| Title |
Employing bibliometric analysis to identify suitable business models for electric cars |
| ID_Doc |
78384 |
| Authors |
Secinaro, S; Brescia, V; Calandra, D; Biancone, P |
| Title |
Employing bibliometric analysis to identify suitable business models for electric cars |
| Year |
2020 |
| Published |
|
| DOI |
10.1016/j.jclepro.2020.121503 |
| Abstract |
Business model architectures in the car industry are gaining increased attention from scientists and policymakers. Although scientific studies have been conducted to address the pressures faced by future business models to change, no research has examined the bibliometric variables in this area. This study aims to fill the gap by conducting a bibliometric analysis of 104 articles on business models for electric cars. The analysis showed that the literature on business models for electric cars is exhaustive, and it focuses on business model decisions for charging technologies, driver services, electricity management, commercial contracts, and plant. China, the United States of America, and Germany have conducted the maximum number of studies on the aforementioned theme. The topic dendrogram identified two evolving strands of discussionsdinnovative technologies and resource optimization and electricity management systems and product life cycle. These findings can guide the formulation of environmentally sustainable policies for electric car manufacturing and help car manufacturers to restructure their models. (C) 2020 The Authors. Published by Elsevier Ltd. |
| Author Keywords |
Business model; Electric cars; Electricity management; Cost-sharing scheme; Energy policy; Bibliometric |
| Index Keywords |
Index Keywords |
| Document Type |
Other |
| Open Access |
Open Access |
| Source |
Science Citation Index Expanded (SCI-EXPANDED); Social Science Citation Index (SSCI) |
| EID |
WOS:000538390400015 |
| WoS Category |
Green & Sustainable Science & Technology; Engineering, Environmental; Environmental Sciences |
| Research Area |
Science & Technology - Other Topics; Engineering; Environmental Sciences & Ecology |
| PDF |
https://doi.org/10.1016/j.jclepro.2020.121503
|