A Stakeholder-Driven Fuzzy Analytic Hierarchy Process Framework for Sustainable Battery Selection in Hybrid Electric Vehicles

Hybrid Electric Vehicles (HEVs) are recognized as one of the effective technologies for reducing fuel consumption and greenhouse gas emissions. However, selecting the most suitable battery technology requires balancing technical performance, manufacturing feasibility, customer expectations, resource security, and sustainability objectives. Existing studies primarily evaluate battery technologies from technical, economic, or environmental perspectives independently, with limited consideration of stakeholder conflicts and trade-offs. Therefore, this study develops a stakeholder-driven Fuzzy Analytic Hierarchy Process (FAHP) framework to evaluate Nickel–Metal Hydride (NiMH) and Lithium-Ion (LIB) batteries for HEV applications. The framework integrates three key stakeholder groups: final customers, vehicle manufacturers (OEMs), and society and policymakers, and evaluates battery technologies using four criteria: Customer Value, Technical and Commercial Performance, Production Feasibility, and Resource Security and Social Responsibility. The results indicate that OEMs are the most influential stakeholders (54.30%), followed by final customers (24.81%) and society and policymakers (20.89%). Overall, NiMH achieved the highest score (53.10%), outperforming LIB (46.90%) because of its superior production feasibility and resource security, despite LIB’s higher technical performance. Sensitivity analysis under equal-criteria and equal-stakeholder weighting scenarios confirmed the stability of the rankings.

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Publication Details

Journal
World Electric Vehicle Journal
Published
2026-10-16
DOI
https://doi.org/10.3390/wevj17100531
Primary Topic
Multi-Criteria Decision Making
Type
article
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article

A Stakeholder-Driven Fuzzy Analytic Hierarchy Process Framework for Sustainable Battery Selection in Hybrid Electric Vehicles

Waleed Al‐Nuaimy, Khaled Hossin, Hussain Attia, Muataz Hazza Faizi Al Hazza et al.
World Electric Vehicle Journal
Multi-Criteria Decision Making
article

A Stakeholder-Driven Fuzzy Analytic Hierarchy Process Framework for Sustainable Battery Selection in Hybrid Electric Vehicles

Waleed Al‐Nuaimy, Khaled Hossin, Hussain Attia, Muataz Hazza Faizi Al Hazza, Ali Al-Ataby
article en

Abstract

Hybrid Electric Vehicles (HEVs) are recognized as one of the effective technologies for reducing fuel consumption and greenhouse gas emissions. However, selecting the most suitable battery technology requires balancing technical performance, manufacturing feasibility, customer expectations, resource security, and sustainability objectives. Existing studies primarily evaluate battery technologies from technical, economic, or environmental perspectives independently, with limited consideration of stakeholder conflicts and trade-offs. Therefore, this study develops a stakeholder-driven Fuzzy Analytic Hierarchy Process (FAHP) framework to evaluate Nickel–Metal Hydride (NiMH) and Lithium-Ion (LIB) batteries for HEV applications. The framework integrates three key stakeholder groups: final customers, vehicle manufacturers (OEMs), and society and policymakers, and evaluates battery technologies using four criteria: Customer Value, Technical and Commercial Performance, Production Feasibility, and Resource Security and Social Responsibility. The results indicate that OEMs are the most influential stakeholders (54.30%), followed by final customers (24.81%) and society and policymakers (20.89%). Overall, NiMH achieved the highest score (53.10%), outperforming LIB (46.90%) because of its superior production feasibility and resource security, despite LIB’s higher technical performance. Sensitivity analysis under equal-criteria and equal-stakeholder weighting scenarios confirmed the stability of the rankings.

World Electric Vehicle JournalVol. 17(10)
University of Liverpool (GB), American University of Ras Al Khaimah (AE)
Affordable and clean energy, Industry, innovation and infrastructure
Openalex Percentile: Top 9%
Multi-Criteria Decision Making
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