MODELS FOR PREDICTING THE IMPACT OF TRANSPORTATION POLICIES ON RETAIL ACTIVITY

Comprehensive urban land-use models designed in the past to predict the affects of large, capital-intensive transportation facilities on the spatial distribution of urban activities are not well suited for predicting the impacts of newer policies to control and manage existing facilities. This paper describes a case study that develops two alternatives models with a much sharper, policy-oriented focus and substantially reduced requirements for data and computational resources. The case selected for study involves the hypothetical adoption of transportation control measures to improve air quality in the Denver central business district and the potential impact of controls on retail activity. The two models are a cross-section, lagged-adjustment regression that identifies determinants of aggregate sales at any location and a set of disaggregate travel demand models that predicts the equilibrium between shopping trips and retail activity. The forecasts of both models are consistent in predicting substantial declines in retail activity in response to restrictions on automobile access and negligible offsetting effects of improvements in transit service. It is concluded that compensatory nontransportation measures that enhance downtown amenities or the uniqueness of downtown retail opportunities may offset the negative influence of reduced accessibility. /Author/

Media Info

  • Media Type: Print
  • Features: Figures; References; Tables;
  • Pagination: pp 34-41
  • Monograph Title: Transportation system analysis
  • Serial:

Subject/Index Terms

Filing Info

  • Accession Number: 00195968
  • Record Type: Publication
  • ISBN: 0309028221
  • Files: TRIS, TRB
  • Created Date: Sep 15 1981 12:00AM