Expert Evaluation of the Significance of Criteria for Electric Vehicle Deployment: A Case Study of Lithuania DOI Creative Commons
Henrikas Sivilevičius, Vidas Žuraulis, Justas Bražiūnas

et al.

Smart Cities, Journal Year: 2024, Volume and Issue: 7(4), P. 2208 - 2231

Published: Aug. 3, 2024

This study presents the hierarchical structure of 50 sub-criteria divided into 7 main criteria for assessment electric vehicle (EV) deployment. Two options, Average Rank Transformations and Analytic Hierarchy Process methods, were applied in determining local weights sub-criteria. The sufficient compatibility expert opinions was accomplished using averages ranks as result solving problem. calculated employing three Multiple Criteria Decision-Making methods that increased reliability research results. Based on this, global priorities evaluated. experts suppose EV deployment at national level is mainly affected by higher cost manufacturing purchasing EVs, application financial incentives lack exhausted gasses, installation fast charging points, absence infrastructure five largest cities nationwide. obtained results demonstrate out sub-criteria, cumulative weight 10 most important (mainly based economics) amounts to more than 35%, whereas 22 have a above average (0.2), reaching approximately 65%. findings can be put practice state decision makers

Language: Английский

Socially Sustainable Mobility as a Service (MaaS): A practical MCDM framework to evaluate accessibility and inclusivity with application DOI Creative Commons
Nima Dadashzadeh, Seda Sucu, Kate Pangbourne

et al.

Cities, Journal Year: 2024, Volume and Issue: 154, P. 105360 - 105360

Published: Aug. 20, 2024

Language: Английский

Citations

10
A framework for ranking potential cities for implementing emerging urban mobility technologies: A case study for eVTOL aircraft DOI
Felix Spühler,

Kristian Siebenrock,

Ivan Terekhov

et al.

Journal of Urban Mobility, Journal Year: 2025, Volume and Issue: 7, P. 100102 - 100102

Published: Feb. 2, 2025

Language: Английский

Citations

1
Modular AI agents for transportation surveys and interviews: Advancing engagement, transparency, and cost efficiency DOI
Jiangbo Yu, Jianning Zhao, Luis Miranda-Moreno

et al.

Communications in Transportation Research, Journal Year: 2025, Volume and Issue: 5, P. 100172 - 100172

Published: March 24, 2025

Language: Английский

Citations

1
Stakeholders’ viewpoints analysis on mobility as a service using the MAMCA and the fuzzy AHP method DOI
Willy Kriswardhana, Domokos Esztergár-Kiss

Journal of Urban Mobility, Journal Year: 2025, Volume and Issue: 7, P. 100121 - 100121

Published: April 26, 2025

Language: Английский

Citations

0
Equity implications of emerging mobility services and public transit coopetition: A review DOI Creative Commons

Abebe Dress Beza,

Merkebe Getachew Demissie, Lina Kattan

et al.

Transportation Research Part D Transport and Environment, Journal Year: 2025, Volume and Issue: 144, P. 104751 - 104751

Published: April 26, 2025

Language: Английский

Citations

0
Expert Evaluation of the Significance of Criteria for Electric Vehicle Deployment: A Case Study of Lithuania DOI Creative Commons
Henrikas Sivilevičius, Vidas Žuraulis, Justas Bražiūnas

et al.

Smart Cities, Journal Year: 2024, Volume and Issue: 7(4), P. 2208 - 2231

Published: Aug. 3, 2024

This study presents the hierarchical structure of 50 sub-criteria divided into 7 main criteria for assessment electric vehicle (EV) deployment. Two options, Average Rank Transformations and Analytic Hierarchy Process methods, were applied in determining local weights sub-criteria. The sufficient compatibility expert opinions was accomplished using averages ranks as result solving problem. calculated employing three Multiple Criteria Decision-Making methods that increased reliability research results. Based on this, global priorities evaluated. experts suppose EV deployment at national level is mainly affected by higher cost manufacturing purchasing EVs, application financial incentives lack exhausted gasses, installation fast charging points, absence infrastructure five largest cities nationwide. obtained results demonstrate out sub-criteria, cumulative weight 10 most important (mainly based economics) amounts to more than 35%, whereas 22 have a above average (0.2), reaching approximately 65%. findings can be put practice state decision makers

Language: Английский

Citations

1