Modelling route choices and outlet visits in the downtown shopping area of Maastricht

  • Author:
  • Year: 2018

It is of importance to gain insight in pedestrian behaviour in downtown shopping areas since, the size of pedestrian flows in pedestrianized shopping areas is an important indicator of turnover figures and real estate values in shopping areas. To better understand the shopping preferences and route choice behaviour of different population groups, models of pedestrian movement may be helpful in predicting likely consumer response to managerial and planning decisions. In general, most shopping areas in the Netherlands are completely pedestrianized. The pedestrian behaviour in inner cities is complex and hard to predict. However, many models have shown that pedestrian behaviour at least partially can be predicted.

The following problem statement is set to be answered in this study: What is the pedestrian behaviour in the downtown area of Maastricht and to what extent is there a difference in age categories, gender and the endpoint of the pedestrian in the route choice behaviour and the shops that are visited?

The literature study pointed out that personal characteristics, characteristics of the trip and environmental and infrastructure characteristics are of influence on the pedestrian behaviour in downtown shopping areas. Characteristics that may have an influence on the pedestrian behaviour in downtown shopping areas are taken into account in the questionnaire that is prepared for data collection.

The results showed that there are some differences regarding the pedestrian behaviour between the different gender groups. Secondly, the differences according to the age categories are small. Thirdly, the exit-point where pedestrians leave the downtown shopping centre appears to influence pedestrian behaviour in the downtown shopping area. In addition physical developments and social developments have their impact on the pedestrian flow and the outlets visited in the downtown shopping area of Maastricht. Since gaining insight in pedestrian behaviour is complex nonetheless very important it is of importance to collect more data and optimize the pedestrian model.