2025
Decision-Making on Key Factors Driving the Demand for Electric Vehicles
STOPKA, Ondrej; Vladimír ĽUPTÁK; Anna BORUCKA; Mária STOPKOVÁ; Branislav ŠARKAN et al.Základní údaje
Originální název
Decision-Making on Key Factors Driving the Demand for Electric Vehicles
Autoři
Vydání
Applied Sciences (Basel), 2025, 2076-3417
Další údaje
Jazyk
angličtina
Typ výsledku
Článek v odborném periodiku
Obor
50703 Transport planning and social aspects of transport
Stát vydavatele
Švýcarsko
Utajení
není předmětem státního či obchodního tajemství
Odkazy
Impakt faktor
Impact factor: 2.500 v roce 2024
Označené pro přenos do RIV
Ano
Kód RIV
RIV/75081431:_____/25:00002872
Organizační jednotka
Vysoká škola technická a ekonomická v Českých Budějovicích
UT WoS
Klíčová slova anglicky
multi-criteria decision-making; PROMETHEE II; ELECTRE I; sustainability; mobility; electromobility; electric van
Štítky
Návaznosti
LUABA24085, projekt VaV.
Změněno: 19. 5. 2025 11:57, Ing. Barbora Langšádlová
Anotace
V originále
The article presents a research study dealing with the issue of identifying the crucial criteria driving the demand for electric vehicles and decision-making on the ideal electric vehicle choice for the company under investigation. Specifically, the research aimed to identify key factors influencing the decision-making process to purchase electric vans and to propose adequate recommendations when applying adequate multi-criteria decision-making methods, namely, ELECTRE I and PROMETHEE II, in the Czech and Slovak market conditions. The present survey identified six key criteria: mileage, load-carrying capacity, recharging speed, purchase price, load-bearing capacity, and electricity consumption. Based on the expert team preferences, the criteria weights were calculated, followed by data normalization and the application of both methods to evaluate individual vehicle models. Using the ELECTRE I method, the options were classified as either preferred (dominant) or unpreferred (undominant), while the PROMETHEE II ranked them from the best to the worst, preserving viable alternatives should the preferred model be unavailable. The study concludes by emphasizing the relevance of these methods in optimizing the selection of sustainable transport solutions and their broader applicability in the decision-making process on transport and mobility.