A New Rough Ordinal Priority-Based Decision Support System For Purchasing Electric Vehicles

Authors

Sadik Kucuksari, University of Northern IowaFollow
Dragan Pamucar, University of BelgradeFollow
Muhammet Deveci, Milli Savunma ÜniversitesiFollow
Nuh Erdogan, Nottingham Trent University
Dursun Delen, Spears School of Business at Oklahoma State University

Comments

First published in Information Sciences v.647 (2023) by Elsevier B.V. DOI: https://doi.org/10.1016/j.ins.2023.119443

Document Type

Article

Keywords

Bonferroni function, Decision support systems, Electric mobility, Electric vehicle adoption, Multi-criteria decision-making, Rough numbers

Journal/Book/Conference Title

Information Sciences

Volume

647

Abstract

This study proposes a novel multi-criteria decision-making (MCDM) model based on a rough extension of the Ordinal Priority Approach (OPA) to determine the order of importance of users' perspectives on Electric Vehicle (EV) purchases. Unlike conventional methods that rely on predefined ranks for criteria weighting coefficients, the proposed rough OPA method employs an aggregated rough linguistic matrix, enabling a more precise and unbiased calculation of interval values. Moreover, the model addresses inherent uncertainties by incorporating nonlinear aggregation functions, accommodating decision makers' risk attitudes for flexible decision-making. To validate the model's efficacy, a large-scale post-EV test drive survey is conducted, enabling the determination of relative criterion importance. Sensitivity analysis confirms the robustness of the model, demonstrating that marginal changes in parameters do not alter the ranking order. The results unveil the significance of the reliability criterion and reveal that vehicle-related characteristics outweigh economic and environmental attributes in the decision-making process. Overall, this innovative MCDM model contributes to a more accurate and objective analysis, enhancing the understanding of users' preferences and supporting informed decision-making in EV purchases.

Department

Department of Applied Engineering and Technical Management

Original Publication Date

11-1-2023

Object Description

1 PDF File

DOI of published version

10.1016/j.ins.2023.119443

Repository

UNI ScholarWorks, Rod Library, University of Northern Iowa

Copyright

©2023 The Authors. CC BY 4.0 License

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

Language

en

File Format

application/pdf

Recommended Citation

Kucuksari, Sadik; Pamucar, Dragan; Deveci, Muhammet; Erdogan, Nuh; and Delen, Dursun, "A New Rough Ordinal Priority-Based Decision Support System For Purchasing Electric Vehicles" (2023). Faculty Publications. 5411.
https://scholarworks.uni.edu/facpub/5411