A Satisfaction Evaluation Model of the Rail Feeder Modes Based on SEM
Science Discovery
Volume 6, Issue 5, October 2018, Pages: 320-326
Received: Sep. 16, 2018; Published: Sep. 18, 2018
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Zhou Yun-yun, Institute of Rail Transit, Tongji University, Shanghai, China
Yu Lu-man, Institute of Rail Transit, Tongji University, Shanghai, China
Teng Jing, Key Laboratory of Road and Traffic Engineering of the Ministry of Education, Tongji University, Shanghai, China
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As the city entering the era of public transport mainly with the rail transit, the good feeder system and transfer system have become the most prominent problems in urban rail transit. High synergy between urban rail transit and transfer facilities is an inevitable requirement to optimize traffic, but there are few studies on urban rail transfer and the research content is only based on data statistics without considering the mutual influence of various factors. For more accurate evaluation of the relevant service level, this paper combines customer satisfaction and SERVQUAL theory with the structural equation, uses SmartPLS software to explore the evaluation model of urban rail transfer, and then in this paper we investigate the citizens in Shanghai to calculate the satisfaction index of bus, taxi, bicycle and pedestrian as empirical analysis. This model can analyze the relationship between different variables, gain the key factors influencing the satisfaction index, and point out the problems in the connection service, so as to provide decisions supporting the optimization of urban rail transfer. The results of the model can be used in various connection modes and can solve the remaining "last kilometer" problem of urban rail transit, which is of great significance to improve the service level and operation efficiency of rail transit.
Integrated Transportation, Satisfaction Evaluation Model, Structural Equation Model, Rail Feeder Modes, Transportation in Shanghai
To cite this article
Zhou Yun-yun, Yu Lu-man, Teng Jing, A Satisfaction Evaluation Model of the Rail Feeder Modes Based on SEM, Science Discovery. Vol. 6, No. 5, 2018, pp. 320-326. doi: 10.11648/j.sd.20180605.12
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