The influence of weight change of C51-C54 on Q.

<div><p>Current mobility trend indicates that the number of private cars will decline in the near future. One of the reasons for this trend is the development of Mobility as a Service (MaaS), which in conjunction with information and communication technologies (ICT) drive the application of transport services in smart city, respond to environmental issues, and provide users with reliable mobility. Electric vehicle sharing (EVS) travel has been regarded as a feasible mainstream model of sustainable mobility services in the future, which can effectively improve the utilization rate of motor vehicles, solve the problems of traffic congestion, environmental pollution and urban land, and promote low-carbon and sustainable development. To help electric vehicle operators improve service quality, the establishment of EVS program service performance evaluation is an urgent problem to be solved. Based on this, this paper firstly constructs the evaluation index system from 5 aspects: electric vehicle, charge station, user experience, payment and intelligent services through literature review and Delphi method. Secondly, the criteria importance though intercriteria correlation (CRITIC) and the improved G1 method are introduced to overcome the shortcomings of the single method, and the combined weights are calculated by the multiplication normalization method. Finally, a decision model based on intuitionistic fuzzy soft set (IFSS)-prospect theory and VIse Kriterijumski Optimizacioni Racun (VIKOR) method is constructed to select the best service performance of EVS program, and its feasibility and effectiveness are verified by sensitivity analysis and comparative analysis. The result shows that EVCARD is the best performing EVS program, and shared electric vehicle and charge station are the key factors to be considered in the selection. This study provides scientific and feasible guidance for the optimal service performance selection of EVS programs, which is of great significance for users to choose EVS programs.</p></div>

Publication Details

Journal
Figshare
Published
2024-11-07
DOI
https://doi.org/10.1371/journal.pone.0309512.s007
Primary Topic
Botanical Studies and Applications
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

The influence of weight change of C51-C54 on Q.

Figshare
Botanical Studies and Applications
article

The influence of weight change of C51-C54 on Q.

article en

Abstract

<div><p>Current mobility trend indicates that the number of private cars will decline in the near future. One of the reasons for this trend is the development of Mobility as a Service (MaaS), which in conjunction with information and communication technologies (ICT) drive the application of transport services in smart city, respond to environmental issues, and provide users with reliable mobility. Electric vehicle sharing (EVS) travel has been regarded as a feasible mainstream model of sustainable mobility services in the future, which can effectively improve the utilization rate of motor vehicles, solve the problems of traffic congestion, environmental pollution and urban land, and promote low-carbon and sustainable development. To help electric vehicle operators improve service quality, the establishment of EVS program service performance evaluation is an urgent problem to be solved. Based on this, this paper firstly constructs the evaluation index system from 5 aspects: electric vehicle, charge station, user experience, payment and intelligent services through literature review and Delphi method. Secondly, the criteria importance though intercriteria correlation (CRITIC) and the improved G1 method are introduced to overcome the shortcomings of the single method, and the combined weights are calculated by the multiplication normalization method. Finally, a decision model based on intuitionistic fuzzy soft set (IFSS)-prospect theory and VIse Kriterijumski Optimizacioni Racun (VIKOR) method is constructed to select the best service performance of EVS program, and its feasibility and effectiveness are verified by sensitivity analysis and comparative analysis. The result shows that EVCARD is the best performing EVS program, and shared electric vehicle and charge station are the key factors to be considered in the selection. This study provides scientific and feasible guidance for the optimal service performance selection of EVS programs, which is of great significance for users to choose EVS programs.</p></div>

Figshare
Sustainable cities and communities
Openalex Percentile: Top 33%
Botanical Studies and Applications
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

The influence of weight change of C51-C54 on Q. · Figshare (2024) | TGRS Research Map | TGRS