Driving the Change: How Do Personal Factors and Socio-Economic Context Influence Electric Vehicles Adoption Across Europe? DOI
Valerio Schiaroli, Luca Fraccascia

Published: Jan. 1, 2024

Language: Английский

Beyond conventional: Analysing the factors affecting the adoption of electric four-wheelers in an Indian metropolis DOI
Furqan A. Bhat, Yash Seth, Ashish Verma

et al.

Transportation Research Part D Transport and Environment, Journal Year: 2024, Volume and Issue: 131, P. 104200 - 104200

Published: April 16, 2024

Language: Английский

Citations

6

A decision framework for improving the service quality of charging stations based on online reviews and evolutionary game theory DOI

Shengnan Lv,

Anran Xiao, Yong Qin

et al.

Transportation Research Part A Policy and Practice, Journal Year: 2024, Volume and Issue: 187, P. 104168 - 104168

Published: July 13, 2024

Language: Английский

Citations

5

Assessing optimized time-of-use pricing for electric vehicle charging in deep vehicle-grid integration system DOI
So Young Yang, JongRoul Woo, Wonjong Lee

et al.

Energy Economics, Journal Year: 2024, Volume and Issue: 138, P. 107852 - 107852

Published: Aug. 20, 2024

Language: Английский

Citations

4

Electric vehicle adoption and the energy rebound effect in the transportation sector: evidence from China DOI
Xiaolei Zhao, Xuemei Li, Yumeng Mao

et al.

Transport Policy, Journal Year: 2025, Volume and Issue: unknown

Published: April 1, 2025

Language: Английский

Citations

0

Towards sustainable Transportation: Factors influencing electric vehicle charging stations development DOI
Sudhanshu Ranjan Singh, Abhijeet K. Digalwar, Srikanta Routroy

et al.

Sustainable Energy Technologies and Assessments, Journal Year: 2025, Volume and Issue: 77, P. 104339 - 104339

Published: May 1, 2025

Language: Английский

Citations

0

Understanding the zero-emission vehicle market spatial diffusion and its determinants from 2019 to 2022 using spatial econometric models DOI Creative Commons
Hui Shi, Konstadinos G. Goulias

Energy, Journal Year: 2024, Volume and Issue: unknown, P. 133607 - 133607

Published: Oct. 1, 2024

Language: Английский

Citations

3

Are past ownership experience and satisfaction major determinants of endorsement and future demand for zero emission vehicle technology when accounting for vehicle characteristics? DOI Creative Commons
Hui Shi, Konstadinos G. Goulias

Research in Transportation Economics, Journal Year: 2025, Volume and Issue: 110, P. 101535 - 101535

Published: March 5, 2025

Language: Английский

Citations

0

What drives the adoption of electric four-wheelers in India? An investigation of the reasons for and against DOI
Furqan A. Bhat, Ashish Verma

Travel Behaviour and Society, Journal Year: 2025, Volume and Issue: 40, P. 101016 - 101016

Published: March 18, 2025

Language: Английский

Citations

0

Self-reported public fast charging infrastructure demand: what do existing and potential electric vehicle adopters want and where? DOI
Ubaid Illahi, Robert Egan, Margaret O’Mahony

et al.

Sustainable Cities and Society, Journal Year: 2024, Volume and Issue: unknown, P. 105935 - 105935

Published: Oct. 1, 2024

Language: Английский

Citations

1

Modeling of the Acceptable Waiting Time for EV Charging in Japan DOI Open Access

Umm e Hanni,

Toshiyuki Yamamoto, Toshiyuki Nakamura

et al.

Sustainability, Journal Year: 2024, Volume and Issue: 16(6), P. 2536 - 2536

Published: March 20, 2024

The limited number of charging stations for electric vehicles (EVs) necessitates periodic charging, resulting in extended queues at as drivers await their availability. This study contributes to the existing body literature by providing estimates consumer preferences allowable waiting times stations, well furthering understanding roles explanatory variables influencing these preferences. also compares average and maximum experienced EV drivers, with acceptable time. Responses from stated preference survey Japan 2021 were analyzed using a generalized ordered logit model. results show that (a) sex, age, household income, employment status, vehicle usage frequency significantly influenced times, (b) time associated locations. Our estimation model indicated positive association convenience stores, large commercial facilities, highway locations short medium times. provide useful insights into policy implications infrastructure.

Language: Английский

Citations

0