Transport user satisfaction modelling : application to the brokerage vehicle selection process
General customer satisfaction studies link use and reuse of a commodity or service to the extent to which customers are satisfied. There is currently great interest in increasing transport accessibility, which in this context consists of the ease of reaching and using transport, and thus means are being devised to increase both the use and reuse of transport. This thesis investigates the use of customer satisfaction models in relation to the use and reuse of transport services. Much of the transport for people with restricted mobility is provided by the Community Transport sector where the criteria for vehicle selection in relation to a particular person's proposed journey are currently vehicle availability, costs and time constraints, and the matching of passenger disability and vehicle capability. Beyond requirements related to the barriers to access found in the transport system, transport users do have other needs and preferences, such as safety, comfort, convenience, friendly crew, reliability, etc., that can affect their satisfaction with the service provided. Unfortunately, such a multi-criteria decision process makes it difficult for community transport managers and operators to take these preferences into consideration systematically when allocating transport to individuals. This thesis develops a predictive model of transport satisfaction that can be used in such transport provision decision-making. A comprehensive list of travel attributes affecting transport-user satisfaction has been derived from the literature and confirmed through group interviews. For each of these attributes, a predictive model of satisfaction based on the level of service of the attribute, the user's prior transport experience and socio-demographic characteristics, has been derived. An overall transport satisfaction model has been developed from a combination of the individual attribute satisfactions. The model was validated by comparing its output to an independent dataset and a high level of similarity was observed. In addition, a framework for such a decision-making process for a community transport brokerage has been designed.