In this thesis, the functioning of passenger delay-based refund schemes in urban public transportation settings is evaluated, such as metros or light-rails. These are used when a passenger encounters a delay on their trip, in order to grant a form of refund to them. To the best o
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In this thesis, the functioning of passenger delay-based refund schemes in urban public transportation settings is evaluated, such as metros or light-rails. These are used when a passenger encounters a delay on their trip, in order to grant a form of refund to them. To the best of knowledge, no research has been carried out yet on several aspects of these refund schemes, such as which design considerations can be taken into account upon establishing one, or how their performance can be evaluated. To clarify these issues, the state of the practice is reviewed by surveying the internet and the information that is being provided by the individual public transport operators. By categorising this information, it can be established what the design aspects of these refund schemes are. These are the delay type such as departure or arrival delay, the delay threshold, i.e., the minimum delay from which a trip taken is elegible for a refund, the refund type, which is the form of refund that the passenger receives, and the possibility for alternative transport to be refunded. In order to determine whether there could be a form of linearity between delays and refunds, and to facilitate the evaluation of different refund schemes, a regression analysis was carried out on approximately a year of passenger trip data and vehicle data from the Washington Metro. This enabled acquiring more reliable, i.e., excluding individual passenger’s possibly erroneous behaviour, observations of the departure delay and arrival delay of every trip taken during this study period. Using this data, a possible link between the total amounts of delays encountered and refunds granted per day was analysed. It could be concluded that there is indeed a strong linear effect between these two. Furthermore, a number of key performance indicators (KPI’s) was established which allowed to assess the performance of a set of synthetic refund schemes, in which the parameters were varied that resulted from the aforementioned survey. Furthermore, a refund scheme was recreated that uses the general punctuality on a line and subsequently refunds all travelers that can have been expected to be effected by a possible drop in this punctuality. Using these KPI’s, conclusions could be drawn on the performance of different refund schemes, in the sense of how many refunds per trip are granted, how the ratio of the average delay of all refunded trips vs. the average delay of all trips is, how many revenue losses the refund schemes yield for the operator, and how much of the time losses (using a certain Value of Time) are compensated for.