Selection of EVs as Tourist and Logistic Means of Transportation in Bosnia and Herzegovina’s Nature Protected Areas Using Z-Number and Rough Set Modeling

Table 1

EV selection problems, an overview of various approaches and methods.

Author	Objective	Method
Biswas and Das [18]	Selection of BEVs	Fuzzy AHP, MABAC
Biswas et al. [19]	EV evaluation under sustainable automotive environment	CoCoSo, CRITIC
Loganathan et al. [20]	Advanced battery technologies selection	MCDM-WPM
Babar et al. [21]	Viability of EV in the current market	Fuzzy SWOT, fuzzy LP
Büyüközkan and Uztürk [22]	Sustainable urban logistics	SAW, VIKOR
Hamurcu and Eren [23]	Electric bus selection	AHP, TOPSIS
Khan et al. [24]	HEV selection	TOPSIS
Ziemba [25]	EV selection for government use	PROSA-C, Monte Carlo
Ecer [26]	Comprehensively assessing BEV alternatives	SECA, MARCOS, MAIRCA, COCOSO, ARAS, COPRAS
Khan and Ali [27]	Smart waste management adoption framework	Fuzzy SWARA, fuzzy VIKTOR
Ren et al. [28]	Selection strategies for BEVs	LDA, DEMATEL, DANP, VIKTOR
Ziemba [29]	Selection of city and compact EVs	NEAT F-PROMETHEE
Ziemba [30]	Analysis and recommendation of the EV	Monte Carlo, fuzzy TOPSIS, fuzzy SAW, NEAT F-PROMETHEE II
Hamurcu and Eren [31]	EV selection for transportation in inner city	AHP, GP, TOPSIS
He [32]	Selection of battery electric bus	EWM
Oztaysi et al. [33]	EV selection problem	F-SMART
Ozdagoglu et al. [34]	Bus selection for intercity transportation	PIPRECIA, COPRAS-G
Stopka et al. [35]	Evaluation of selected passenger EVs	AHP
Štilić et al. [36]	Taxi service EV selection	SWARA, MSDM, MABAC
Wei and Zhou [37]	EV supplier selection	BWM, fuzzy VIKOR
Ziemba and Gago [38]	Selection and analysis of e-scooters	PROMETHEE GDSS, GAIA
Puška et al. [39]	EV selection	DNMEREC, DNCRADIS
Bączkiewicz and Wątróbski [40]	EV selection	Entropy, standard deviation (SD), CRITIC, Gini coefficient-based, MEREC, statistical variance, CILOS, IDOCRIW, VIKOR
Dwivedi and Sharma [41]	EV selection	Entropy, TOPSIS