Forecasting Methods for the Electric Vehicle Ownership: A Literature Review

Bunga Kharissa Laras Kemala; Isti Surjandari; Angella Natalia Ghea Puspita

doi:10.1016/j.procs.2024.02.155

Forecasting Methods for the Electric Vehicle Ownership: A Literature Review

Bunga Kharissa Laras Kemala, Isti Surjandari, Angella Natalia Ghea Puspita

Department of Industrial Engineering

Research output: Contribution to journal › Conference article › peer-review

1 Citation (Scopus)

Abstract

The sustainability issue in the transportation sector brings the electric vehicle (EV) as a new promising solution for reducing carbon emissions. However, the EV adoption faces issues regarding range, recharging time, and high initial investment. To enhance the adoption, supporting infrastructures should be planned. Therefore, forecasting the growth of EV adoption becomes important to help industries and government in strategic decision making. This paper provides a literature review about forecasting methods in EV ownership, which includes studies from 2011 to March 2023. This will contribute to highlight the current methods and stimulating more developments of forecasting methods related to EV ownership.

Original language	English
Pages (from-to)	87-95
Number of pages	9
Journal	Procedia Computer Science
Volume	234
DOIs	https://doi.org/10.1016/j.procs.2024.02.155
Publication status	Published - 2024
Event	7th Information Systems International Conference, ISICO 2023 - Washington, United States Duration: 26 Jul 2023 → 28 Jul 2023

Keywords

Electric Vehicle
EV ownership forecasting
EV sales forecasting
forecasting
systematic literature review

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10.1016/j.procs.2024.02.155

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title = "Forecasting Methods for the Electric Vehicle Ownership: A Literature Review",

abstract = "The sustainability issue in the transportation sector brings the electric vehicle (EV) as a new promising solution for reducing carbon emissions. However, the EV adoption faces issues regarding range, recharging time, and high initial investment. To enhance the adoption, supporting infrastructures should be planned. Therefore, forecasting the growth of EV adoption becomes important to help industries and government in strategic decision making. This paper provides a literature review about forecasting methods in EV ownership, which includes studies from 2011 to March 2023. This will contribute to highlight the current methods and stimulating more developments of forecasting methods related to EV ownership.",

keywords = "Electric Vehicle, EV ownership forecasting, EV sales forecasting, forecasting, systematic literature review",

author = "Kemala, {Bunga Kharissa Laras} and Isti Surjandari and Puspita, {Angella Natalia Ghea}",

note = "Publisher Copyright: {\textcopyright} 2023 The Authors. Published by Elsevier B.V.; 7th Information Systems International Conference, ISICO 2023 ; Conference date: 26-07-2023 Through 28-07-2023",

year = "2024",

doi = "10.1016/j.procs.2024.02.155",

language = "English",

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journal = "Procedia Computer Science",

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T2 - 7th Information Systems International Conference, ISICO 2023

AU - Kemala, Bunga Kharissa Laras

AU - Surjandari, Isti

AU - Puspita, Angella Natalia Ghea

PY - 2024

Y1 - 2024

N2 - The sustainability issue in the transportation sector brings the electric vehicle (EV) as a new promising solution for reducing carbon emissions. However, the EV adoption faces issues regarding range, recharging time, and high initial investment. To enhance the adoption, supporting infrastructures should be planned. Therefore, forecasting the growth of EV adoption becomes important to help industries and government in strategic decision making. This paper provides a literature review about forecasting methods in EV ownership, which includes studies from 2011 to March 2023. This will contribute to highlight the current methods and stimulating more developments of forecasting methods related to EV ownership.

AB - The sustainability issue in the transportation sector brings the electric vehicle (EV) as a new promising solution for reducing carbon emissions. However, the EV adoption faces issues regarding range, recharging time, and high initial investment. To enhance the adoption, supporting infrastructures should be planned. Therefore, forecasting the growth of EV adoption becomes important to help industries and government in strategic decision making. This paper provides a literature review about forecasting methods in EV ownership, which includes studies from 2011 to March 2023. This will contribute to highlight the current methods and stimulating more developments of forecasting methods related to EV ownership.

KW - Electric Vehicle

KW - EV ownership forecasting

KW - EV sales forecasting

KW - forecasting

KW - systematic literature review

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M3 - Conference article

AN - SCOPUS:85193201214

SN - 1877-0509

VL - 234

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EP - 95

JO - Procedia Computer Science

JF - Procedia Computer Science

Y2 - 26 July 2023 through 28 July 2023

ER -

Forecasting Methods for the Electric Vehicle Ownership: A Literature Review

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Keywords

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