Distances, accessibilities and attractiveness; looking at new approaches to include measures of urban form in hedonic pricing modelling

Artikel i vetenskaplig tidskrift, 2016

The population of Oslo increases rapidly and the corresponding demand of housing is an issue of great public, political and professional interest. Today, we can see several interesting discrepancies in the housing market, such as very high prices for dwellings with low technical standards and dwellings located in neighbourhoods very different from those planned and built today. There is a great diversity in the housing households’ willingness to pay. What are the patterns of such attractiveness in more detail and what might be the lessons to learn concerning what to build in the future? How can we plan and build housing that responds to the wide range of contemporary demands and that will also be attractive in decennials to come?
Economists and real estate businesses provide statistics on prices of dwellings, but the variables examined are usually too general for the results to be useful for actual planning and design. However, space syntax based research has shown that locations in cities can be measured more specifically and that analyses of these measurements correlate with numerous phenomenon related to activities and attractiveness of cities. By applying space syntax based measurements in GIS, comparing housing prices with presumed relevant variables of buildings and neighbourhoods by means of hedonic regression analysis, it is possible to seize new knowledge about how specific urban form variables of buildings and neighbourhoods correlate with housing prices. By this approach, willingness to pay for dwellings has been examined in two studies in Stockholm and Copenhagen. This paper presents methods and some result of these studies. In brief, we see that continuous urban form measurements in GIS are significant for willingness to pay for dwellings. The specificity of these measurements achieved by GIS analyses, applying the Place Syntax Tool, provides new and more detailed knowledge in this field.