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Title: Evaluation of benefits and effectiveness of smart cards for public transport
Author: Hao, Xu
ISNI:       0000 0001 3531 0971
Awarding Body: University of Leeds
Current Institution: University of Leeds
Date of Award: 2007
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As a new technology, smart card ticketing for public transport has become increasingly popular across the world. Now smart cards and the traditional fare payment methods, cash and paper-based travel cards, have become three major fare payment options in public transport systems. The success of smart card applications across the world led to the realisation of the potential of smart card ticketing by some local governments and public transport service providers in China. For example, in Dalian, China, more than one million public transport smart cards have been issued since the payment application was just introduced in July 2001. However, the traditional payment methods (i. e. cash and travel cards) are still in use in most Chinese cities. Passengers may choose between smart cards and traditional payment methods, according to their perceptions. Therefore, the aim of this research is to identify the fare payment preferences of passengers based on the existing and prospective situations for three fare payment methods (i. e. cash, travel cards and smart cards), to carry out the user demand analysis and provide an insight into the benefits and effectiveness of smart card ticketing. The revealed preference (RP) and stated preference (SP) surveys were designed and carried out in Dalian, China, where the smart card project has been successfully implemented. In the data analysis, two different models are discussed: firstly standard logit models are used to analyse the joint RP and SP data. Secondly, two kinds of new techniques: fuzzy logic (FL) and artificial neural network (ANN) methods are introduced as an alternative to model discrete choice data. The motivation for using FL and ANN is that these two models can be non-linear and simulate human's decision making process without any a priori assumptions between inputs and outputs. The purpose of using FL and ANN in this research is to explore and compare the forecasting ability in the user demand analysis and model performance between new techniques and logit models. Finally, results of the analysis, including forecasted market shares, valuation of attributes, fare elasticities, etc, indicate the increasing trend of smart card use in future development. Through monetary valuations, the importance of attributes is determined, such as multifunction and top-up/purchase options for smart cards. In addition, relevant policies are suggested to authorities to enhance the smart card payment service.
Supervisor: Wardman, M. ; Chen, H. Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available