Benefit-estimation for mobility management by stat. data Walter Bien ECOMM-2008 (London, June-2008) 1 Quick & Simple – a new approach for benefit-estimation.

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