UTSG 213: Exploring gendered cycling behaviours within a large-scale dataset

Paper presented at Universities Transport Study Group 2013 conference. January 2013, Smeed Prize for best student paper.

Transcript

1. Exploring gendered cycling behaviours within a large, attribute rich, transactional dataset Roger Beecham giCentre and Transport Hub, City University
2. The increasing availability of sensor data in urban areas now offers the opportunity to perform continuous evaluations of transport systems and measure the effects of policy changes, in an empirical, large-scale and non- invasive way. (Lathia et al. 2012:88)
3. Collaboration with TfL and the London Cycle Hire Scheme
4. Objectives In bicycle-friendly cities […] cycling is an inclusive, population-wide activity. […] In car-oriented cities […] the majority of cyclists are middle-aged men. [...] So strong is the association between cycling mode share and female rates of cycling that some observers have suggested that cycle-equity in cycling is an indicator of a cycling-friendly environment. Garrard, Handy & Dill, 2012: 211
5. Data processing and analysis
6. Output area classification
7. Indices of Multiple Deprivation
8. Distance to docking station 0! 25,000! < 0.125! < 0.25! < 0.5! < 1! < 2! < 3! < 4! < 5! < 10! < 15! < 25! < 50! < 100! < 900! distance (km)!
9. Recency-Frequency segmentation frequency 808 1428 1678 3780 8898 1612 2205 3388 5086 4300 2530 3535 4454 4001 2072 4455 4647 4078 2491 920 7186 4776 2994 1233 402 recency
10. Recency 0! 5,000! 10,000! 15,000! 20,000! 25,000! 30,000! 35,000! 14/09/2011! 14/12/2011! 14/03/2012! 14/06/2012! 14/09/2012! # members! Recent journeys!
11. Recency 0! 5,000! 10,000! 15,000! 20,000! 25,000! 30,000! 35,000! 14/09/2011! 14/12/2011! 14/03/2012! 14/06/2012! 14/09/2012! # members! Recent journeys! 1 2 3 4 5
12. Frequency 0! 1,000! 2,000! 3,000! 4,000! 5,000! 6,000! 7,000! 8,000! 9,000! 10,000! 0.00! 0.20! 0.40! 0.60! 0.80! 1.00! # members! Frequency score!
13. Frequency 0! 1,000! 2,000! 3,000! 4,000! 5,000! 6,000! 7,000! 8,000! 9,000! 10,000! 0.00! 0.20! 0.40! 0.60! 0.80! 1.00! # members! Frequency score! 1 2 3 4 5
14. Recency-Frequency segmentation frequency 808 1428 1678 3780 8898 1612 2205 3388 5086 4300 2530 3535 4454 4001 2072 4455 4647 4078 2491 920 7186 4776 2994 1233 402 recency
15. Travel-time z-scores 0! 5,000! 10,000! 15,000! 20,000! 25,000! -3! -2.75! -2.5! -2.25! -2! -1.75! -1.5! -1.25! -1! -0.75! -0.5! -0.25! 0! 0.25! 0.5! 0.75! 1! 1.25! 1.5! 1.75! 2! 2.25! 2.5! 2.75! 3! 3.25! 3.5! 30!
16. Relating customer variables with space- time patterns of behaviour
19. Weekday am Weekday pm
20. Findings
21. Male Female 0%! 100%! Lowest RF! Highest RF! 0%! 50%! Lowest RF! Highest RF! 0%! 50%! Lowest RF! Highest RF! All women! Selected women! 0%! 100%! Lowest RF! Highest RF! All men! Selected men!
22. Male Female 0%! 50%! -3! -2.5! -2! -1.5! -1! -0.5! 0! 0.5! 1! 1.5! 2! 2.5! 3! All! Male! 0%! 50%! -3! -2.5! -2! -1.5! -1! -0.5! 0! 0.5! 1! 1.5! 2! 2.5! 3! All! Female!
23. Male Female 0.0%! 1.0%! 2.0%! 3.0%! Monday! Tuesday! Wednesday! Thursday! Friday! Saturday! Sunday! 0.0%! 1.0%! 2.0%! 3.0%! Monday! Tuesday ! Wednesday! Thursday! Friday! Saturday! Sunday!
24. Male
25. Female
26. Male Female
27. Controlling for geo-demographics
28. All! High RF!
29. All! Women! All! High RF!
30. Male <5km Sep 2011-2012 Female <5km Sep 2011-2012 0.0%! 1.0%! 2.0%! 3.0%! Monday! Tuesday! Wednesday! Thursday! Friday! Saturday! Sunday! 0.0%! 1.0%! 2.0%! 3.0%! Monday! Tuesday ! Wednesday! Thursday! Friday! Saturday! Sunday!
31. Women’s journeys remain spatially constrained - even controlling for access period, level of usage and geo-demographics
32. Male High RF <5km Sep 2011-2012
33. Female High RF <5km Sep 2011-2012
34. Male High RF <5km Sep 2011-2012 Female High RF <5km Sep 2011-2012
35. Discussion    
36. Beyond exploration?
37. Thanks