No open-access location is known for this record yet.
No open-access location is known for this record yet.
This paper describes a set of new procedures used to generate choice sets for grocery shopping destination choices observed in a large scale GPS data set.The procedures are a rulebased identification of the shopping trips, defining places from the observed locations using a hierarchical-clustering algorithm and finally a rule-based identification of the place of home and work/education and implicitly with this the imputation of the trip purposes.The GPS traces were collected by volunteers: 2,435 persons in Zurich and 1,086 persons in the smaller city of Winterthur.No socio-demographic information such as age, sex, income, etc. was available for this research, as the data was collected for a different purpose.The choice sets are generated by transport mode used for the shopping trip; car, walking and urban public transport whereas trips by intercity rail and bicycle were excluded since their numbers are too low for an estimation of a destination choice model, the ultimate purpose of the overall project.The results were compared with the Swiss Microcensus (MZ) 2005, the national travel behaviour survey, for time-of-week, time-of-day, duration, duration of the shopping activity.While the quality of the results was high, the comparisons highlight instructive differences resulting from the different data generation process.
Loading…
Stored only when both papers are in the corpus — 9 citations exist upstream.
Papers that cite the same references — the relational fallback while embeddings are still backfilling.
Imported from OpenAlex (CC0) — nothing here is generated.