Benefit-estimation for mobility management by stat. data Walter Bien ECOMM-2008 (London, June-2008) 1 Quick & Simple – a new approach for benefit-estimation.
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benefit-estimation for mobility management by stat. data
Walter Bien ECOMM-2008 (London, June-2008) 1
„Quick & Simple“ – a new approach
for benefit-estimation of mobility-management (MM)
and other soft-policies by statistical data
Walter Bien, head of sales und customer-caretraffiQ – local public transport authority (city of frankfurt, germany)
European Conference on Mobility Management, ECOMM 2008, London
benefit-estimation for mobility management by stat. data
Walter Bien ECOMM-2008 (London, June-2008) 2
Overview
1. The problem: effect estimation of measures
2. Structural data: important for modal-choice / „available“
3. Combining structural data with passenger numbers in PT
4. Example: developement and results in the frankfurt urban region
5. Next steps and chances
benefit-estimation for mobility management by stat. data
Walter Bien ECOMM-2008 (London, June-2008) 3
1. The problem: effect estimation of measures (a)
year
Public Transport
passengerschange-
rate
1995 170,0
2001 183,4 7,9%
2007* 183,8 0,2%
„success“
of mobility management
???
* means: preliminary
benefit-estimation for mobility management by stat. data
Walter Bien ECOMM-2008 (London, June-2008) 4
1. The problem: effect estimation of measures (b)
„success“
of mobility management
… could be ?
yearPT-
passengers
income by
ticket-sales
change-rate
1995 170,0 117,0
2001 183,4 137,3 17,3%
2007* 183,8 167,0 21,6%
benefit-estimation for mobility management by stat. data
Walter Bien ECOMM-2008 (London, June-2008) 5
1. The problem: effect estimation of measures (c)
„success“
of mobility management
… yes !
yearinhabi-tants
emplo-yees
inhab.+employ.
change-rate
1995 653 548 1.201
2001 646 603 1.249 4,0%
2007* 668 610 1.278 2,3%
benefit-estimation for mobility management by stat. data
Walter Bien ECOMM-2008 (London, June-2008) 6
1. The problem: effect estimation of measures (d)
PT-passengers and PT-income (1995 - 2008) compared to fuel-price (index numbers: base 1995 = 100)
20082007200620052004200320022001200019991998199719961995
90
100
110
120
130
140
150
160
170
180
Index
PT - income (local)
fuel-price (standard)
PT passengers in frankfurt
benefit-estimation for mobility management by stat. data
Walter Bien ECOMM-2008 (London, June-2008) 7
1. The problem: effect estimation of measures (e)
Public Transport: offer and usage (1995 - 2008) (index numbers: base 1995 = 100)
95
100
105
110
115
120
125
20082007200620052004200320022001200019991998199719961995
level of capacity
PT - offer
PT - usage
benefit-estimation for mobility management by stat. data
Walter Bien ECOMM-2008 (London, June-2008) 8
2. Structural data: important for modal-choice / „available“ (a)
95
100
105
110
20082007200620052004200320022001200019991998199719961995
95
100
105
110Index
households in Frankfurt
number of household members
inhabitants younger than 18
inhabitants of Frankfurt
benefit-estimation for mobility management by stat. data
Walter Bien ECOMM-2008 (London, June-2008) 9
2. Structural data: important for modal-choice / „available“ (b)
95
100
105
110
115
120
20082007200620052004200320022001200019991998199719961995
95
100
105
110
115
120Index
employees - working in Frankfurt
employees - living in Frankfurt
number of cars in Frankfurt
benefit-estimation for mobility management by stat. data
Walter Bien ECOMM-2008 (London, June-2008) 10
2. Structural data: important for modal-choice / „available“ (c)
… on the next slide
– see the combination
benefit-estimation for mobility management by stat. data
Walter Bien ECOMM-2008 (London, June-2008) 11
95
100
105
110
115
120
20082007200620052004200320022001200019991998199719961995
95
100
105
110
115
120Index
households in Frankfurt
number of household members
inhabitants younger than 18
employees - working in Frankfurt
number of cars in Frankfurt
employees - living in Frankfurt
inhabitants of Frankfurt
benefit-estimation for mobility management by stat. data
Walter Bien ECOMM-2008 (London, June-2008) 12
3. Combining structural data with passenger-numbers in public-transport (a)
The weighted combination of 4 single-indicator values is a good fitting indicator for the developement of PT-passenger-numbers:
Inhabitants of frankfurt (weight: 1)+ (reciprocal) number of cars (weight: 2)+ employees (working) in frankfurt (weight: 3)+ number of commuters to frankfurt (weight: 4)-------------------------------------------------------------------------average of the indicators above = indicator for pt-passengers
benefit-estimation for mobility management by stat. data
Walter Bien ECOMM-2008 (London, June-2008) 13
3. Combining structural data with passenger- numbers in public-transport (b)
from structural data to an indicator-value (index numbers: base 1995 = 100)
80
90
100
110
120
130
20082007200620052004200320022001200019991998199719961995
inhabitants of frankfurt
employees (working) infrankfurt
number of cars (inreciprocal manner)
number of commutersto frankfurt
(weighted) average ofthe indicators above
benefit-estimation for mobility management by stat. data
Walter Bien ECOMM-2008 (London, June-2008) 14
3. Combining structural data with passenger- numbers in public-transport (c)
PT-passengers and indicator-value (index numbers: base 1995 = 100)
20082007200620052004200320022001200019991998199719961995
80
90
100
110
120
130
140
150
Index
indicator-value (combining structural data)
PT - income (local)
PT passengers in frankfurt
benefit-estimation for mobility management by stat. data
Walter Bien ECOMM-2008 (London, June-2008) 15
3. Combining structural data with passenger- numbers in public-transport (d)
PT-passengers, indicator-value and a target value for passenger-number (index numbers: base 1995 = 100)
20082007200620052004200320022001200019991998199719961995
80
90
100
110
120
130
140
150
Index
indicator-value (combining structural data)
PT - income (local)
target für PT-passengers
PT passengers in frankfurt
benefit-estimation for mobility management by stat. data
Walter Bien ECOMM-2008 (London, June-2008) 16
4. Example: developement and results in the Frankfurt urban region (a)
1. It becomes possible to determine the effects of other measures
- such as mobility management or further soft-policies in PT
(advertisement, special efforts of information...) - separately
and also prove their economic efficiency.
2. Regarding the Frankfurt-area this approach shows that since the year 2000 with
rising tendency, the applied measures have generated additional fare income
within a two-digit million range (of EUROs).
3. The lower costs (for mobility management) must lead to a continuation and legitimate
the spending of money not only from an organisational/company-internal but also
from a political and public point of view.
benefit-estimation for mobility management by stat. data
Walter Bien ECOMM-2008 (London, June-2008) 17
4. Example:
developement
and results in
the Frankfurt
urban region
(b)
PT-passengers in Frankfurt (1995 - 2008) in compare to other mobility-indicators (index numbers: base 1995 = 100)
20082007200620052004200320022001200019991998199719961995
80
90
100
110
120
130
140
150
Index
inhabitants in frankfurt
employees (working) in frankfurt
number of cars (in reciprocal manner)
number of commuters to frankfurt
average from the indicators above
PT - income (local)
target für PT-passengers
PT passengers in frankfurt
benefit-estimation for mobility management by stat. data
Walter Bien ECOMM-2008 (London, June-2008) 18
4. Example:
developement
and results in
the Frankfurt
urban region
(c)
the "result" of mobility-management in Frankfurt (2001 to 2007)
20082007200620052004200320022001200019991998199719961995
90
100
110
120
130
140
Index
PT - income (local)
target-value for PT passengers
PT passengers in Frankfurt
benefit-estimation for mobility management by stat. data
Walter Bien ECOMM-2008 (London, June-2008) 19
4. Example: developement and results in the Frankfurt urban region (d)
the "result" of mobility-management in Frankfurt (2001 to 2007)
20082007200620052004200320022001200019991998199719961995
95
100
105
110
115
120
Index
target-value for PT passengers
PT passengers in Frankfurt
~ 20 Mio. EURO
benefit-estimation for mobility management by stat. data
Walter Bien ECOMM-2008 (London, June-2008) 20
5. Next steps and chances (a)
If the economic effects of mobility management and other soft traffic
policies can be estimated quantitatively in an easy way with only few
available indicators, low priced basic conditions for these measures can
be achieved.
The broad application and testing of this methodology would induce
an equal treatment of soft policies and mobility management with rather
"hardware-oriented" measures as for example new travel offers
(temporal/spatial), new vehicles or price-arrangements in the PT-sector.
benefit-estimation for mobility management by stat. data
Walter Bien ECOMM-2008 (London, June-2008) 21
5. Next steps and chances (b)
In a further step a methodology can be developed, which
permits effect estimations for mobility management in advance,
like it has already been implemented in the German-speaking-
area by the so-called "standardized evaluation" for all kind of
infrastructure measures.
And that means:
New and equal opportunities for mobility management!
benefit-estimation for mobility management by stat. data
Walter Bien ECOMM-2008 (London, June-2008) 22
… and so – we reach her/him:
the “multi-modal” mobility-user
5. Next steps and chances (c)
benefit-estimation for mobility management by stat. data
Walter Bien ECOMM-2008 (London, June-2008) 23
car(at all)
82%
bike(at all)
40%
Today: modal-choice of the inhabitants of Frankfurt (~ 670.000 persons)
PT (at all)
43%
car (only)
37%
bike (only)
6%
PT (only)
7%
car & PT16%
car& bike14%
PT & bike 5%
PT & car & bike 15%
benefit-estimation for mobility management by stat. data
Walter Bien ECOMM-2008 (London, June-2008) 24
car(at all)
69%
bike(at all)
56%
Tomorrow: Sustainable developement in modal-choice
PT (at all)
57%
car (only)
35%
bike (only)
16%
PT (only)
17%
car & PT5%
car& bike
4%
PT & bike 15%PT & car
& bike
25%
benefit-estimation for mobility management by stat. data
Walter Bien ECOMM-2008 (London, June-2008) 25
Thank you
for your attention and patience!
Walter Bien
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