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A new approach for MM benefit-estimation
Walter Bien
ECOMM 2009May 15 – San Sebastián
2
Eltis Café @ ECOMM 2008June 5th - London www.eltis.org
Effect Estimation within changing framework/conditions
The classical (best) approach:Evaluation of treatment groups and “placebo”-groups
Estimation of change in the mobility/traffic area (modal split, PT passenger numbers, …) using statistical data (inhabitants, number of cars, commuters, PT offer, …)
Comparison of estimated and measured values
Example: Development of the number of PT passengers in Frankfurt from 1995 to 2010
Overview
Eltis Café @ ECOMM 2009 www.eltis.org
3
Eltis Café @ ECOMM 2008June 5th - London www.eltis.org
1. Effect Estimation within changing framework/conditions
Eltis Café @ ECOMM 2009 www.eltis.org
Compare: The “fat car driver”
vs. the “slim biker”
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Eltis Café @ ECOMM 2009
year
Public Transport
passengerschange-
rate
(values in millions)
1995 170,0
2001 183,4 7,9%
2007* 183,8 0,2%
„success“
of mobility management ???
* means: preliminary
… starting with mobility management measures in the year 2000
… establish mobility management in the following years
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Eltis Café @ ECOMM 2009
„success“of mobility management
… could be ?
yearPT-
passengers
income by
ticket-sales
change-rate
(values in millions)
1995 170,0 117,0
2001 183,4 137,3 17,3%
2007* 183,8 167,0 21,6%
… but in the same two periods we have a strong increase of income by ticket sales (based on a higher price level)
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Eltis Café @ ECOMM 2009
„success“
of mobility management
… yes !
yearinhabi-tants
emplo-yees
inhab.+employ.
change-rate
(all values in thousands)
1995 653 548 1.201
2001 646 603 1.249 4,0%
2007* 668 610 1.278 2,3%
… the increase of customer potential (inhabitants and employees) is less in the second period
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Eltis Café @ ECOMM 2009
„success“ of mobility management:
… Yes (in a special manner) if we assume that there would be a decrease of the number of PT passengers and a less increase of income without mobility management …
period
Public Transport passen-
gers
Income by
ticket sales
Inhabitants &
employees
Compare of the change rates
1995-2001 7,9% 17,3% 4,0%
2001-2007 0,2% 21,6% 2,3%
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Eltis Café @ ECOMM 2009
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
Public Transport passengers
The problem: effect estimation of measures
… we can see non effect of fuel prices on the developement of PT passengers
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Eltis Café @ ECOMM 2009
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
The PT offer is stable in the first period while the usage icreases for 15%.
In the second period PT offer and also the usage is grown up for 6-7%-points.
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Eltis Café @ ECOMM 2009
2. The classical (best) approach: Evaluation of treatment groups and “placebo”-groups
Remember – (Eric Schreffler; S. Diego):
The data never lie
– but do we so ?
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Eltis Café @ ECOMM 2009
2. The classical (best) approach: Evaluation of treatment groups and “placebo”-groups
But also (Herbert Kemming, germany):
… The control group method… and its problems
12
Eltis Café @ ECOMM 2009
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Eltis Café @ ECOMM 2009
3. Estimation of change in the mobility/traffic area (modal split, PT passenger numbers, …) using statistical data (inhabitants, number of cars, commuters, PT offer, …)
14
Eltis Café @ ECOMM 2009
In the slides before we have to deal with this kind of data:
Number of Public Transport Passengers
PT income by ticket sales
Inhabitants (in city/region)
Employees (in city/region)
Fuel price
PT offer (in km*places - offered)
PT usage (in km*places - used)
… and all this data are almost available – and can be used (in combination with some others) to estimate effects of measures.
Structural data: important for modal-choice / „available“
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Eltis Café @ ECOMM 2009
95
100
105
110
20082007200620052004200320022001200019991998199719961995
95
100
105
110Index
households in Frankfurt
number of household members
inhabitants younger than 18
inhabitants of Frankfurt
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Eltis Café @ ECOMM 2009
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
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Eltis Café @ ECOMM 2009
… on the next slide
– see the combination
18
Eltis Café @ ECOMM 2009
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
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Eltis Café @ ECOMM 2009
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
Combining structural data with passenger-numbers in public-transport
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Eltis Café @ ECOMM 2009
Combining structural data with passenger- numbers in public-transport
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 (in reciprocalmanner)
number of commuters tofrankfurt
(weighted) average of theindicators above
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Eltis Café @ ECOMM 2009
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
Combining structural data with passenger- numbers in public-transport
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Eltis Café @ ECOMM 2009
Now we can construct a so called „Target Value“ for the number of PT passengers.
This is a weighted combination of the indicator-value before (combined by the 4 structural data) and the PT-offer (see slide no.8):
Indicator Value (weight: 2) + PT offer (weight: 1) -------------------------------------------------------------
average of the indicators above = Target Value for PT-passengers
Combining structural data with passenger- numbers in public-transport
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Eltis Café @ ECOMM 2009
4. Comparison of estimated and measured values
The convincing argument:
Decisive – is the final result !
In german: “… was hinten rauskommt.”
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Eltis Café @ ECOMM 2009
Combining structural data with passenger- numbers in public-transport
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… now we can see the difference between the (realized) number of PT passengers and the expected number (target value) of PT passengers …
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Eltis Café @ ECOMM 2009
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.
Conclusion
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Eltis Café @ ECOMM 2009
5. Example:
Development of the number of PT passengers in Frankfurt from 1995 to 2010
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Eltis Café @ ECOMM 2009
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
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Eltis Café @ ECOMM 2009
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
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Eltis Café @ ECOMM 2009
Next steps and chances
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.
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Eltis Café @ ECOMM 2009
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!
Next steps and chances
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Eltis Café @ ECOMM 2009
… and so – we reach her/him:
the “multi-modal” mobility-user
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Eltis Café @ ECOMM 2009
car(at all)
82%
bike(at all)
40%
Modal-choice of the inhabitants of Frankfurt (~ 670.000 p.)
PT (at all)
43%
car (only)
37%
bike (only)
6%
PT (only)
7%
car & PT16%
car& bike14%
PT & bike 5%
PT & car & bike 15%
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Eltis Café @ ECOMM 2009
car(at all)
58%
bike(at all)
57%
Sustainable developement in modal-choice
PT (at all)
59%
car (only)
24%
bike (only)
13%
PT (only)
14%
car & PT5%
car& bike
4%
PT & bike 15%
PT & car
& bike
25%
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Eltis Café @ ECOMM 2009
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Eltis Café @ ECOMM 2009
Thank you
for your attention and patience!
Walter Bien
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