%A Christopher Godier
%X The built environment of the area within walking and cycling distance of railway stations represents a finite public resource. This research investigates how this resource can be most effectively used by conducting a multilinear regression analysis of geospatial data of the areas surrounding 50 Dutch railway stations to determine which attributes of the built environment encourage rail ridership and higher degrees of customer satisfaction. To do this, indicators of
rail service quality ("node") and those of the built environment ("place") were evaluated under Bertolini's Node-Place Framework. The potentially explanatory node indicators included train service frequency, for how much of the day service operates and the number of local bus connections. Place indicators evaluated included the degree of mix of land uses around a station, the possibility of walking and cycling in a neighbourhood and the population and local
jobs. The research found that certain node and place indicators did have an effect on rail ridership. These included off-peak train frequency, number of bus, tram and metro connections, job density and street network permeability. However, node and place indicators were not found to have an effect on customer satisfaction scores. This research then applies
these findings to various Dutch railway stations and describes remedial actions.
%L theses_frw4384
%T Back on Track: Increasing Dutch Train Ridership using the Node-Place Model
%D 2023