||Analyse af indkøbsture i Hovedstadsområdet
||Nielsen, Rune Kruse
||Nielsen, Otto Anker (Trafikmodeller, Institut for Transport, Danmarks Tekniske Universitet, DTU, DK-2800 Kgs. Lyngby, Denmark)
Rich, Jeppe (Trafikmodeller, Institut for Transport, Danmarks Tekniske Universitet, DTU, DK-2800 Kgs. Lyngby, Denmark)
||Technical University of Denmark, DTU, DK-2800 Kgs. Lyngby, Denmark
||TU) performed by the Danish Transport Research Institute. It contains three
parts, all with the shopping trips in focus.
1. Statistical research of TU data from the entire country without spatial
2. Analysis of TU data from the Copenhagen area with spatial reference
3. Modeling of home-shopping trips in the Copenhagen area.
In the first part an overview of the shopping behavior is established. Essential
parts to point out are: The overall average shopping trip length is 6 km,
68 % of all shopping trips have the residence as starting point, which makes
home-shopping trips representative of the shopping trips in general when it
comes to mode choice. Furthermore there are studies of household size influence
on shopping behavior and shopping trips during year, month, week and
In second part, an investigation has been carried out to try out the thesis,
that there is an coherence between the shopping destinations station vicinity
and the mode choice for shopping trips, like the one found for home-work
trips. The analysis showed to be influenced by too much noise, to give a clear
conclusion. Further fragmentation might meet the expected results, however
data is not comprehensive enough to bear further fracmentation.
In the last part, trip distribution and mode choice is modeled in a nested
logit model, using TU data as RP-data and OTM-zonestructure as home and
destination zones. The nest structure was mode choice conditioned by the destination
choice. The final model gives fine results and is in many ways consistent
with a similar model carried out by Rand Europe for Danish Transport
Research Institute. However the model suffer from the fact, that OTM zones
is much different in size. The model is hard to benchmark, since the exact distribution
and mode choice for shopping centers is not known.
Creation date: 2009-01-08
Update date: 2011-04-13