Intelligent Transportation Systems Institute, Center for Transportation Studies, University of Minnesota
Anecdotal and empirical evidence has shown strong associations between the built environment and individuals’
travel decision. To date, data about individuals’ travel behavior and the nature of the retail environment have not
been linked at the fine-grained level for verifying such relationships. GPS and GIS have revolutionized how we
measure and monitor land use and individual travel behavior. Compared with traditional travel survey methods,
GPS technologies provide more accurate and detailed information about individuals’ trips. Based the GPS travel
data in the Twin Cities we analyze the impact of individuals’ interactions with road network structure and the
destinations’ accessibility on individuals’ destination choice for home-based non-work retail trips. The results
reveal that higher accessibility and diversity of services make the destination more attractive. Further, accessibility
and diversity of establishments in a walking zone are often highly correlated. A destination reached via a more
circuitous or discontinuous route dampens its appeal. In addition, we build an agent-based simulation tool to study
retail location choice on a supply chain network consisting of suppliers, retailers, and consumers. The simulation
software illustrates that the clustering of retailers can emerge from the balance of distance to suppliers and the
distance to consumers. We further applied this tool in the Transportation Geography and Networks course (CE
5180) at the University of Minnesota. Student feedback reveals that it is a useful active learning tool for
transportation and urban planning education. The software also has the potential of being extended for an integrated
regional transportation-land use forecasting model.
Huang, Arthur; Levinson, David.
Accessibility, Network Structure, and Consumers’ Destination Choice: A GIS Analysis of GPS Travel Data and the CLUSTER Simulation Module for Retail Location Choice.
Intelligent Transportation Systems Institute, Center for Transportation Studies, University of Minnesota.
Retrieved from the University of Minnesota Digital Conservancy,
Content distributed via the University of Minnesota's Digital
Conservancy may be subject to additional license and use
restrictions applied by the depositor.