By Francesca Pagliara, John Preston, David Simmonds
ISBN-10: 3642127878
ISBN-13: 9783642127878
ISBN-10: 3642127886
ISBN-13: 9783642127885
The powerful making plans of residential place offerings is likely one of the nice demanding situations of latest societies and calls for forecasting features and the honour of complicated interdependencies that may purely be dealt with through complicated computing device versions. This e-book provides quite a number methods used to version residential destinations in the context of constructing land-use and shipping versions. those techniques illustrate the diversity of selections that modellers need to make so as to characterize residential selection behaviour. The types provided during this publication symbolize the cutting-edge and are priceless either as key construction blocks for basic city versions, and as consultant examples of complexity science.
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Additional resources for Residential Location Choice: Models and Applications
Example text
The negative impact of a change from single family dwellings to highrises is particularly dramatic for this sub-sample, which is consistent with expectations for households with children. Another difference concerns speed bumps and chicanes on the road in front of the dwelling. The parameter estimates for both are very near zero and highly insignificant in this case; whereas they are both negative and significant for the full sample.
One difference between this sub-sample and the full sample concerns the impacts of changes in dwelling type from “single family”: types associated with higher residential densities have greater negative impacts for this sub-sample than they do for the full sample. The negative impact of a change from single family dwellings to highrises is particularly dramatic for this sub-sample, which is consistent with expectations for households with children. Another difference concerns speed bumps and chicanes on the road in front of the dwelling.
The estimation results for the “air quality” group of parameters are expressed relative to the “never bad” category, which has a fixed utility of zero. Not surprisingly, the parameter estimates for all the non-zero frequencies of bad air quality are negative and become more negative as the frequency increases. The frequency of bad air going from “never bad” to “bad 1 day per week” has the same impact as an increase in municipal taxes of about $122 per month, or as an increase in auto drive time to work of about 52 min per trip.
Residential Location Choice: Models and Applications by Francesca Pagliara, John Preston, David Simmonds
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