Geographically Weighted Regression based Investigation of Transport Policies for Increased Public Transport Ridership : A Case Study of Stockholm

Abstract: Public transport plays a vital role in society as the economy, the degree of sustainability and the qualityof life of a city is directly affected by transportation. A shift in modal share towards public transport isassociated with many benefits such as increased air quality and improved space allocation within thecity. To further promote public transport, an appropriate measure of competitiveness is required toevaluate the impact of past and future transport policies. This study introduces the journeys per capitaratio as a new way of measuring public transport competitiveness. Firstly, the key factors affecting thepublic transportation usage rate expressed as the journeys per capita ratio are identified to evaluatethe impact of public transport provider efforts. For this purpose, data for a total of 32 explanatoryvariables and a scope of 218 regions for seven consecutive time frames are collected. Secondly,geographically weighted regression (GWR) – a local regression-based spatial analysis technique – isperformed to test if the journeys per capita ratio is a suitable target variable to predict the impact ofcertain transport supply changes. A traditional global ordinary least square (OLS) model is conductedas well to compare if a local model could be more beneficial. The GWR and the OLS model are trainedwith the data of previous years and tested with data from the consecutive following years. Thirdly,further temporal and socio-economic based cluster analyses are performed to assess the validity andthe explanatory power of the journeys per capita ratio. The conducted analyses reveal that thejourneys per capita ratio is a superior measure for assessing public transport competitiveness.Goodness of fit statistics and estimation results demonstrate that the GWR model has betterprediction accuracy and is more capable of retrospectively predicting the impact of previous transportpolicies.