Cities are growing worldwide, which leads to an increase in trips in urban areas. In Europe, more than half of the trips are made by car, while car takes most space of all modalities. Of all modalities car has the highest CO2 emissions. Thehigh number of trips by car within cities lead to challenges related to the accessibility, livability, and sustainability of cities. Sustainable mode alternatives in this research are the bicycle, shared bicycle, and urban public transport whichhave potential for being an attractive alternative on short trips (<5 kilometer). Therefore, this study researches factors that influence car users’ mode choice towards those three sustainable modes, for stand-alone trips with trip purpose shopping. Through a stated preference survey amongst car drivers in a Dutch mid-sized city (N=360), preferences are gathered with respect to the mode choice. A panel mixed logit model with error component and interaction variables is used for the analysis of the stated preference data. The factors with most impact on mode choice are (shared) bicycle travel time, bicycle parking costs, shared bicycle availability, public transport travel costs, and public transport in-vehicle crowdedness. The non-mode factor with most impact is attitude towards tram, which is negatively correlated to car frequency. Car users tend to switch towards public transport, so a guaranteed seat in public transport, a more positive attitude towards public transport and higher car parking costs can achieve the switch. The switch towards bicycle can be made if the bicycle travel time is lower than currently.

In an environment in which Public Transport plays an ever growing role in urban areas and passenger experience. In-depth knowledge on customer satisfaction is key in improving passenger experience. Crowding has shown to be an important aspect of route and mode choice, but its impact on customer satisfaction has not yet been quantitatively explored. This paper investigates this impact. Using a Structural Equation Model based on customer satisfaction survey data and corresponding occupancy and punctuality numbers a significant effect of occupancy levels on perceived crowding was found. In-vehicle crowding, both subjective and objective, seems to impact overall customer satisfaction indirect, with comfort being the main mediating variable. Model results were converted into a calculation tool which can be used to assess the impact of changes in passenger numbers, passenger distribution and frequencies on customer satisfaction. Further research can verify the linearity of the relation between in-vehicle crowding and customer satisfaction and deepen knowledge of external factors such as weather and disruptions have on experienced crowding.