An Alternative Ranking Order Method Accounting for Two-Step Normalization (AROMAN)-A Case Study of the Electric Vehicle Selection Problem
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216275%3A25510%2F23%3A39920310" target="_blank" >RIV/00216275:25510/23:39920310 - isvavai.cz</a>
Result on the web
<a href="https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=10097712" target="_blank" >https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=10097712</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1109/ACCESS.2023.3265818" target="_blank" >10.1109/ACCESS.2023.3265818</a>
Alternative languages
Result language
angličtina
Original language name
An Alternative Ranking Order Method Accounting for Two-Step Normalization (AROMAN)-A Case Study of the Electric Vehicle Selection Problem
Original language description
Decision-making is a ubiquitous and paramount issue in the modern business world. Inappropriate decisions may lead to severe consequences for companies. Considering that the evaluation of alternatives is generally affected by several criteria, decision-making should be considered a very challenging task. From the 1945s to the present day, various multi-criteria decision-making (MCDM) methods have evolved, supporting people in the decision-making process. The main aim of this paper is to propose an original MCDM method and to demonstrate its applicability in an empirical case study that relates to the Electric Vehicle (EV) selection problem. To solve the electric vehicle selection problem for the last-mile delivery, we developed and applied a new MCDM method - the AROMAN (Alternative Ranking Order Method Accounting for Two-Step Normalization) method. The main contribution of the AROMAN method is coupling the linear and vector normalization techniques to obtain precise data structures used in further calculation. In addition, the original final ranking equation is developed. To demonstrate the robustness of the proposed method, a comparative analysis with other state-of-the-art MCDM methods is conducted. The results indicate a high level of confidence in the AROMAN method in the decision-making field. In addition, the sensitivity analysis is performed, and the results indicate a high level of stability. Nevertheless, based on the confident results, the managerial implications have also been indicated.
Czech name
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Czech description
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Classification
Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
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OECD FORD branch
50204 - Business and management
Result continuities
Project
<a href="/en/project/CK01000032" target="_blank" >CK01000032: Smart City Logistics as a Response to Current E-Commerce Trends and Sustainable Urban Mobility Planning</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2023
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
IEEE ACCESS
ISSN
2169-3536
e-ISSN
2169-3536
Volume of the periodical
11
Issue of the periodical within the volume
JAN 2023
Country of publishing house
US - UNITED STATES
Number of pages
12
Pages from-to
39496-39507
UT code for WoS article
000979472600001
EID of the result in the Scopus database
2-s2.0-85153399216