Mixed Method Investigation of the Major Challenges to the Sustainable Deployment of the Electric Vehicle Charging Station Network in Türkiye
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Date
2025
Journal Title
Journal ISSN
Volume Title
Publisher
Taylor & Francis Ltd
Open Access Color
Green Open Access
Yes
OpenAIRE Downloads
OpenAIRE Views
Publicly Funded
No
Abstract
Charging the increasing number of electric vehicles (EVs) in use requires the deployment of EV charging station networks (EVCSN). However, there are various challenges to deploying EVCSN in a sustainable manner. T & uuml;rkiye, a developing country, should also build a robust EVCSN to encourage future adoption of EVs as the country's market for EVs has been rapidly growing. The literature review concludes that no previous study has systematically explored challenges to the sustainable deployment of EVCSN. The goal of this study is, therefore, twofold: first, it identifies those challenges through the lenses of commonly used theories. Second, it explores them using a multi-criteria decision-making (MCDM) framework that incorporates a rough-derived interval-valued neutrosophic set (R-IVN)-based ISM into MICMAC. By deriving interval neutrosophic information from single-valued expert inputs using rough number operators, the proposed approach more accurately captures epistemic uncertainty and variability in expert judgments compared to conventional interval-based models. The method is further validated through a novel Dice-S & oslash;rensen similarity index-based simulation approach. The findings of this study suggest that developing government policies and regulations and addressing the existence of vertically integrated companies are the critical challenges with higher driving powers. These findings provide key responsibilities for stakeholders, including urban municipalities, in developing guidelines for EVCSN deployment.
Description
Benli, Tolga/0000-0003-1028-8573; Erol, İsmail/0000-0003-3327-7068; Öztel, Ahmet/0000-0002-9627-7850
Keywords
Electric Vehicles, Charging Stations, ISM, Dice-S & Oslash, Rensen Similarity Index-Based Simulation, Sustainability, Sustainability, Technology Management, Supply Chain Management
Fields of Science
Citation
WoS Q
Q3
Scopus Q
Q2

OpenCitations Citation Count
N/A
Source
Engineering Management Journal
Volume
Issue
Start Page
1
End Page
34
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Citations
Scopus : 0
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