-
Institution:
商学院
-
Title of Paper:
A Structured Review of Electric Vehicle Sales Research: Multi-Level Driving Factors and Forecasting Pathways over the Past Decade
-
Teaching and Research Group:
管理学系
-
Journal:
World Electric Vehicle Journal
-
Place of Publication:
SWIZLAND
-
Project Source:
This research was funded by National Social Science Fund of China (Project No. 25BGL010).
-
Key Words:
electric vehicle sales; influencing factors; sales forecasting; feature selection
-
Summary:
Under dual-carbon targets, electric vehicles (EVs) have become central to transport decarbonization, making EV sales a key indicator of market diffusion and policy effectiveness. Despite the growing body of research, studies on EV sales remain fragmented and lack systematic integration. This study provides a structured review of EV sales research published between 2016 and 2025. Based on searches in Scopus and Web of Science, 1518 records were identified, and 194 peer-reviewed journal articles were retained after a multi-stage screening process. Temporal analysis reveals a clear stage-based evolution of EV sales research, with limited publications prior to 2020 and a marked expansion after 2021. The literature is categorized into two main streams: (i) determinants of EV sales and (ii) forecasting approaches. For determinants, a macro–meso–micro analytical framework is developed to organize policy, market, and behavioral factors. For forecasting, quantitative analysis shows that econometric and statistical models remain dominant (54%), while machine learning (18%), behavior simulation (14%), hybrid models (8%), and deep learning (4%) are increasingly adopted. This indicates a gradual shift toward data-driven and model integration approaches. This review offers a structured synthesis of determinant mechanisms and forecasting paradigms, identifies methodological imbalances, and outlines future research directions toward improved multi-level integration and mechanism-based modeling of EV sales dynamics.
-
Note:
World Electr. Veh. J. 2026, 17(3), 122; https://doi.org/10.3390/wevj17030122
JCR - Q2 (Engineering, Electrical and Electronic) / CiteScore - Q2 (Automotive Engineering)
-
Document Code:
wevj17030122
-
Volume:
17
-
Issue:
3
-
Page Number:
122-161
-
Impact Factor:
2.6
-
Number of Words:
15621
-
Translation or Not:
No
-
Date of Publication:
2026-02
-
Included Journals:
SSCI、EI、SCI
-
Links to Published Journals:
-
Release Time:
2026-02-28
