use. However, they tended to overestimate the importance of the battery SoC when setting charging preferences. This overestimation was especially evident for participants who only drive short distances and may be lead to inefficient use of smart charging technology. Translating battery SoC into tailored information corrected for this bias and increased the number of smart charging choices. Our findings illustrate how behavioral interventions can be leveraged to attain energy transition goals.",
keywords = "Behavioral insights strategies, Choice architecture, Decision-making, EV, Smart charging, Tailored information, Psychology",
author = "Maria Lagomarsino and {van der Kam}, Mart and David Parra and Hahnel, {Ulf J.J.}",
note = "Publisher Copyright: {\textcopyright} 2022 The Authors",
year = "2022",
month = mar,
doi = "10.1016/j.enpol.2022.112818",
language = "English",
volume = "162",
journal = "Energy Policy",
issn = "0301-4215",
publisher = "Elsevier B.V.",

}

RIS

TY - JOUR

T1 - Do I need to charge right now? Tailored choice architecture design can increase preferences for electric vehicle smart charging

AU - Lagomarsino, Maria

AU - van der Kam, Mart

AU - Parra, David

AU - Hahnel, Ulf J.J.

N1 - Publisher Copyright: © 2022 The Authors

PY - 2022/3

Y1 - 2022/3

N2 - The increasing diffusion of electric vehicles (EVs) can challenge the stability of distribution grids. Smart charging systems can reduce the stress of EV charging on the grid, but the potential of the technology depends on EV drivers' participation in smart charging schemes. To investigate this potential, we conducted an online randomised-controlled experiment with two waves (baseline and experimental phase, N = 222), in which we examined drivers' preferences for smart charging and tested a behavioral intervention to increase the number of smart charging choices. We translated state-of-charge (SoC) information from percentage of battery level into miles corresponding to the battery level and tailored information, i.e., the number of driving days covered by the actual SoC based on participants’ personal driving profiles. Participants preferred to use smart charging systems to decrease costs and to increase renewable energy use. However, they tended to overestimate the importance of the battery SoC when setting charging preferences. This overestimation was especially evident for participants who only drive short distances and may be lead to inefficient use of smart charging technology. Translating battery SoC into tailored information corrected for this bias and increased the number of smart charging choices. Our findings illustrate how behavioral interventions can be leveraged to attain energy transition goals.

AB - The increasing diffusion of electric vehicles (EVs) can challenge the stability of distribution grids. Smart charging systems can reduce the stress of EV charging on the grid, but the potential of the technology depends on EV drivers' participation in smart charging schemes. To investigate this potential, we conducted an online randomised-controlled experiment with two waves (baseline and experimental phase, N = 222), in which we examined drivers' preferences for smart charging and tested a behavioral intervention to increase the number of smart charging choices. We translated state-of-charge (SoC) information from percentage of battery level into miles corresponding to the battery level and tailored information, i.e., the number of driving days covered by the actual SoC based on participants’ personal driving profiles. Participants preferred to use smart charging systems to decrease costs and to increase renewable energy use. However, they tended to overestimate the importance of the battery SoC when setting charging preferences. This overestimation was especially evident for participants who only drive short distances and may be lead to inefficient use of smart charging technology. Translating battery SoC into tailored information corrected for this bias and increased the number of smart charging choices. Our findings illustrate how behavioral interventions can be leveraged to attain energy transition goals.

KW - Behavioral insights strategies

KW - Choice architecture

KW - Decision-making

KW - EV

KW - Smart charging

KW - Tailored information

KW - Psychology

UR - http://www.scopus.com/inward/record.url?scp=85123750721&partnerID=8YFLogxK

U2 - 10.1016/j.enpol.2022.112818

DO - 10.1016/j.enpol.2022.112818

M3 - Journal articles

AN - SCOPUS:85123750721

VL - 162

JO - Energy Policy

JF - Energy Policy

SN - 0301-4215

M1 - 112818

ER -

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