Deliverable D 6.1 Impact Assessment Framework

P ojec numbe : F-DUT-2022-0088
D i ing Equi able and Accessible 15 Minu e
Neighbou hood T ans o ma ions
WP6. Impac assessmen and e alua ion
T6.1. Impac assessmen amewo k
Deli e able D 6.1
Impac Assessmen F amewo k
Ve sion: 2.0
Da e: July 4 h, 2025
Responsible pa ne : V ije Uni e si ei B ussel (VUB)
Au ho s: Cha lo e an Vessem (VUB) & Im e Kese ű (VUB)
2
DOCUMENT CHANGE RECORD
Ve sion
Da e
S a us
Au ho
Desc ip ion
0.1
10/02/2025
D a o
in e nal e iew
Cha lo e an Vessem (VUB)
Fi s d a e sion
0.2
26/02/2025
D a o
in e nal e iew
Cha lo e an Vessem (VUB)
& Im e Kese ű (VUB)
Second d a e sion
wi h in e nal VUB
commen s
0.3
03/03/2025
D a o
in e nal e iew
Cha lo e an Vessem (VUB)
& Im e Kese ű (VUB)
Thi d d a e sion
wi h in e nal VUB
commen s
0.4
06/03/2025
D a o
in e nal e iew
wi h eques
o inpu
be o e he
Pa is
conso ium
Cha lo e an Vessem (VUB)
& Im e Kese ű (VUB)
D a e sion
ci cula ed o
conso ium in
p epa a ion o he
Pa is conso ium
mee ing
0.5
28/03/2025
D a o
in e nal e iew
Cha lo e an Vessem (VUB)
& Im e Kese ű (VUB)
Added cla i ica ion
on he ables in he
Li ing Lab da a
collec ion plans
1.0
23/05/2025
D a o
in e nal e iew
by pa ne s
Cha lo e an Vessem (VUB)
& Im e Kese ű (VUB)
Finalised e sion o
be e iewed by
pa ne s BOKU and
UGE
1.1
30/05/2025
In e nal e iew
Roman Klemen schi z
(BOKU), Cha alampidou
Geo gia (BOKU), Yusak
Susilo (BOKU)
P o ision o in e nal
e iew on d a 1.0
1.2
12/06/2025
In e nal e iew
Alain L’Hos is, Hey hem
Adje oud (UGE)
P o ision o in e nal
e iew on d a 1.1
2.0
04/07/2025
Final d a
Cha lo e an Vessem (VUB),
Im e Kese ű (VUB)
Finalisa ion o he
Deli e able o be
published on he
p ojec websi e
3
EXECUTIVE SUMMARY
This deli e able p esen s he Impac Assessmen F amewo k (pa o Task 6.1) de eloped o e alua ing
he Li ing Lab in e en ions implemen ed ac oss he six Li ing Labs o he DREAMS-p ojec : B ussels,
Budapes , Munich, Pa is, U ech and Vienna. As a s a ing poin , his Deli e able e lec s on he easons
o conduc e alua ion, explaining he di e en ypes o e alua ion ha will be used in he DREAMS
p ojec and hei mos impo an concep s. We look in o di e en imings o e alua ion and wha ype
o da a needs o be collec ed, when and why, pe e alua ion ype. The deli e able also explains he uses
o s akeholde e alua ion, S akeholde -Based Impac Sco ing (SIS), and wha is needed o conduc such
an analysis. Then, an o e iew is gi en o he es ablishmen o he DREAMS E alua ion F amewo k, as
well as how he da a collec ion plans pe Li ing Lab we e c ea ed. These da a collec ion plans de ail each
Li ing Lab's objec i es, in e en ions, expec ed impac s, as well as indica o s and a ge . This also
includes an o e iew o wha da a needs o be collec ed, how, by whom and when. Fu he mo e, i
includes a i s o e iew o he s akeholde assessmen (pa o Task 6.2) o be conduc ed in each Li ing
Lab. Fo his, he Deli e able includes an o e iew o each Li ing Lab’s ele an s akeholde s, hei
goals, and he in e en ions al e na i es. This Deli e able se es as a bo h a guideline and a epo o
he Li ing Lab’s in e en ions: i is expec ed o egula ly ecei e upda es as he in e en ions ake place.
These changes a e e lec ed in he documen change eco d.
4
TABLE OF CONTENTS
Lis o igu es ............................................................................................................................. 6
Lis o ables ............................................................................................................................... 6
1 Lis o abb e ia ions ............................................................................................................ 8
2 In oduc ion ........................................................................................................................ 9
2.1 Pu pose o he Deli e able and Wo k Package and in e ac ion wi h o he asks ........................ 9
2.2 S uc u e o he Deli e able ................................................................................................... 10
3 E alua ion asks in he d eams-p ojec .............................................................................. 10
3.1 The goals and scopes o he DREAMS-e alua ion .................................................................... 10
3.2 Impac e alua ion ................................................................................................................. 11
3.3 S akeholde -based e alua ion (T6.2) ...................................................................................... 12
3.4 P ocess E alua ion (T6.3) ....................................................................................................... 14
3.5 Timing o da a collec ion ....................................................................................................... 14
4 The DREAMS E alua ion F amewo k .................................................................................. 15
4.1 Impac assessmen and p ocess e alua ion.................................................................................. 15
4.2.6 Da a collec ion o s akeholde -based assessmen .............................................................. 21
5 De elopmen o Indica o s o he Li ing Lab in e en ions ................................................ 23
5.1 Iden i ica ion o LL indica o s o he DREAMS E alua ion F amewo k .................................... 23
5.1.1 S age o e iew o amewo k c ea ion ............................................................................... 23
5.1.2 Vienna Symposium wo kshop (Oc obe 2024) ..................................................................... 23
5.2 De elopmen o he LL Indica o empla e ............................................................................. 24
6 Da a collec ion plan pe Li ing Lab .................................................................................... 28
6.1 O e iew o he Li ing Labs ................................................................................................... 28
6.2 Li ing Lab B ussels ................................................................................................................. 29
6.2.1 Sho o e iew .................................................................................................................. 29
6.3 Li ing Lab Budapes ............................................................................................................... 34
6.3.1 Sho o e iew .................................................................................................................. 34
6.4 Li ing Lab Munich .................................................................................................................. 36
6.5 Li ing Lab Pa is ...................................................................................................................... 41
6.6 Li ing Lab U ech .................................................................................................................. 47
6.7 Li ing Lab Vienna................................................................................................................... 50
7 Conclusion and nex s eps .................................................................................................. 54
8 Acknowledgemen s ........................................................................................................... 55
9 Re e ences ........................................................................................................................ 55
10 Appendices .................................................................................................................... 56
5
10.1 Appendix I. Templa e o LL leade s ....................................................................................... 56
10.2 Appendix II. Templa e o local s akeholde s .......................................................................... 59
10.3 Appendix III. Pos e empla es o he Vienna Symposium Day ............................................... 62
10.4 Appendix IV. Pos e empla es Vienna – pic u es o he wo kshop session .............................. 68
10.5 Appendix V. S akeholde -based Impac Sco ing guide by Te Bo eld , G. .................................. 76

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LIST OF FIGURES
Figu e 1 The di e en s ages o he e alua ion p ocess and he in e en ion…………………………………..11
Figu e 2 S eps in he impac e alua ion p ocess………………………………………………………………………….....12
Figu e 3 Visualisa ion o he di e en s eps in a S akeholde Impac Sco ing……………………………….…13
Figu e 4 Visualisa ion o he DREAMS E alua ion
F amewo k.………………………………………………………………………………………………………………………………….16
Figu e 5 Example o he wo kshop pos e s…………………………………………………………………………………....24
Figu e 6 Visualisa ion o he o de o he DREAMS Impac Assessmen …………………………………………..26
LIST OF TABLES
Table 1: : Example o an emp y Li ing Lab objec i es, indica o s and measu emen in o ma ion
empla e ……………………………..………………………………………………………………………….........................................28
Table 2: Mobi win objec i es, indica o s and measu emen in o ma ion…………………………………………30
Table 3: Cozywheels objec i es, indica o s and measu emen in o ma ion……………………………………...31
Table 4: Ca gobike objec i es, indica o s and measu emen in o ma ion……………………………………31-32
Table 5: S akeholde s B ussels………………………………………………………………………………………………………32
Table 6: S akeholde objec i es B ussels………………………………………………………………………………………..32
Table 7: Baseline and al e na i es Mobi win……………………………………………………………………………..32-33
Table 8: Baseline and al e na i es Cozywheels………………………………………………………………………..……..33
Table 9: Baseline and al e na i es Ca gobike…………………………………………………………………………….…...33
Table 10: Li ing Lab imeline B ussels…………………………………………………………………………………………..33
Table 11: Budapes in e en ion objec i es, indica o s and measu emen in o ma ion………….………..34
Table 12: S akeholde s Budapes …………………………………………………………………………………………………..35
Table 13: S akeholde goals Budapes …………………………………………………………………………………………...35
Table 14: Baseline and al e na i es Budapes ………………………………………………………………………………..35
Table 15: Li ing Lab imeline Budapes …………………………………………………………………………………………36
Table 16: : Mic o-mobili y poin s’ objec i es, indica o s, and measu emen in o ma ion ………………..37
Table 17: Rewa ds p og am o public anspo and sha ed mobili y’s objec i es, indica o s and
measu emen in o ma ion……………………………………………………………………………………………………….…..38
Table 18: S akeholde s Munich…………………………………………………………………………………………………38-39
Table 19: S akeholde objec i es Munich………………………………………………………………………………..39-40
Table 20: Baseline and al e na i es o mic o-mobili y poin s in Wol a shausen.…………………………40
Table 21: Baseline and al e na i es o mic o-mobili y poin s in Ge e s ied …………………………………40
Table 22: Baseline and al e na i es o he ewa ds p og am o public anspo and sha ed
mobili y………………………………………………………………………………………………………………………………………41
Table 23: Li ing Lab imeline Munich…………………………………………………………………………………………..41
Table 24: New mobili y sys ems objec i es, indica o s and measu emen in o ma ion…………………..42
7
Table 25: Discoun s on sha ed mobili y objec i es, indica o s and measu emen in o ma ion……….43
Table 26: T12 signage objec i es, indica o s and measu emen in o ma ion……………………………43-44
Table 27: S akeholde s Pa is……………………………………………………………………………………………………….44
Table 28: S akeholde goals Pa is ………………………………………………………………………………………….44-45
Table 29: Baseline and al e na i es Pa is……………………………………………………………………………….47-48
Table 30: Li ing Lab imeline Pa is ……………………………………………………………………………………….46-47
Table 31: Discoun s o sha ed bikes objec i es, indica o s and measu emen in o ma ion………….47
Table 32: Sola s a ion objec i es, indica o s and measu emen in o ma ion……………………………….48
Table 33: S akeholde s o e iew U ech …………………………………………………………………………………...48
Table 34: S akeholde goals U ech …………………………………………………………………………………………...48
Table 35: Baseline and al e na i es U ech ………………………………………………………………………………..49
Table 36: Li ing Lab imeline U ech ……………………………………………………………………………………49-50
Table 37: Flexible ac i i y hub objec i es, indica o s and measu emen in o ma ion……………....51-52
Table 38: Bike sha ing s a ion objec i es, indica o s and measu emen in o ma ion……………….52-53
Table 39: S akeholde s Vienna…………………………………………………………………………………………………..53
Table 40: S akeholde goals Vienna……………………………………………………………………………………………53
Table 41: Baseline and al e na i e lexible hub…………………………………………………………………………..53
Table 42: Baseline and al e na i es bike sha ing s a ion…………………………………………………………….54
Table 43: Li ing Lab imeline Vienna………………………………………………………………………………………....54
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1 LIST OF ABBREVIATIONS
15mC: 15-minu e ci y
BME: Budapes i Műszaki és Gazdaság udományi Egye em / Budapes Uni e si y o Technology and
Economics
BOKU: Uni e si ä ü Bodenkul u Wien / Uni e si y o Na u al Resou ces and Li e Sciences, Vienna
CBA: Cos -Bene i Analysis
DAT: DREAMS Accessibili y Tool
DDST: DREAMS Decision Suppo Tool
DREAMS: D i ing Equi able and Accessible 15 Minu e Neighbou hood T ans o ma ions
DUT: D i ing U ban T ansi ions
Dx.x: Deli e able numbe pe Wo k Package
HU: Hogeschool U ech
IKP: In e ac i e Knowledge Pla o m
KPI: Key Pe o mance Indica o
LL: Li ing Lab
MCA: Mul i-C i e ia Analysis
SIS: S akeholde Impac Sco ing
Tx.x: Task numbe pe Wo k Package
TUM: Technische Uni e si ä München / Technical Uni e si y o Munich
TUW: Technische Uni e si ä Wien / Vienna Uni e si y o Technology
UGE: Uni e si é Gus a e Ei el
UT: Uni e si ei Twen e / Twen e Uni e si y
VUB: V ije Uni e si ei B ussel
WP: Wo k Package
9
2 INTRODUCTION
2.1 Pu pose o he Deli e able and Wo k Package and in e ac ion wi h o he asks
This epo is Deli e able 6.1 (D6.1) o he DREAMS (D i ing Equi able and Accessible 15 Minu e
Neighbou hood T ans o ma ions)
1
p ojec , which aims o explo e how co-c ea ed and use -cen ic
mobili y se ices, mobili y and lexible ac i i y hubs can ac i ely con ibu e o c ea ing accessible,
sus ainable, and inclusi e 15-minu e Ci y (15mC) neighbou hoods in he u ban ou ski s
2
o Eu opean
ci ies and egions. This deli e able is pa o Wo k Package 6 (WP6), i led “Impac Assessmen and
E alua ion”. Coo dina ed by he V ije Uni e si ei B ussel (VUB), his WP assesses and syn hesises he
impac s o co-c ea ed scena ios and se ices in he Li ing Labs co e ing angible (clima e, accessibili y,
economic, heal h, li eabili y), non- angible (go e nance, equi y) and s akeholde -speci ic impac s.
Wo k Package 6 consis s o he ollowing h ee Tasks:
• Task 6.1: Impac assessmen amewo k, led by V ije Uni e si ei B ussel (VUB). This ask is
ac i e in p ojec mon hs 14 un il 18 (2025).
• Task 6.2: Impac assessmen o 15mC in e en ions and scena ios, led by he Uni e si y o
Na u al Resou ces and Li e Sciences, Vienna (BOKU). Ac i e in p ojec mon hs 18 un il 32 (2025-
2026).
• Task 6.3: E alua ion Syn hesis, led by VUB. Ac i e in mon hs 32-34 o he p ojec (2026).
This Deli e able is he esul o he co esponding Task 6.1 (T6.1), “Impac Assessmen F amewo k”.
The goal o his Task was o de elop an impac assessmen amewo k o he a ious Li ing Lab (LL)
scena ios, pa o WP5 ha is conce ned wi h he unning o all LLs in he p ojec , and in e en ions on
he di e en laye s o he D eams Decision Suppo Tool (DDST). This ool (cu en ly in de elopmen )
will o e se e al ‘laye s’ o bes p ac ices, me hodologies and p oximi y calcula ions o help u ban
planne s and o he s akeholde s design 15mC neighbou hoods. Wo k Package 6 is speci ically linked o
laye s 3, 4 & 5 o he DDST (pa o Wo k Package 3 and Deli e ables 3.1, 3.2 and 3.3, all o hcoming).
Addi ionally, his Deli e able (D6.1) indexes he measu emen me hods and de ines he da a collec ion
schedule and da a quali y equi emen s o each LL in e en ion, o unc ion as a da a collec ion guide
h oughou he in e en ions. I also includes explana ions o he s akeholde assessmen me hod
S akeholde Impac Sco ing (SIS) ha will be used as pa o T6.2, “Impac assessmen o 15mC
in e en ions and scena ios”, led by he Uni e si y o Na u al Resou ces and Li e Sciences, Vienna
(BOKU). Finally, i includes a i s e alua ion amewo k, which will be used in T6.3, he “E alua ion
Syn hesis” in which he implemen a ion o all LL in e en ions will be e alua ed.
WP6 is scheduled o p oduce wo Deli e ables, he i s one being his cu en Impac Assessmen
F amewo k (D6.1). The second Deli e able will be he Syn he ic e alua ion epo o all Li ing Labs,
which is scheduled o mon h 34, a he end o he p ojec in la e 2026.
As he wo k o WP6 is closely ela ed o he LL’s in e en ions o all Tasks o WP6, i is impo an o
ensu e a good connec ion o WP5, which en ails he Li ing Labs se -up and coo dina ion, led by BME
(Budapes Uni e si y o Technology and Economics). Fo his eason, common mon hly mee ings o
bo h WP5 and WP6 ha e been se -up since Ap il 2025. Addi ionally, he Impac Assessmen F amewo k
and he Assessmen o T6.2 will also connec o a ious laye s o he WP3 D eams Decision Suppo
Tool, especially o T3.5, “S a egic objec i es and socie al impac s”, led by UGE (Uni e si é Gus a e
1
A lis o all abb e ia ions can be ound a he beginning o his Deli e able.
2
In he DREAMS-p ojec , u ban ou ski s a e unde s ood as “Medium-sized a eas o neighbou hoods in
he nea con ex o an u ban a ea, whe e high ca dependency is p esen and a s ong economical and
unc ional connec ion o he ci y is obse ed, p ima ily h ough daily wo k commu es” (Deli e able 2.1,
DREAMS-p ojec , 2024).
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Figu e 4: Visualisa ion o he DREAMS E alua ion F amewo k.
In o de o make Figu e 4 easie o unde s and, he nex sec ions will ou line he de ini ion o objec i es;
indica o s and speci ically indica o s; a ge s; possible da a collec ion me hods o hese indica o s and
KPIs; and he p inciples o he da a collec ion plans o he DREAMS LLs.
4.2 Key elemen s o he DREAMS E alua ion F amewo k
4.2.1 Objec i es
In he DREAMS E alua ion F amewo k, objec i es a e he o e a ching goals o an in e en ion o
p ojec . As such, hey can e e o ei he an ou pu o an ou come, meaning ha hey ei he connec o a
LL-speci ic goal (ou pu ), o a p ojec - ela ed one (ou come). To gi e an example o each: an ou come
objec i e could be ‘ os e ing 15-minu e accessibili y o key des ina ions in u ban ou ski s’, o
‘suppo ing modal shi o sus ainable modes’. An example o an ou pu objec i e could be ‘inc easing
up ake o sha ed bikes’ o ‘be e unde s anding o he a ea’s business po en ial’. Objec i es can be
linked o one o se e al indica o s (see nex sec ion) and hey can also be linked o s akeholde s in SIS
e alua ions.
4.2.2 Indica o s
Once he objec i es o he p ojec and/o he in e en ion ha e been es ablished, i is ime o con inue
o se indica o s. Indica o s a e measu able elemen s ha a e used o ack he p og ess, pe o mance
o quali y o a p ojec , p ocess, o sys em. They can be bo h quali a i e and quan i a i e in na u e. Wi hin
( anspo ) p ojec s, indica o s a e used o gain insigh s in a p ojec ’s cu en pe o mance, and o ake
e idence-based decisions ega ding he p ojec ’s u u e di ec ions.
Indica o s can be ca ego ised in o wo main ypes: desc ip i e indica o s and pe o mance indica o s.
Desc ip i e indica o s assess he s a e o a sys em a a gi en poin in ime, allowing o c oss-sec ional
e alua ions. Pe o mance indica o s, on he o he hand, acili a e compa isons o desc ip i e indica o s
o e di e en pe iods, enabling he assessmen o p og ess owa d speci ic a ge s (Chakh ou a &
Pojani, 2016).
In a op-down app oach, a se o indica o s is c ea ed based on li e a u e esea ch o in e iews wi h
expe s, keeping in mind he main scope(s) o he p ojec and i s in e en ions. When choosing his
app oach, Do an asse s ha indica o s should adhe e o he SMART c i e ia, meaning hey mus be (a)
speci ic, (b) measu able, (c) achie able, (d) ele an , and (e) ime-bound (Do an, 1981 in Bje ke &
Renge , 2017, p. 125). Simila ly, Gillis e al. (2015) a gue ha indica o s should be (a) speci ic, (b)
comp ehensi e, (c) p ecisely measu able, (d) sensi i e, (e) echnologically neu al, and ( ) scalable.

17
When selec ing indica o s in a bo om-up manne , he p ojec pa ne and ele an s akeholde s c ea e
a se o indica o s based on hei planned in e en ions and wha hey would wan o achie e and assess
in hei speci ic con ex .
The selec ion o indica o s should conside he empo al and spa ial dimension o he e alua ion.
Addi ionally, he choice o indica o se s should be guided by he scale o he e alua ion, he con ex ual
ac o s—including en i onmen al, geog aphical, and socioeconomic conside a ions— he iming o he
assessmen , and he a ailabili y o ele an da a (Gudmundsson, 2004).
4.2.3 Indica o s o he 15-minu e ci y in u ban ou ski s
The 15-minu e Ci y (15mC) is an u ban planning concep ha emphasises p oximi y-based accessibili y,
ensu ing ha neighbou hood esiden s can mee hei daily needs—such as wo k, educa ion,
heal hca e, shopping, and leisu e—wi hin a 15-minu e walk o bicycle ide om hei homes (Mo eno
e al., 2021). While much o he exis ing esea ch and applica ion o his model ha e ocused on dense
u ban co es, i s implemen a ion in u ban ou ski s p esen s unique challenges, pa icula ly ega ding
anspo in as uc u e, in e connec i i y, and accessibili y o ameni ies. As he goal o he DREAMS-
p ojec is o “explo e how co-c ea ed and use -cen ic mobili y se ices, mobili y and lexible ac i i y
hubs can ac i ely con ibu e o c ea ing accessible, sus ainable, and inclusi e 15mC neighbou hoods in
he u ban ou ski s o Eu opean ci ies and egions”, his indica es a need o a speci ic se o indica o s
ocused on hese co e elemen s o he p ojec .
So a , no s anda d indica o s dedica ed o sus ainable 15mC in u ban ou ski s ha e been iden i ied.
Howe e , he DREAMS-p ojec p oposal did indica e six key impac s a eas ha a e essen ial o assess
he p ojec ’s in e en ions. These key a eas a e : Accessibili y, Ca bon Emissions, Li eabili y, Heal h,
Economic Impac , and Equi y.
A mo e in-dep h analysis and explana ion o hese hemes and he KPIs ha will be connec ed o hese
domains will be included in D3.3, which includes he esul s om T3.5, “S a egic Objec i es and Socie al
Impac s”. This ask will de ine he o e all s a egic objec i es o he p ojec , which will as such no be
discussed in de ail in his Deli e able (6.1). Howe e , as D3.3 is only scheduled o be published in la e
2025, we gi e a sho o e iew o he main hemes down below.
Designing a cohe en and con ex -sensi i e indica o amewo k o 15mC e alua ion in u ban ou ski s
equi es bo h heo e ical g ounding and p ac ical conside a ion o wha is measu able ac oss di e se
local con ex s and condi ions. T3.5 con ibu es o his e o by iden i ying a co e se o accessibili y
indica o s ( o be in eg a ed in o he DREAMS Accessibili y Tool (DAT)), and es ablishing a b oade se
o addi ional indica o s ( eeding in o he In e ac i e Knowledge Pla o m (IKP)) ha would allow a
comp ehensi e p ojec -le el impac assessmen . Toge he , hese ools aim o suppo p ac i ione s in
selec ing app op ia e me ics based on hei speci ic planning p io i ies.
The indica o selec ion p ocess in ol ed igo ous e alua ion o each po en ial indica o 's sensi i i y o
LL ac i i ies, ele ance o indi idual LLs, and measu abili y ac oss di e en con ex s. This sc eening
p ocess, ou lined in mo e de ail in he o hcoming comp ehensi e indica o analysis in Deli e able 3.3,
has led o he iden i ica ion o a e ined se o indica o s ha is designed o ensu e bo h p ac ical
applicabili y in he p ojec LL con ex s and a s ong alignmen wi h he p ojec 's s a egic objec i es.
While esea ch on he 15mC concep in connec ion o u ban ou ski s is sca ce, D2.1 o he DREAMS-
p ojec , i led "Explo ing he 15-minu e ci y concep o u ban ou ski s: a sys ema ic li e a u e e iew”,
w i en by he Uni e si ei Twen e (UT), has highligh ed six key a eas ha need o be conside ed in his
con ex . These key a eas a e: Densi y, Di e si y, Design, Human pe spec i es, Go e nance, and Business.
In he sec ion below, hese a eas ha e been ma ched o indica o s. We ha e also chosen o add a se en h
a ea on En i onmen and Sus ainabili y, as his is a key componen o a 15mC s a egy (Mo eno e al.,
2021). I is impo an o no e ha no all impac a eas a e equally ep esen ed in he inal indica o se ,
as his e lec s he eali y ha no all LLs a e conduc ing ac i i ies o which ce ain indica o s would be
sensi i e.
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1. Densi y
Fi s , a undamen al aspec o he 15mC concep is p oximi y o essen ial se ices, which e e s o he
accessibili y o ameni ies such as heal hca e, educa ion, e ail, and ec ea ional a eas wi hin a 15-minu e
walking o cycling adius. Fo example, Chia adia e al. (2024) p opose measu ing se ice in ensi y
wi hin a gi en a ea o assess spa ial inequali ies in accessibili y. This app oach helps iden i y gaps in
se ice dis ibu ion and suppo s u ban planning s a egies aimed a educing spa ial dispa i ies. This
aspec o he 15mC also en ails he p esence o (essen ial) ameni ies.
The il e ed indica o se in he DREAMS-p ojec includes:
• T a el imes: A e age a el ime o essen ial se ices
• Se ice in ensi y index: Numbe and dis ibu ion o essen ial se ices wi hin a 15-minu e
adius
• P oximi y o daily needs: Pe cen age o popula ion wi hin x-minu e adius o ameni ies
• PT ca chmen : Pe cen age o popula ion wi hin x-minu e adius o a ansi s op
• A ailabili y o sha ed mobili y op ions: Numbe o sha ed bikes/scoo e s/ca s a ailable pe
esiden o wi hin x-minu e adius
• Residen sa is ac ion: Sco es ega ding accessibili y o di e en ameni ies
2. Land use di e si y
Land use di e si y is measu ed h ough indica o s o mixed-use de elopmen . A balanced mix o
esiden ial, comme cial, and ins i u ional land uses can help os e local economic ac i i y and educe
he need o long-dis ance a el (Zhang e al., 2022). This is pa icula ly ele an o he DREAMS-
p ojec , as we speci ically conside he e ec i eness o mobili y in e en ions in pe i-u ban a eas, which
depends on he a ailabili y o se ices wi hin a sho a el dis ance. The p o ision o public spaces,
ec ea ional and g een a eas is ano he key aspec o he 15mC model. S udies emphasise he
impo ance o access o pa ks and ec ea ional a eas in p omo ing physical ac i i y, social cohesion, and
o e all well-being (Chia adia e al., 2024). E alua ing he p opo ion o esiden s wi h access o (high-
quali y) g een spaces wi hin a 15-minu e adius can p o ide insigh in o he li eabili y o u ban
ou ski s.
Al hough he il e ing p ocess e ealed limi ed sensi i i y o cu en LL ac i i ies and challenges ela ed
o measu abili y, he ollowing indica o s we e e ained in he inal se because hey can be eliably
measu ed h ough he DREAMS Accessibili y Tool (DAT):
• Public spaces & ec ea ion: a eas accessible wi hin an x-min adius
• G een space accessibili y: % o popula ion wi hin an x-min adius o pa ks and g een space
• Spo & ec ea ion: % o popula ion wi hin an x-min adius o ields, playg ounds, ana o he
ec ea ional ameni ies
3. Design
The design dimension mainly ocuses on he physical in as uc u e ha enables 15mC unc ionali y
h ough he moni o ing o me ics such as he walkabili y index ha helps assess he quali y o
pedes ian in as uc u e, and conside s ac o s such as sidewalk a ailabili y, pedes ian sa e y, and
ou e di ec ness (Chia adia e al., 2024). Howe e , adi ional walkabili y and cyclabili y indica o s
showed limi ed sensi i i y o he speci ic LL in e en ions being es ed ac oss he Li ing Labs. The e’s
clea ly a need o u u e esea ch o de elop design indica o s ha be e cap u e he impac o
in e en ions like he implemen a ion o new inno a i e mobili y se ices on he quali y o
in as uc u e in u ban ou ski s.
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4. Human pe spec i es
Social equi y and inclusion a e also cen al o he e alua ion o 15mC ini ia i es. Equi y indica o s assess
whe he all demog aphic g oups—including women, low-income households, olde adul s, and people
wi h disabili ies—ha e equal access o essen ial se ices and sus ainable mobili y op ions. By
in eg a ing hese indica o s in o he e alua ion amewo k, he p ojec can ensu e ha 15mC p inciples
bene i all segmen s o he popula ion, a he han ein o cing exis ing spa ial inequali ies (Zhang e al.,
2022).
Ou cu en il e ed indica o se includes:
• Di e si y: Pe cen age o emale and elde ly se ice/ac i i y use s
• Repo ed accessibili y o ameni ies o a ge g oups
• Accessibili y o he se ice/ac i i y o a ge g oups
• T a el cos : Es ima ed a e age a el cos pe ip o pe iod
5. Go e nance
Go e nance ep esen s a c i ical ye o en unde explo ed dimension o 15mC implemen a ion,
pa icula ly in u ban ou ski s whe e adi ional op-down planning app oaches may p o e insu icien .
E ec i e go e nance in his con ex equi es collabo a i e and pa icipa o y p ocesses ha engage a
b oad ange o s akeholde s, including public au ho i ies, local businesses, esiden s, and especially
unde ep esen ed and unde se ed communi ies, in he co-c ea ion o mobili y solu ions and u ban
se ices (Pozoukidou & Cha ziyiannaki, 2021).
The go e nance amewo k o 15mC in u ban ou ski s mus add ess se e al key challenges:
coo dina ing ac oss mul iple adminis a i e bounda ies ha o en cha ac e ize pe i-u ban a eas,
ensu ing inclusi e pa icipa ion in planning p ocesses, and es ablishing mechanisms o adap i e
managemen o a ious in e en ions.
Howe e , go e nance amewo ks enable long e m s a egies and a e di icul o assess wi hin he
ela i ely sho e alua ion pe iods o mos u ban expe imen a ion p ojec s., Ou indica o sc eening
p ocess e lec ed hese di icul ies: go e nance- ela ed indica o s o en lack di ec sensi i i y o Li ing
Lab (LL) ac i i ies o p esen measu emen challenges. While indica o s such as "Numbe o public
e en s o ganized by public au ho i ies" and "Residen sa is ac ion sco es ega ding communica ion,
decision-making" we e iden i ied in he comp ehensi e analysis, only one key indica o is cu en ly
e ained:
• Pe cen age o a ge -a ea esiden s who a ended wo kshops, ga e eedback o
pa icipa ed in a su ey
6. Business
Economic i ali y is an impo an ac o in e alua ing 15mC p ojec s. Indica o s such as local business
ac i i y, employmen a es, and comme cial di e si y wi hin a 15-minu e adius can o e aluable
insigh s in o he economic sus ainabili y o u ban neighbou hoods (Chia adia e al., 2024). Howe e ,
hese indica o s showed limi ed alignmen wi h cu en LL ac i i ies, wi h only one indica o e ained
in he il e ed se :
• Willingness o pay
7. En i onmen and sus ainabili y
En i onmen al impac assessmen s wi hin he 15mC amewo k ypically ocus on educ ions in ca bon
emissions due o inc eased accessibili y and dec eased eliance on p i a e ehicles. Measu ing
anspo - ela ed emissions be o e and a e in e en ions can p o ide insigh in o he en i onmen al
bene i s o shi ing owa ds localized mobili y solu ions (Zhang e al., 2022). By in eg a ing hese
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indica o s in o he e alua ion amewo k o he DREAMS p ojec , we ensu e ha he assessmen ex ends
beyond con en ional anspo - ocused KPIs o cap u e he b oade socio-spa ial impac s o 15mC
in e en ions. This app oach aligns wi h ecen esea ch emphasizing he need o mul idimensional
e alua ion me hods in 15mC planning (Chia adia e al., 2024; Zhang e al., 2022). Howe e , as o he
cu en si ua ion in he LLs, ew en i onmen al indica o s go h ough he sc eening p ocess because o
he measu abili y challenges. he il e ed indica o se only includes:
• Repo ed numbe o ca ips ( o speci ic a ge g oups in he LL a ea)
• Up ake o sha ed mobili y: Including sha ed mobili y usage, numbe o ips, numbe o new
use s, and dis ance co e ed
I is impo an o no e ha , ega dless o hei cu en ca ego isa ion wi hin he e alua ion amewo k,
ce ain indica o s may demons a e ele ance ac oss mul iple hema ic ca ego ies. This is due o he
inhe en ly o e lapping na u e o impac s ac oss dimensions such as accessibili y, sus ainabili y, human
expe ience, and economic iabili y. Mo eo e , he cu en se o indica o s e lec s he p esen s a e o
Li ing Lab ac i i ies and should be conside ed a ounda ional laye , open o e inemen and expansion
as in e en ions e ol e. This app oach ensu es ha he e alua ion amewo k emains g ounded in
measu able ou comes while main aining alignmen wi h he b oade heo e ical unde s anding o 15mC
p inciples in u ban ou ski s con ex s.
4.2.4 Ta ge s
A e deciding wha indica o s a e ele an o measu e ou come and ou pu , i is be necessa y o
o mula e wha quali ies as a success o his indica o and objec i e. Se ing a ge s plays a c ucial ole
in e alua ion, as hey enable he ex-pos assessmen o how well he objec i es ha e been achie ed.
Ta ge s a e di ec ly ied o he p ojec ’s main objec i es and he indica o s. In many cases, ailing o
mee key a ge s can esul in he p ojec being deemed unsuccess ul, e en i i pe o ms well on o he
c i e ia o sco es well o e all based on he ull e alua ion amewo k (Kese u e al., 2016). Ta ge s se
a quan i iable h eshold ha indica es di ec ion (i.e., an inc ease o a dec ease) and a numbe o
pe cen age (i.e., inc eased up ake o he se ice wi h 10%). Simila ly o indica o s, a ge s should also
comply wi h he SMART c i e ia ou lined abo e (Bje ke and Renge , 2017; Hyllenius e al., 2009). This
en ails he ollowing elemen s:
Speci ic: a ge s should be clea ly de ined, p e e ably in quan i iable e ms. Fo example, a a ge could
be o educe peak-hou ca a ic in a subu ban neighbou hood by 15%. This a ge assumes ha
baseline a ic da a is a ailable and ha a ic can be measu ed bo h be o e and a e he p ojec . I
quan i ica ion is no possible, a quali a i e assessmen can be used, wi h e ms like ‘imp o emen ’ o
‘posi i e’ impac .
Measu able: a ge s can only be moni o ed i bo h he baseline and pos -p ojec condi ions a e
measu able. In ou example, i should be possible o measu e peak-hou a ic be o e he p ojec begins
and a e i s comple ion.
Ambi ious and Accep ed: ambi ious a ge s mo i a e p og ess h oughou he p ojec . Addi ionally,
a ge s should be suppo ed by bo h decision-make s and he p ojec eam.
Realis ic: while a ge s should be ambi ious, hey mus also be achie able. Fo ins ance, i public
anspo usage declines by wo pe cen annually, main aining he same le el o public anspo use as
he p e ious yea may be a ealis ic a ge .
Time-bound: he ime ame wi hin which a ge s should be achie ed should be de ined. In ou example,
he a ge o educe peak-hou ca a ic be ween 2025 and 2027 would be ime-bound.
O cou se, a ge s should be ambi ious, bu hey should also easible. This is why i is impo an o ha e
access o baseline da a ega ding he a ge indica o , so ha he a ge can be se a an app op ia e
le el. I is also impo an o no e ha in he DREAMS-p ojec , a ge s se e as an ambi ion, bu ailing o
mee hem will ha e no nega i e consequences on he LL pa ne s (beyond he lack o success o hei
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in e en ion). These a ge s a e s ic ly mean o p o ide an aim o he in e en ion. In he in e iews
planned o T6.3, we will hen discuss i he a ge s we e me , and he easons o success o ailu e o
mee hem.
4.2.5 Da a collec ion me hods
Impac assessmen is based on he sys ema ic collec ion o quan i a i e and quali a i e da a. Da a
collec ion mus ensu e ha he esul s a e eliable and ep esen a i e o he a ge popula ion o he
p ojec . The choice o he da a collec ion me hod depends on he budge a ailable, a ailabili y o ex e nal
da a, expe ise o he p ojec managemen eam and imescale o he p ojec .
The ollowing me hods can be used o collec da a depending on he ype o he indica o :
Di ec measu emen o indica o s: he mos eliable way o collec ing indica o da a is he di ec
measu emen o he indica o s using impac measu emen de ices (e.g. NHx, PM2.5, noise), acking
equipmen (GPS) o ca ying ou coun s o su eys ( a ic da a, passenge numbe s, e c.). A he same
ime, i is he mos esou ce-in ensi e way o da a collec ion as hese measu emen s a e expensi e and
equi e he in ol emen o expe s.
Su eys: some indica o s canno be measu ed di ec ly as hey a e quali a i e (e.g. pe cep ion o sa e y,
sa is ac ion wi h ou e planning se ices, quali y o u ban space, socio-poli ical accep ance). Such
indica o s equi e a su ey o ci izens and/o anspo use s.
Es ima ion: in some cases, di ec measu emen o indica o s may no be possible because o lack o
esou ces o he complexi y o such measu emen s. I is especially ue o such cos -in ensi e ac i i ies
as ai quali y moni o ing, noise measu emen s and modelling. In hese cases, i is possible o es ima e
he impac s h ough o he p oxy indica o s. Ai pollu ion and noise a e, o example, di ec ly ela ed o
he numbe o kilome es a elled by di e en anspo modes. Moni o ing he numbe o passenge
o ehicle kilome es a elled and using a e age emission ac o s hese indica o s can be es ima ed.
Modelling: Indica o s ha should be collec ed om se e al loca ions a e o en modelled. Such
indica o s include noise, a ic and ai pollu ion. Using a compu e model o es ima e hem educes he
cos o da a collec ion. I , howe e , equi es expe ise o he in ol emen o an ex e nal consul an .
O icial s a is ics: some indica o s may be a ailable om o icial na ional, egional, local o ope a o s’
s a is ics. Typically, indica o s like he numbe and se e i y o acciden s, public anspo passenge s
e c. can be de i ed om such s a is ics. Ve y o en, howe e , he spa ial ex en and he ime pe iod
co e ed by o icial s a is ics a e di e en o he p ojec ’s geog aphic and empo al scope.
The app op ia e da a collec ion me hod will be iden i ied o each DREAMS LL in e en ion and
indica o in he indi idual LL da a collec ion plans (see below)
4.2.6 Da a collec ion o s akeholde -based assessmen
This sec ion ou lines he key elemen s o he s akeholde assessmen me hod ‘S akeholde Impac
Sco ing’ (SIS), which will be used in all LLs as pa o T6.2. In o de o conduc a SIS e alua ion, he da a
needs pe key s ep (desc ibed in Sec ion 2.2) a e as ollows:
1. Da a collec ion
o Ga he ing s uc u ed and uns uc u ed da a om mul iple sou ces. This can be om
sou ces such as li e a u e e iews, bu can also come om expe consul a ions, and
s akeholde inpu s. S akeholde inpu s and consul a ions can be o ganised in di e en
ways; o example, a wo kshop day can be held o a empla e can be made o be illed
ou by he expe o s akeholde (simila o he empla e ha can be seen in Appendix
II).
o Da a: he da a used can also come om di e en sou ces. Repo s, s a is ical da ase s,
expe opinions, and policy documen s can all unc ion as da a o a SIS.

22
o The da a collec ion will be done by each LL indi idually. The LL leade (s) will ha e o
o ganise he da a collec ion o hei own ele an local s akeholde s. As he LLs each
ha e hei own opic and scope, he decision on who a e ele an s akeholde s o ex-
pe s will di e pe LL. A i s o e iew o he LLs local s akeholde s can be seen in
Sec ion 6.
2. Da a p ocessing and in eg a ion
o This en ails s anda dising and in eg a ing da a o c ea e a cohe en da ase o analysis.
o Da a: in o de o be eady o use, he da a should be cleaned and compiled in o o ma -
ed da ase s.
3. Analy ical modelling and scena io de elopmen
o Employing quali a i e and quan i a i e me hods o analyse ends, ela ionships, and
po en ial ou comes.
o Da a: Fo ecas models, scena io simula ions, and compa a i e assessmen s.
4. Visualisa ion and communica ion
o P esen ing esul s in an accessible manne o in o m decision-make s and s akehold-
e s.
o Da a: G aphical ep esen a ions, dashboa ds, and summa y epo s.
I is impo an o no e ha each LL will be esponsible o conduc ing hei own SIS. As he LLs a y in
hei scope, he inal choices as o who a e ele an expe s o s akeholde s, as well as wha ype o da a
will be used as inpu will a y be ween he a ious LLs. Each LL leade has he inal say o e hei spe-
ci ic SIS analysis. As he c ea o s o he me hod, he VUB will assis he LLs in pe o ming hei SIS anal-
ysis.
4.2.7 S akeholde pe spec i es and iden i ica ion o baselines and al e na i es
Nex o he objec i es, po en ial impac s, indica o s, a ge s, and measu emen me hods and
equencies, he s akeholde empla e desc ibed abo e also included ques ions ega ding s akeholde
p e e ences as well as he iden i ica ion o scena ios and al e na i es. These las wo concep s a e key
elemen s o he SIS analysis used in T6.2.
The s akeholde empla es we e dis ibu ed by he VUB o he LL leade s in No embe 2024, who in
u n dis ibu ed he empla e o hei ele an local pa ne s. The selec ion o local s akeholde was
made au onomously by each LL leade . The dis ibu ion i sel happened in mul iple ways: some pa ne s
held a mee ing wi h he local s akeholde (s) o discuss hei objec i es, illing ou he empla e oge he ,
while o he s had he s akeholde ill ou he empla e by hemsel es. The ull empla e can be ound in
Appendix II. In any case, his empla e ep esen s a i s explo a ion o he a ious s akeholde
pe spec i es p esen h oughou he di e en LL and hei in e en ions. I se es as a s a ing poin o
T6.2, bu i will ha e o be enhanced wi h mo e da a collec ion ega ding he a ious s akeholde
pe spec i es, objec i es, and p e e ences.
Addi ionally, i was necessa y o es ablish a baseline as well as al e na i es o each in e en ion. These
sec ions on scena ios and al e na i es we e pa o he LL leade s akeholde empla es ha we e
dis ibu ed by VUB o he LL leade s in he same ime ame as he s akeholde empla es. This empla e
included a sec ion in which he LL leade s we e asked o iden i y a baseline and al e na i es o each
in e en ion. The baseline is a si ua ion wi hou any in e en ion and al e na i es a e di e en e sions
o he in e en ions’ implemen a ion. These may include di e en designs, loca ions, policies, o
app oaches. An example o his could be:
Baseline: he e a e no sha ed bikes in he Li ing Lab loca ion [cu en si ua ion].
Al e na i e A: sha ed bikes a e placed in a cen al loca ion.
Al e na i e B: sha ed bikes and ca go-bikes a e placed in a cen al loca ion.
Al e na i e C: sha ed bikes a e placed in a cen al loca ion and h oughou he neighbou -
hood.
23
Al e na i es can be e y simila o each o he , such as A-B-C abo e, bu hey can also be less simila :
Al e na i e D: sha ed ca s a e placed in a cen al loca ion
Al e na i e E: we hos a ca é o neighbou s.
Sec ion 6 p o ides he con ac ed local s akeholde s as well as hei goals and he baseline and
al e na i es d a ed by each LL leade . S akeholde in ol emen is o en a long- e m p ocess, whe e
o en mul iple mee ings a e necessa y o cla i y he goals and iewpoin s o he s akeholde s. A anging
such mee ings can also p o e di icul wi h ce ain s akeholde g oups. As such, his is an ongoing
p ocess in mos Li ing Labs, whe e changes o upda es a e expec ed h oughou he cou se o he
p ojec and he speci ic in e en ions. Such changes will be e lec ed in his Deli e able, p ima ily in
Sec ion 6.
5 DEVELOPMENT OF INDICATORS FOR THE LIVING LAB
INTERVENTIONS
A e ha ing es ablished he o e a ching objec i es o he p ojec , i is ime o conside each Li ing Lab’s
indi idual goals and in e en ions. This was a pa o Task 6.1, which was ca ied ou by he VUB. This
p ocess had se e al s ages, which a e explained in he ollowing sec ions.
5.1 Iden i ica ion o LL indica o s o he DREAMS E alua ion F amewo k
5.1.1 S age o e iew o amewo k c ea ion
Fi s , he LL loca ions and local in e en ion we e selec ed by local pa ne s ( he uni e si y pa ne s
and hei local s akeholde s). This happened du ing he i s mon hs o he p ojec , s a ing om Ma ch
2024 un il No embe 2024. Each LL eam could decide hese o hemsel es, and hese we e pa ially
p ede ined be o e he s a o he p ojec (du ing he p oposal w i ing s age).
5.1.2 Vienna Symposium wo kshop (Oc obe 2024)
Once he plans o he LLs we e known, he VUB o ganised a wo kshop du ing he DREAMS Vienna
Symposium day on Oc obe 11 h, 2024. The goal o his wo kshop was o ha e a i s explo a ion o he
possible goals and objec i es o each LL. Toge he wi h pa ne s om each ci y plus membe s o he
local audience, he wo kshop c ea ed a i s lis o expec ed impac s o each LL loca ion, as well as
possible KPIs and hei measu emen me hod and equency. he only excep ion o his p ocess was he
Pa is LL, as he e was no p ojec pa ne p esen o ep esen hei Li ing Lab.
The h ee esea ch ques ions o his wo kshop session we e:
• Wha impac would you expec om he in e en ion o he Li ing Lab (posi i e o nega i e)?
• Wha indica o s would you use o measu e hese impac s?
• How would you measu e hese impac s?
Figu e 5 shows an example o he B ussels pos e mid-session, wi h answe s o he i s wo ques ions
s a ed he e.
24
Figu e 5: Example o he wo kshop pos e s, in his case he B ussels Li ing Lab (pho o c edi s: VUB)
The o he pos e s, as well as he empla es ha we e used in his wo kshop can be ound in Appendices
III and IV.
5.2 De elopmen o he LL Indica o empla e
Based on hese i s esul s om he Vienna wo kshop, he VUB c ea ed a i s hema ic o e iew o he
epo ed impac s, indica o s and measu emen me hods. These we e hen used o c a wo empla es:
one o he Li ing Lab leading pa ne , and one o be illed ou by local s akeholde s (wi h he help o
he LL leade (s)). These empla es we e used o indica e objec i es, expec ed impac s, indica o s and
possible measu emen me hods o each indi idual LL loca ion. These empla es can be ound in
Appendix I. The c ea ion o hese empla es was done in No embe 2024, and he pe iod o illing ou
he empla es ini ially ook place du ing Decembe 2024. Howe e , as i p o ed di icul o some
pa ne s o o ganise a mee ing wi h hei local s akeholde s, his imeline was ex ended in o Janua y
and Feb ua y o 2025.
5.2.1 Templa e collec ion and analysis
These indi idual empla es we e analysed by he VUB o iabili y and o common hemes. As all LL’s
a ied in hei in e en ions and app oaches, no many commonali ies we e ound. These common
hemes we e discussed in a WP6 pa ne mee ing, as well as a he Pa is Conso ium mee ing in Ma ch
2025. A e his mee ing i , was decided o ollow up on he empla es sepa a ely o each Li ing Lab and
de elop LL-speci ic indica o s, wi h he mo e o e a ching se o indica o s being pa o Task 3.5
25
ins ead. I was decided ha ins ead, each indica o in he da a collec ion plan would be classi ied as
ei he e e ing o an ou come (i.e., ela ed o he p ojec ) o ou pu (i.e., ela ed o he in e en ion). A
ull lis o ou pu indica o s is being de eloped as pa o Task 3.5, which will be p esen ed in a
o hcoming deli e able.
5.2.2 Da a collec ion plan inalisa ion
Based on he a ie y o in e en ions and hei impac s, he decision was made o c ea e a empla e ha
would be o e a ching bu s ill allowed o ailo o each indi idual Li ing Lab and in e en ion.
Pe Li ing Lab, his amewo k includes in o ma ion on he in e en ions, as well as a desc ip ion o he
da a needs o he ou pu and he in e en ion ou come. Depending on he exac con en s o he
in e en ion pe LL, his can en ail a mix o da a o be collec ex-an e, ex-pos and con inuous collec ion.
These plans we e ‘ inalised’ as a i s d a a e Pa is Conso ium mee ing in Ma ch 2025, a e he VUB
held mee ings wi h all LL leade s sepa a ely in Ma ch and Ap il 2025.
5.3 Measu emen App oaches
The e alua ion o in e en ions ac oss he di e en Li ing Labs employs a combina ion o quali a i e
and quan i a i e me hodologies. The measu emen amewo k ollows an ex-an e, ex-du an e and ex-
pos e alua ion s uc u e. Conside ing he a ying objec i es and expec ed impac s o each LL and
in e en ion, he measu emen app oaches a e ailo ed o speci ic con ex s while main aining common
elemen s ac oss loca ions. These common elemen s include sha ed hemes and me hodologies, such as
he use o su eys, acking da a om in e en ion- ela ed ehicles, and a mix o quali a i e and
quan i a i e app oaches.
As shown in Figu e 6 below he measu emen p ocess is s uc u ed in ou key s ages:
1. Planning: de ining objec i es, selec ing indica o s (KPIs), and iden i ying app op ia e da a
collec ion me hods.
2. Baseline measu emen : conduc ing ex-an e da a collec ion o es ablish a e e ence poin be o e
in e en ion implemen a ion. This s ep was pa o he LL leade empla e (explained abo e).
3. Pilo /measu e implemen a ion: ga he ing ex-pos da a and compa ing i o baseline
measu emen s o assess impac .
4. Re lec ion: in e p e ing esul s and o mula ing ecommenda ions based on indings.
The Re lec ion s age will be he opic o Deli e able 6.2, which will be he E alua ion Syn hesis o he
DREAMS-p ojec , so i will no be discussed he e ye . Deli e able 6.2 will be published a he end o he
p ojec (la e 2026).
5.4 Measu emen imeline and me hods
This sec ion ou lines he speci ic da a collec ion me hods used in each s age o he measu emen
p ocess, ensu ing cla i y in he alignmen o he di e en quali a i e and quan i a i e app oaches used
in he LLs wi h he o e all DREAMS E alua ion F amewo k. As he in e en ions do no all ha e he
same du a ion and a e no scheduled o ake place a he same momen ac oss LLs, a gene al imeline in
mon hs canno be gi en he e. Fo his, we e e o he imeline pe Li ing Lab in Sec ion 6. The gene al
s ages ha all LL in e en ions will go h ough in isualised in Figu e 6 below.
32
posi i ely o
e y posi i ely
1,2,3,
4
Imp o ed
se ice in he
a ea
Finding a sui able
loca ion o a
s a ion
Ou come
1 s a ion
iden i ied pe
bike
Quali a i e me hods
(su ey/in e iew/ o
cus g oup)
One- ime, ex-
pos
Mpac
1,2
Imp o ed
isibili y
Inc eased
ecogni ion/in e es
by pilo use s
Ou pu
10 use s
egis e ed pe
bike
Quali a i e me hods
(su ey/in e iew/ o
cus g oup)
One- ime, ex-
pos
Mpac
Table 4: Ca gobike objec i es, indica o s and measu emen in o ma ion
6.2.3 S akeholde -based assessmen
Name (o ganisa ion)
S akeholde g oup
Cambio
P ojec -suppo ing
B ussels Mobili y
Decision-make
Table 5: S akeholde s o e iew B ussels
Objec i es/local goals:
S akeholde
Goals o he in e en ion(s)
Cambio
P o ide eedback
Sha e da a whe e app op ia e
P o ide ma e ial suppo
Pa icipa e in wo kshops
P o ide ma e ial suppo (e.g. a ca go bike)
B ussels Mobili y
S udy he po en ial o ca go bikes o modal shi
Gain insigh s om he sha ing o Cambio ehicles ia Mobi win o
he wo k ca ied ou by he PRM wo king g oup wi hin he
amewo k o he G een Deal Inclusi e Ca sha ing
P o ide a mo e comp ehensi e documen a ion o ca sha ing
be ween indi iduals o be ween indi iduals and o ganisa ions
Table 6: S akeholde goals B ussels
Mobi win
Baseline (please s a e):
The e is al eady a small numbe o ides (wi hou a sha ed ca )
om he LL loca ion + (assump ion) he e a e al eady in o mally
o ganised ides be ween neighbou s
Al e na i e A:
We enhance he local an enna in he LL loca ions by o e ing sha ed
ehicles o he olun ee s.

33
Al e na i e B:
O he anspo op ions + o he o ganisa ional op ions (TBD a e
su ey)
Al e na i e C:
We do no de elop he local an enna u he o ind local olun ee s.
Ins ead, we explo e he local in e es in he se ice.
Table 7: Baseline and al e na i es Mobi win
Cozywheels
Baseline (please s a e):
The e is no o ganiza ion ha is cu en ly sha ing i s lee wi h
locals in he LL loca ions.
Al e na i e A:
We explo e he po en ial o companies in he LL loca ions o sha e
hei ehicles wi h locals ou side o business hou s.
Table 8: Baseline and al e na i es Cozywheels
Ca gobike
Baseline (please s a e):
The e is no p esence o sha ed ca go-bikes in he LL loca ions
Al e na i e A:
We se up ca go-bikes in p i a e loca ions (s a ion-based)
Al e na i e B:
We se up ca go-bikes in public loca ions (s a ion-based)
Al e na i e C:
We se up ee- loa ing ca go-bikes
Table 9: Baseline and al e na i es Ca gobike
6.2.4 B ussels imeline
The imeline o he in e en ions o he B ussels Li ing Lab is as ollows:
In e en ion name
Task
Scheduled ime ame
P ojec mon hs
Pa ne esponsible
Cozywheels
Ca ying ou in e iews
wi h po en ially
in e es ed local
businesses
No embe 2024-
Feb ua y 2025
11-14
Mpac
Mobi win
Se ice pilo
Oc obe – No embe
2025
21-22
Mpac
Ca gobike
Bike-sha ing pilo
Sep embe – Oc obe
2025
20-21
Mpac
Table 10: Li ing Lab imeline B ussels
34
6.3 Li ing Lab Budapes
6.3.1 Sho o e iew
The Budapes Li ing Lab aims o p o ide an e ec i e al e na i e o he eliance on p i a e ca usage and
low- equency public anspo in he Rákosmen e dis ic o Budapes . By encou aging mo e
sus ainable anspo modes, he li ing lab seeks o educe he eliance on single-occupancy
ehicles, he eby os e ing a g eene and mo e accessible u ban en i onmen . The li ing lab's
co e ocus is s eng hening connec ions wi hin he Rákosmen e dis ic . Enhancing hese connec ions
acili a es be e mo emen ac oss neighbou hoods and p omo es a sense o communi y among
esiden s. Wi h imp o ed accessibili y, esiden s a e mo e likely o engage wi h local se ices, boos ing
he local economy and encou aging a ib an neighbou hood a mosphe e.
6.3.2 Impac assessmen
6.3.2.1 In e en ions
MOL Bubi is Budapes 's communi y bike-sha ing sys em, which has only been a ailable in he ci y cen e
un il now. In he DREAMS pilo , we wan o es he se ice in an "island ope a ion" on he ou ski s o
Budapes ( he planned se ice a ea is no connec ed o he Budapes down own se ice a ea).
• Objec i es and Goals
(1) Tes bike sha ing scheme in subu ban ci cums ances
Obj.
Expec ed
impac
Indica o
Ou pu o
ou come
Ta ge
Measu emen
me hod
Measu emen
equency
Da a
collec ion
1
New use s o
he bike-
sha ing sys em
n . o new use s
Ou pu
50 new use s
n . o newly
egis e ed use s
Con inuous
BKK
1
In eg a ion o
he Mobi poin s
in o he u ban
space
n . o
mic omobili y ools
in Mobi poin s
Ou pu
2 ools / Mobi
poin s
pe sonal
obse a ion o
he s a us o he
ools
Ex-du an e
Rákosmen e,
BME
1
Awa eness-
aising on he
se ice in he
LL a ea
n . o local
esiden s eached
in any channels
Ou pu
500 local
esiden s
social media
pages and
g oups, local
media epo s
Con inuous
Rákosmen e
1
Enhanced
usage o bike-
sha ing in he
LL a ea
n . o ips wi h
MOL BuBi wi hin
he dis ic
Ou pu
100 ips
da a collec ion o
bike-sha ing
se ice p o ide
Con inuous
BKK
du a ion o ips
wi h MOL BuBi
wi hin he dis ic
Ou pu
5 min
(a e age)
da a collec ion o
bike-sha ing
se ice p o ide
Con inuous
BKK
u ilisa ion a e o
he MOL BuBi bikes
Ou pu
1 usage / day
da a collec ion o
bike-sha ing
se ice p o ide
Con inuous
BKK
bike a ailabili y
wi hin he dis ic
Ou come
1 bike / Mobi
poin
da a collec ion o
bike-sha ing
se ice p o ide
Con inuous
BKK
1
Financial
iabili y o he
se ice in he
LL a ea
o al cos pe
numbe o use s
Ou come
Cos b eak-
e en
n . o egis e ed
use s compa ed
o he o al cos o
he pilo and
calcula ed cos o
pe ip in o he
a eas
Ex-pos
Rákosmen e,
BME
Table 11: Budapes objec i es, indica o s and measu emen in o ma ion
35
6.3.3 S akeholde -based assessmen
P ima y s akeholde s + s akeholde g oups:
Name (o ganisa ion)
S akeholde g oup
BKK Cen e o Budapes
T anspo
Decision-make
KTI Hunga ian Ins i u e o
T anspo Science and
Logis ics
Ad iso y ole
Municipali y o Rákosmen e
Decision-make
Bike ide associa ion
Ad iso y ole
Ci izens
Ad iso y ole
Table 12: S akeholde s o e iew Budapes
S akeholde
Goals o he in e en ion(s)
BKK
Inc ease he modal sha e o sus ainable anspo modes
De elop and es he cu en sha ed mic omobili y sys em in an
ou ski dis ic o Budapes
KTI
P o ide be e accessibili y o local public anspo
Be e capaci y sha ing be ween public anspo and sus ainable
indi idual anspo modes in he pilo a ea
Rákosmen e
O e al e na i e anspo modes o ci izens
Inc ease he usage o local se ices
Bike ide associa ion
Dec ease he ca dependency o he pilo a ea
Change he anspo choices o he inhabi an s
Ci izens
Ha e access o al e na i e anspo modes
Possibili y o combine anspo modes and educe a el ime
Table 13: S akeholde s goals Budapes
Scena ios and al e na i es pe in e en ion:
Baseline (please s a e):
The e is no mic omobili y hub in as uc u e and bike-sha ing
se ice in Rákosmen e.
Al e na i e A:
Bike-sha ing se ice in Rákosmen e.
Al e na i e B:
Mobi mic omobili y poin s in Rákosmen e.
Table 14: Baseline and al e na i es Budapes in e en ion
36
6.3.4 Budapes imeline
Once p o ided, he imeline o he in e en ions o he Budapes Li ing Lab will be p esen ed he e.
In e en ion name
Task
Scheduled ime ame
P ojec mon hs
Pa ne esponsible
Table 15: Li ing Lab imeline Budapes
6.4 Li ing Lab Munich
6.4.1 Sho o e iew
Munich’s Li ing Lab cen e s on he neighbo ing ci ies o Ge e s ied and Wol a shausen in Uppe
Ba a ia, si ua ed app oxima ely 43 km and 38 km sou h o Munich, espec i ely. Ge e s ied, he la ge
and mo e ecen ly ounded o he wo, has a popula ion o app oxima ely 26,000 and was es ablished
a e Wo ld Wa II as a planned se lemen o displaced pe sons. I exhibi s a dispe sed u ban o m
cha ac e ized by pos -wa esiden ial de elopmen s and ligh indus ial zones. In con as ,
Wol a shausen, wi h a ound 19,000 inhabi an s, ea u es a compac his o ical cen e wi h medie al
s ee pa e ns posi ioned a he con luence o he Loisach and Isa i e s. Acco ding o he 2022 Ge man
Census, bo h ci ies exhibi ela i ely high p opo ions o olde adul esiden s—29.31% in Ge e s ied
and 28.64% in Wol a shausen—as well as no able sha es o mig an s, comp ising 19.23% and 16.54%
o he popula ion, espec i ely. The e o e, he Li ing Lab aims o de elop s a egies o educe
inequali ies in access o essen ial se ices wi hin 15-minu e neighbo hoods, ocusing on suppo ing
olde adul s and indi iduals wi h mig a ion backg ounds. Consequen ly, i will assess he po en ial o
eme ging mic o-mobili y hubs and ide-sha ing ini ia i es in collabo a ion wi h SIXT Sha e, E-Obe land,
and MVV. As pa o hese e o s, i en isions de eloping a ewa d p og am ha bene i s use s o local
public anspo and sha ed mobili y se ices, enhancing he engagemen and accessibili y o esiden s.
6.4.2 Impac assessmen
6.4.2.1 In e en ions
Wi hin Munich’s Li ing Lab, wo p ima y in e en ions a e en isioned o be es ed (i is s ill o be
de e mined i hey will be on-si e in es iga ions o heo e ical):
1. Mic o-Mobili y Poin s: o explo e he po en ial and easibili y o es ablishing local, decen alized
mobili y poin s wi h bus and bike/ca -sha ing o e s o se e esiden s wi hin walking and
biking dis ance.
2. Rewa ds p og am o public anspo and sha ed mobili y: o explo e he po en ial business o
implemen ing a poin -based sys em ha ewa ds use s o public anspo and sha ed mobili y
se ices. These poin s collec ed could be edeemed o discoun s on local goods o se ices, o
example.
37
1. Mic o-Mobili y Poin s
Objec i es:
As p e iously ou lined, he Mic o-Mobili y Poin s ini ia i e seeks o assess he po en ial and p ac ical
easibili y o es ablishing local-scale, decen alized mobili y hubs o e ing bike and ca -sha ing se ices
connec ed o local bus ou es. This in e en ion in es iga es sui able si e selec ion o hese hubs based
on demog aphic densi y and anspo needs, he modali ies o in eg a ion wi h exis ing public
anspo sys ems, and he necessa y suppo ing in as uc u e. The o e a ching objec i e is o educe
i s - and las -mile mobili y gaps and imp o e local accessibili y (pa icula ly o socially ulne able
g oups, such as olde adul s and mig an s, who o en ace compounded ba ie s due o limi ed digi al
li e acy, physical mobili y, and language skills). By in eg a ing he public anspo o e s wi h sha ed
mobili y se ices and suppo ing in as uc u e, his in e en ion aims o:
1. Iden i y sui able loca ions o he mic o-mobili y poin s based on demog aphic da a, cu en
in as uc u e, and public anspo o e s.
2. Examine in eg a ion models be ween sha ed mobili y se ices and he exis ing public
anspo ne wo k.
3. Assess usabili y and accessibili y o mic o mobili y poin s’ in e aces and in as uc u e o
olde adul s and mig an s.
4. E alua e communi y up ake and sa is ac ion among a ge use g oups, ocusing on equency
o use, ease o access, and pe cei ed bene i s.
5. Explo e he po en ial o eplicabili y and scalabili y.
The ollowing KPIs and measu emen me hods a e connec ed o he objec i es:
Obj.
Expec ed impac
Indica o
Ou pu o
ou come
Ta ge
Measu emen
me hod
Measu emen
equency
Da a collec ion
1, 3
Enhanced accessibili y
and co e age o mobili y
se ices o esiden s
% o he a ea
wi h imp o ed
accessibili y
Ou pu
A leas 20% o
he a ea had
i s accessibili y
imp o ed
GIS mapping and
spa ial
accessibili y
analysis
One- ime, o de ine
he sui able
loca ion o he
mobili y poin s
TUM
2
Inc ease o sha ed
mobili y op ions’
a ailabili y
Numbe o
a ailable sha ed
mobili y op ions
in eg a ed o
public anspo
Ou pu
A leas one
sha ed-
mobili y
se ice is
a ailable a he
mobili y poin
Coun ing o he
sha ed-mobili y
se ices
inco po a ed
One- ime, a e he
de ini ion o he
loca ion o he
mobili y poin s
TUM, wi h he
suppo o he
local pa ne s
2, 3,
4
Inc ease in he usage o
sha ed mobili y op ions
in i s /las -mile
connec i i y
Numbe o ides
by di e en
popula ion
g oups
Ou come
A leas 10
ides pe day
a e done wi h
sha ed
mobili y
se ices
Numbe o ides
Weekly, du ing he
in e en ion
pe iod
MVV, SIXT, and
E-Obe land
4
The communi y is
sa is ied wi h he mic o-
mobili y poin s and is
willing o keep using
hem in he long e m
Responden s’
sa is ac ion and
willingness o
con inue using
he se ices
Ou come
Mos
esponden s
indica ed
being sa is ied
and willing o
con inue using
he se ices
Quali a i e
me hod (e.g.,
su ey o
wo kshops wi h
ocus g oups)
One- ime, ex-pos
TUM, wi h he
suppo o he
local pa ne s
5
Deepe insigh in o he
a eas’ po en ial o
sha ed-mobili y business
models
Ope a ional
cos s and
e enues
Ou come
Cos b eak-
e en
Numbe o ips
and e enue +
ope a ion cos s
One- ime, ex-pos
MVV, SIXT, and
E-Obe land,
suppo ed by
TUM
Table 16: Mic o-mobili y poin s’ objec i es, indica o s, and measu emen in o ma ion.

38
2. Rewa ds p og am o public anspo and sha ed mobili y
Objec i es:
As p e iously ou lined, he ewa ds p og am o public anspo and sha ed mobili y seeks o assess
he easibili y and po en ial alue o implemen ing a poin -based incen i e sys em ha encou ages
sus ainable anspo modes. Unde his scheme, use s would accumula e poin s h ough egula use o
public anspo and sha ed mobili y se ices (e.g., bike-sha ing, ca -sha ing), which could hen be
edeemed o discoun s on local goods and se ices, ein o cing sus ainable a el beha io and suppo
o he local economy. The o e a ching objec i e is o encou age modal shi s away om p i a e ca use,
p omo e low-emission anspo al e na i es, and os e inclusi e u ban mobili y sys ems ha add ess
en i onmen al and social sus ainabili y goals. By implemen ing he ewa ds p og am, his in e en ion
aims o:
1. Assess he a ac i eness and use accep ance o a poin s-based ewa ds sys em o public
anspo and sha ed mobili y use s.
2. Measu e he impac o incen i es on a el beha io , pa icula ly ega ding modal shi s away
om p i a e ca use owa d sus ainable op ions.
3. E alua e he social inclusi eness o he ewa ds scheme, wi h a ocus on pa icipa ion by olde
adul s, mig an s, and indi iduals wi h limi ed digi al skills.
The ollowing KPIs and measu emen me hods a e connec ed o he objec i es:
Obj.
Expec ed impac
Indica o
Ou pu o
ou come
Ta ge
Measu emen
me hod
Measu emen
equency
Da a
collec ion
1
Use engagemen
and sa is ac ion
wi h he ewa ds
sys em
- % o use s
en olled who
ac i ely use
and edeem
poin s
- Sa is ac ion
and
willingness o
con inue
using he
se ices
Ou come
The e a e a
leas 50 ac i e
use s in he
i s 3 mon hs
- Sys em usage da a
(e.g., logins and
ewa d claims)
- Small su eys o
assess sa is ac ion
le els
One- ime, ex-pos
Municipali ies
o Ge e s ied
and
Wol a shause
n
2
Inc eased use o
public anspo and
sha ed mobili y in
place o p i a e
ehicles
% inc ease in
public/sha ed
mobili y
anspo use
Ou come
20% inc ease
in
public/sha ed
mobili y
anspo use
Numbe o ides
Weekly, du ing he
in e en ion
pe iod
MVV, SIXT,
and E-
Obe land
3
Inc eased
in ol emen o
mig an s and olde
adul s
% o mig an s
and olde
adul s using
he ewa ds
p og am
Ou come
A leas 20% o
egis e ed
use s a e
mig an s o
olde adul s
Demog aphic da a
om egis a ion
p ocess o he
ewa ds p og am
Weekly, du ing he
in e en ion
pe iod
Local pa ne s,
suppo ed by
TUM
Table 17: Rewa ds p og am o public anspo and sha ed mobili y’s objec i es, indica o s and
measu emen in o ma ion.
6.4.3 S akeholde -based assessmen
P ima y s akeholde s + s akeholde g oups:
Name (o ganiza ion)
S akeholde g oup
Ci y o Wol a shausen
Ad iso y ole
39
Ci y o Ge e s ied
Ad iso y ole
MVV (public anspo
ope a o )
P ojec suppo ing
SIXT-Sha e (sha ed-mobili y:
ca s)
P ojec suppo ing
E-Obe land (sha ed-mobili y:
ca s)
P ojec suppo ing
Table 18: S akeholde s’ o e iew Munich.
In he ollowing able, hypo he ical goals (no ye con i med wi h he s akeholde ) ha e been ma ked in
i alics.
S akeholde
Goals o he in e en ion(s)
Ci y o Wol a shausen
P o ide eedback
Sha e da a when app op ia e
P o ide suppo ing ma e ial
Pa icipa e in he wo kshops
Mobili y o he u u e ha combines inclusion, sus ainabili y, and
pa icipa ion
Imp o ing and simpli ying accessibili y and mobili y
Sus ainable u ban de elopmen
Swi ching o public anspo and sha ed mobili y o e s
Public accep ance and e ec i e in o ma ion dissemina ion
Ci y o Ge e s ied
P o ide eedback
Sha e da a when app op ia e
P o ide suppo ing ma e ial
Pa icipa e in he wo kshops
P omo e mobili y o all, including pe sons wi h educed mobili y,
language ba ie s, and educa ional impai men s
S eng hening ac i e o ms o mobili y
Reduce p i a e ca usage
Reduce pa king spaces
Ac ions/in e en ions should ha e high public accep ance
B ing employe s on boa d o inance be e and sus ainable
commu ing choices (ins ead o he use o p i a e ca s by hei
employees)
MVV
P o ide eedback
Sha e da a when app op ia e
P o ide suppo ing ma e ial
Pa icipa e in he wo kshops
Imp o e i s and las -mile connec ion
Tes ing new business models o sha ed mobili y ha can be olled
ou in o he simila ly s uc u ed a eas in he MVV a ea
Reduc ion in a el ime h ough new sha ed mobili y o e s
Enabling mo e people o choose al e na i es o p i a e ca usage
SIXT-Sha e
P o ide eedback
Sha e da a when app op ia e
40
P o ide suppo ing ma e ial
Pa icipa e in he wo kshops
E-Obe land
P o ide eedback
Sha e da a when app op ia e
P o ide suppo ing ma e ial
Pa icipa e in he wo kshops
Le e aging po en ial in all business a eas in he c oss-ne wo k
C ea ing a sensible, cos -e ec i e al e na i e o a p i a e second
ehicle
Reducing company ca lee s in small o medium-sized companies
h ough eliable ca -sha ing
Inc ease use a e and p o i abili y
Table 19: S akeholde s’ goals Munich.
Scena ios and al e na i es pe in e en ion:
1. Mic o-Mobili y Poin s in Wol a shausen:
Baseline (please s a e):
One ain s a ion in Wol a shausen (S7) connec s o Munich, and
13 egional and 2 exp ess bus ou es connec wi hin he ci y and
he egion (buses unning e e y 20 minu es). The ain s a ion
con ains 482 bike pa king spaces.
Al e na i e A:
Bike sha ing is pa o he mobili y hub a Wo a shausen ain s a ion.
Al e na i e B:
Ca sha ing is pa o he mobili y hub a Wo a shausen ain s a ion.
Al e na i e C:
Bike and ca sha ing a e pa o he mobili y hub a Wo a shausen ain
s a ion.
Al e na i e D:
Bike sha ing is in eg a ed along he exp ess bus s ops in
Wo a shausen.
Al e na i e E:
Ca sha ing is in eg a ed along he exp ess bus s ops in Wo a shausen.
Al e na i e F:
Bike and ca sha ing a e in eg a ed along he exp ess bus s ops in
Wo a shausen.
Table 20: Baseline and al e na i es o mic o-mobili y poin s in Wol a shausen.
2. Mic o-Mobili y Poin s in Ge e s ied:
Baseline (please s a e):
The e a e 8 egional and 1 exp ess bus ou es connec ing he ci y
and he egion (buses unning e e y 20 minu es du ing
weekdays). The e a e also 122 bike pa king spaces dis ibu ed
h oughou he u ban o m.
Al e na i e A:
Bike sha ing is in eg a ed along he exp ess bus s ops in Ge e s ied.
Al e na i e B:
Ca sha ing is in eg a ed along he exp ess bus s ops in Ge e s ied.
Al e na i e C:
Bike and ca sha ing a e in eg a ed along he exp ess bus s ops in
Ge e s ied.
Table 21: Baseline and al e na i es o mic o-mobili y poin s in Ge e s ied.
41
c. Rewa ds p og am o public anspo and sha ed mobili y:
Baseline (please s a e):
No mobili y ewa ds p og ams a e unning in Ge e s ied and
Wol a shausen. Ope a ing nex yea : My-Radl (i you use public
anspo , you can ide MVV sha ed bikes o ee)
Al e na i e A:
I you walk XX kilome e s, you ge an incen i e (TBD).
Al e na i e B:
I you ide XX kilome e s by bike, you ge an incen i e (TBD).
Al e na i e C:
I you ha e XX ca -sha ing ides, you ge an incen i e.
Table 22: Baseline and al e na i es o he ewa ds p og am o public anspo and sha ed mobili y .
6.4.4 Munich imeline
Once p o ided, he imeline o he in e en ions o he Munich Li ing Lab will be p esen ed he e.
In e en ion name
Task
Scheduled ime ame
P ojec mon hs
Pa ne esponsible
Table 23: Li ing Lab imeline Munich
6.5 Li ing Lab Pa is
6.5.1 Sho o e iew
The p ima y aim o he Pa is Li ing Lab is o s udy how 15-min accessibili y wi hin he T am 12
co ido could be imp o ed, h ough he implemen a ion o inno a i e mobili y solu ions. This
in ol es add essing las -mile connec i i y gaps by deploying new sha ed mobili y s a ions a
s a egic loca ions nea key T12 s a ions. These s a ions will in eg a e bikes and scoo e s. The Li ing
Lab also aims o imp o e way inding and use expe ience by upg ading signage a majo s a ions a
É y-Cou cou onnes. To analyse he adop ion dynamics o sha ed mobili y se ices, he p ojec will
in oduce discoun ed membe ships and ee- ial o e s. Discoun s mainly a ge s uden s, while
ee- ial p og ams will p o ide use s wi h hei i s ides ee o cha ge. These measu es aim o
educe cos ba ie s and p omo e sus ained adop ion o sha ed mobili y op ions. By le e aging he
exis ing cycling in as uc u e, he Li ing Lab will u he encou age ac i e mobili y, educing
eliance on p i a e ehicles and con ibu ing o en i onmen al sus ainabili y. The Li ing Lab also
seeks o os e collabo a ion among s akeholde s o ensu e he success ul implemen a ion and
scalabili y o i s in e en ions. Key pa ne s include Pony as he sha ed mobili y p o ide , he
municipali y o É y-Cou cou onnes, he Essonne Depa men , Ile-de-F ance Mobili és (PT
au ho i y), and communi y o ganisa ions.
48
1
New use s o he
bike-sha ing
sys em
Numbe o
new use s
Ou pu
Inc ease he
up ake o e-bikes
by 10% o he
wo ke s
commu ing by
p i a e ca s in six
mon hs.
DOTT app
(quick ques ion
be o e wo ke
s a s ip)
Companies
dissemina e
small su ey
Once a e six
mon hs
UT and HU
Table 31: Discoun s o sha ed bikes objec i es, indica o s and measu emen in o ma ion
2. Design and implemen a ion op ions o a pilo sola cha ging sha ed e-bike s a ion
• Sho Desc ip ion: design a pilo o -g id sola cha ging bike s a ion ha will help educe
he cos o DOTT bikes o be dis ibu ed as he company will sa e logis ics cos s (less
ba e y swapping asks o be conduc ed).
• P ima y objec i es o he in e en ion:
1. dec ease cos o mobili y p o ide s, leading o dec easing he cos o
use s and hus, inc easing he up ake o sha ed bikes because hey a e
o e ed a cheape p ices due o educed logis ics cos s.
2. Reducing ene gy dependence o he mobili y p o ide .
Obj.
Expec ed impac
Indica o
Ou pu o
ou come?
Ta ge
Measu emen
me hod
Measu emen
equency
Da a
collec ion
1
Reduc ion o
ba e y swapping
asks
Numbe o asks
educed
Ou pu
Reduce
logis ical cos
by 20%
In e iew
DOTT
Once six mon hs
a e in e en ion
UT and HU
2
Reduc ion in g id
ene gy
dependence.
Eu os sa ed in
ene gy cos
Ou pu
Reduce
ene gy
consump ion
by 5%
Da a om
ene gy
company
Once six mon hs
a e in e en ion
UT and HU
Table 32: Sola s a ion objec i es, indica o s and measu emen in o ma ion
6.6.3 S akeholde -based assessmen
P ima y s akeholde s + s akeholde g oups:
Name (o ganisa ion)
S akeholde g oup
Do
Decision-make
U ech Municipali y
Decision-make
Fie se bond
Local s akeholde
Communi y cen e
Local esiden s/ employees o companies
P ojec O
NGO and owne o he loca ion o sola cha ging s a ion
Companies
Owne s o he companies
Table 33: S akeholde s o e iew U ech
S akeholde
Goals o he in e en ion(s)
Do
Gain he mobili y p o ide ende by educing he cos in he
ou ski s and being a sus ainable se ice.
U ech Municipali y
Dec ease mobili y po e y
Fie se bond
Make cycling an inclusi e op ion o anspo
Communi y cen e
Inc ease accessibili y o di e en se ices
P ojec O
Imp o e oppo uni ies o esiden s in he neighbou hood

49
Companies
Inc ease heal hy wellbeing o wo ke s and educe pa king space
cos s.
Table 34: S akeholde goals U ech
Scena ios and al e na i es pe in e en ion:
Baseline:
Cu en numbe o wo ke s ha commu e by p i a e ca
In e en ion #1
Al e na i e A:
20% discoun o DOTT sha ed e bikes o wo ke s commu ing
ips
In e en ion #1
Al e na i e B:
30% discoun o DOTT sha ed e bikes o wo ke s commu ing
ips
In e en ion #1
Al e na i e C:
F ee DOTT sha ed e bikes o wo ke s commu ing ips
Baseline:
The e is no o -g id sola cha ging sha ed e-bike s a ion o
knowledge abou i
In e en ion #2
Al e na i e A:
Gene a e he knowledge abou he possible implemen a ion o he
sola cha ging s a ion.
In e en ion #2
Al e na i e B:
Ob ain a easible design and showcase i o he municipali y o aise
awa eness o his solu ion as a iable op ion.
In e en ion #2
al e na i e C:
Implemen he sola cha ging s a ion.
Table 35: Baseline and al e na i es pe in e en ion
6.6.4 U ech imeline
The imeline o he in e en ions o he U ech Li ing Lab is as ollows:
50
In e en ion name
Task
Scheduled ime ame
P ojec mon hs
Pa ne esponsible
Sola cha ging docking
sys em o Do ebikes
De elopmen & design o
a sola cha ging docking
sys em o Do ebikes
Feb ua y – July 2025
14-19
HU is leading, al hough
TU is s ill he o mal
lead so esponsible o
inal esul s o he
deli e able
Building & pilo ing he
sola cha ging docking
sys em
Sep embe 2025 – July
2026
21-31
idem
Reduc ion on ip p ice
o employees o
companies
In e iews wi h
companies in O e ech
– o iden i y needs and
desi es
May – July 2025
17-19
idem
One mon h campaign
‘E e yone in O e ech
Cycles o wo k’
Sep embe 2025
21
idem
Con inua ion o educed
ees o companies wi h
ha in e es
Oc obe – Ap il 2026
22-28
idem
Table 36: Li ing Lab imeline U ech
6.7 Li ing Lab Vienna
6.7.1 Sho o e iew
The case s udy a ea o he Vienna Li ing Lab is he Wiene Flu and i s su ounding neighbou hood,
si ua ed in he 23 d Dis ic known as Liesing. Liesing is loca ed in he sou hwes o Vienna and is he
i h la ges dis ic in e ms o a ea, co e ing 32.29 km2. The 23 d Dis ic has a ela i ely high a e age
age, which is s eadily inc easing, and compa ed o he ci y as a whole, i has lowe educa ional le els bu
a highe a e age income (S ad Wien -Liesing in Zahlen). The Vienna Li ing Lab in es iga es how a
lexible ac i i y hub can con ibu e o he 15-minu e ci y concep and how he de elopmen o his
lexible ac i i y hub can be linked o mobili y se ices like bike sha ing and demand esponsi e
anspo .
6.7.2 Impac assessmen
6.7.2.1 In e en ions
In he Vienna LL, he e will be wo in e en ions es ed.:
1. Flexible ac i i y hub: To ans o m unde u ilized spaces, we plan a lexible ac i i y hub
h ough a co-c ea i e app oach. By eac i a ing open a eas in Wiene Flu , hese spaces can
se e as dynamic hubs o (communi y) e en s, cul u al o e s, g oce ies. A co-c ea i e se up
encou ages communi y inpu in designing and p og amming he space, ensu ing i mee s local
needs and os e s engagemen .
51
2. Bike Sha ing S a ion: To enhance accessibili y, a ligh bike sha ing s a ion will be es ablished
nea he lexible ac i i y hub. This s a ion will p o ide a designa ed a ea o bike sha ing,
accessible h ough he WienMobil App, elimina ing he need o physical docking in as uc u e.
By posi ioning he s a ion close o he lexible ac i i y hub, we can acili a e easy bike pick-up
and d op-o , p omo ing sus ainable u ban anspo a ion op ions.
The e is also a demand esponsi e anspo (DRT) a ailable in he LL a ea. WienMobil Hüp e o e s
a demand- esponsi e bus se ice. I will be de e mined i he use da a can be used o e alua e i he
lexible ac i i y hub has an impac on i s ope a ion. The in oduc ion o a lexible ac i i y hub in his a ea
could u he enhance he on-demand bus’s e ec i eness.
1. Flexible ac i i y hub
Wi h he in e en ion “ lexible ac i i y hub” we aim o:
1. Se up a lexible ac i i y hub wi h di e en o e s (e.g. open-ai cinema, hea e, wo kshops)
( ime span mid-June un il mid-Augus 2025)
2. In i e esiden s and local ini ia i es o ge ac i ely in ol ed in he se -up o lexible ac i i y
hub.
3. C ea e ideas/ concep s o ac i a ing acan / unde u ilised spaces ha in ol e local ac o s and
s akeholde s.
4. Assess he impac o lexible ac i i y hubs on mobili y pa e ns and s a is ac ion le el in he
neighbou hood.
5. Discuss and explo e business models o sus ainable space use ha can con inue o exis a e
he esea ch p ojec s ha e been comple ed.
Obj.
Expec ed
impac
Indica o
Ou pu
o
ou come
Ta ge
Measu emen
me hod
Measu emen
equency
Da a
collec ion
1
Imp o ed
access o
e en s and
o e s
Visi o s
du ing
cul u al
e en s
(cinema &
hea e )
Ou pu
100
isi o s pe
e en
Manual isi o
coun ing
Ex-du an e
TU Wien/
BOKU/
S ad land
2
Imp o ed
in ol emen
and
ne wo king o
local ac o s
In ol ed
o ganisa ion
s/ ini ia i es
in he
p epa a ions
o lexible
ac i i y hub
Ou pu
10
o ganisa io
ns/
inia i es
in ol ed
Manual coun ing/
quali a i e
assump ion
One ime, ex-pos
TU Wien/
BOKU/
S ad land
1
Imp o ed
o e s in he
LL a ea
Visi o s a
he lexible
ac i i y hub
(e.g. du ing
wo kshops)
Ou pu
A leas 10
isi o s on
days o
ac i i y
Manual isi o
coun ing
Ex-du an e
TU Wien/
BOKU/
S ad land
4
Imp o ed
quali y o
e en s and
o e s in LL
a ea
Repo ed
eedback on
quali y new
o e s a
lexible
Ou come
High
sa is ac io
n a e
( a ing 4
ou o 5)
In e iews o
eedback o ms
Ex-du an e. ex
pos
TU Wien/
BOKU/
S ad land
52
ac i i y hub
1, 3
Imp o ed
numbe o
o e s in he
LL a ea
Numbe o
ac i i ies and
e en s
hos ed a he
hub
Ou pu
2 e en s/
o e s pe
week (= 24
in o al)
Manual coun
Ex-du an e, ex-
pos
TU Wien/
BOKU/
S ad land
1, 4
Imp o ed
access o
e en s and
o e s
P oximi y o
inhabi an s
Ou come
Dis ance o
cul u al
o e s
educed?
GIS analysis,
isoch one
Ex-pos
TU Wien/
BOKU (wi h
suppo by
TUM)
2?
Sus ainable
a el mode
o he hub
T a el mode
Ou come
80% o
is o s
come by
oo o bike
In e iews o
eedback o ms
Ex-du an e
TU Wien/
BOKU/
S ad land
Tbd.
Imp o ed
usage o DRT
in he LL a ea
Change in
DRT use/
numbe s o
ips booked
ou pu
Da a om he DRT
p o ide /
discussion
Ex-pos
TU Wien/
BOKU/
S ad land
Table 37: Flexible ac i i y hub objec i es, indica o s and measu emen in o ma ion
2. Bike Sha ing S a ion
Wi h he in e en ion “Bike Sha ing S a ion” we aim o:
1. Unde s and local demand o decen al bike sha ing s a ions
2. Collec cus ome eedback o assess he usabili y
3. Explo ing he po en ial o new bike-sha ing s a ions’ in educing ca dependency and CO2
emissions.
Obj.
Expec ed impac
Indica o
Ou pu
o
ou come
Ta ge
Measu emen
me hod
Measu emen
equency
Da a
collec ion
1
Inc ease o bike sha ing
usage in he LL a ea
Numbe o
bike d op-
o s and pick-
ups a new
bike sha ing
s a ion
Ou pu
5 d op-o s
du ing
e en s
Da a om he
bike-sha ing
p o ide
Ex-du an e, ex-pos
TU Wien/
BOKU
1
Inc ease o bike sha ing
usage in he LL a ea
Numbe o
ides;
Dis ance
a elled
( bd) (p oxy:
pick-up and
d op-o
s a ions)
Ou come
Inc ease in
numbe o
ides du ing
he pilo by
25%; 50% o
d op o s
we e ips
wi hin he
dis ic
Da a om he
bike-sha e
p o ide ;
in e iew
Ex-du an e, ex-pos
TU Wien/
BOKU
2
Be e unde s anding
o he need o and
quali y o new bike
sha ing s a ion
Sa is ac ion
wi h new
s a ion
Ou come
High
sa is ac ion
a e (4/5)
In e iews o
eedback o ms
Ex-du an e, ex-pos
TU Wien/
BOKU
3
Sho e dis ance
a elled o e en o
o e s
T a el ime/
a el
dis ance
Ou come
Dec ease in
dis ance by
50%
In e iews o
eedback o ms
(p oxy: usual
isi ed places o
Ex-du an e, ex-pos
TU Wien/
BOKU
53
cinema, hea e
e c.)
3
Reduced eliance on
p i a e ehicles
Reduc ion in
ca bon
oo p in
h ough bike
usage/
walking
Ou come
?
In e iews o
eedback o ms
(p oxy: usual
mode o o isi
cul u al si es e c.)
Ex-du an e, ex-pos
TU Wien/
BOKU
Table 38: Bike sha ing s a ion objec i es, indica o s and measu emen in o ma ion
6.7.3 S akeholde -based assessmen
Name (o ganisa ion)
S akeholde g oup
S a d land/ Lokale Agenda
Neighbou hood ini ia i e
Mo genjungs/ imG ä zl
Social business
Table 39: S akeholde s o e iew Vienna
S akeholde
Goals o he in e en ion(s)
S a d land/ Lokale Agenda
Fos e pa icipa ion o local inhabi an s
Imp o e access o (ou doo ) space in he neighbou hood
C ea e (cul u al) o e s and ac i i ies
Mo genjungs/ imG ä zl
C ea e isibili y o acan space
P omo e local and coope a i e (economic) ac i i y in he
neighbou hood
Table 40: S akeholde goals Vienna
Flexible hub
Baseline (please s a e):
The e is usually no use o he public space (in e ms o cul u al
e en s and simila o e s) a he LL loca ion.
Al e na i e A:
We se up a lexible ac i i y hub wi h cul u al o e s
Al e na i e B:
We se up a lexible ac i i y hub wi h cul u al o e s and g oce ies/

54
ood- ela ed o e s
Table 41: Baseline and al e na i es lexible hub
Bike sha ing s a ion
Baseline (please s a e):
The e is no bike-sha ing s a ion a he LL loca ion.
Al e na i e A:
We se up one bike sha ing s a ion in he LL a ea
Al e na i e B:
We se up wo bike sha ing s a ions in he LL a ea
Table 42: Baseline and al e na i es bike sha ing s a ion
6.7.4 Vienna imeline
Once p o ided, he imeline o he in e en ions o he Vienna Li ing Lab will be p esen ed he e.
In e en ion name
Task
Scheduled ime ame
P ojec mon hs
Pa ne esponsible
Table 43: Li ing Lab imeline Vienna
7 CONCLUSION AND NEXT STEPS
While he 15-minu e ci y concep is becoming inc easingly well-known and s udied in anspo a ion
esea ch, i s applica ion and iabili y in u ban ou ski s has ecei ed less a en ion so a . The DREAMS-
p ojec aims o s udy 15-minu e ci ies in his con ex . This deli e able p o ides an o e iew o he Key
Pe o mance Indica o s o he p ojec , di ided pe Li ing Lab loca ion (loca ed in Aus ia, Belgium,
F ance, Ge many, Hunga y and he Ne he lands). Pe loca ion, he deli e able gi es an o e iew o he
in e en ions planned, hei expec ed impac s and a ached indica o s. I also p o ides a i s da a
collec ion amewo k and imeline pe loca ion, and o he p ojec as a whole. As he na u e o he
in e en ions a ies pe loca ion, he indica o selec ion was done using a bo om-up app oach, by
asking each Li ing Lab leade and ele an s akeholde s o e lec on wha hei speci ic in e en ion(s)
would need. A la ge , o e a ching se o KPIs o he en i e p ojec , ha will ake in o he opics o
55
Accessibili y, Ca bon Emissions, Li eabili y, Heal h, Economic Impac , and Equi y will be de eloped in
Wo k Package 3, as pa o Task 3.5 and Deli e able 3.2 ( o hcoming), o which a i s e sion has been
included in his Deli e able. The KPIs de ined in his cu en deli e able will be implemen ed and es ed
in he ollowing yea s in he six Li ing Labs as pa o Wo k Package 5 o he p ojec . Addi ionally, he
Deli e able also includes an explana ion o he o hcoming Impac Assessmen o Task 6.2. I also
includes an o e iew o he local s akeholde s, hei objec i es, and he scena ios and al e na i es o
each in e en ion and LL. As nex s eps, he e will be he con inua ion o he bi-mon hly mee ings o
ensu e p ope da a collec ion, as well as con inuing T6.2 in he coming mon hs. Whe e T6.1 only en ailed
he se up o he DREAMS Impac Assessmen F amewo k, T6.2 will also allow o a c oss-LL compa ison
h ough he SIS analyses ha will be pe o med in 2025-2026. S a ing in he la e hal o 2025, he
i s s eps in he p ocess e alua ion will be conduc ed o examine how in e en ions a e being
implemen ed ac oss he six Li ing Labs, as pa o Task 6.3. This e alua ion will ocus on iden i ying
enable s and ba ie s o implemen a ion, unde s anding con ex ual di e ences, and assessing he
eplicabili y o in e en ions in di e en u ban ou ski s. Da a will be collec ed h ough in e iews,
su eys, and obse a ional me hods, ensu ing a obus analysis o he Li ing Lab dynamics.
8 ACKNOWLEDGEMENTS
Wi h hanks o he e iewe s:
Roman Klemen schi z (BOKU)
Geo gia Cha alampidou (BOKU)
Yusak Susilo (BOKU)
Hey hem Adje oud (UGE)
Alain L’Hos is (UGE)
We g a e ully acknowledge he B ussels-Capi al Region - Inno i is (B ussels Public O ganisa ion o
Resea ch and Inno a ion) o inancial suppo unde g an numbe ‘RBC/2023-EU-DUT-11’.
9 REFERENCES
Allam, Z., & Newman, P. (2022). Rede ining he sma ci y: Cul u e, me abolism and go e nance.
Sp inge .
Bje ke, M., & Renge , R. (2017). Being sma abou w i ing SMART objec i es.. E alua ion and p og am
planning, 61, 125-127 . h ps://doi.o g/10.1016/j.e alp ogplan.2016.12.009
C40 Ci ies. (2022). How o build back be e wi h a 15-minu e ci y.
h ps://www.c40knowledgehub.o g/s/a icle/How- o-build-back-be e -wi h-a-15-minu e-ci y
Chakh ou a, C., & Pojani, D. (2015). Indica o -based E alua ion o Sus ainable T anspo Plans: a
amewo k o Pa is and o he la ge ci ies. T anspo Policy, 50, 15–28.
h ps://doi.o g/10.1016/j. anpol.2016.05.014
Chia adia, F., Lelo, K., Monni, S., & Tomassi, F. (2024). The 15-Minu e Ci y: An A emp o Measu e
P oximi y o U ban Se ices in Rome. Sus ainabili y, 16(21), 9432.
h ps://doi.o g/10.3390/su16219432
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Gillis, D., Semanjski, I., & Lauwe s, D. (2015). How o Moni o Sus ainable Mobili y in Ci ies? Li e a u e
Re iew in he F ame o C ea ing a Se o Sus ainable Mobili y Indica o s. Sus ainabili y, 8(1), 29.
h ps://doi.o g/10.3390/su8010029
Gudmundsson, H. (2004). Sus ainable anspo and pe o mance indica o s. In The Royal Socie y o
Chemis y eBooks (pp. 35–64). h ps://doi.o g/10.1039/9781847552211-00035
Hyllenius, P., Rosq is q, P. S., Haus ein, S., Welsch, J., Ca eno, M., & Rye, T. (2009). MaxSumo - Guidance
on how o plan, moni o and e alua e mobili y p ojec s: In eg a ed p ojec : 6.2 Sus ainable
De elopmen , 1.6.2 Sus ainable Su ace T anspo Objec i e, 3.1.1.1.3 Ad ancing Knowledge on
inno a i e measu es in u ban anspo .
Kese u, I., Bulckaen, J., & Macha is, C. (2016). Sus ainable, Pa icipa o y and P ac ical: The NISTO
E alua ion F amewo k o U ban and Regional Mobili y P ojec s. T anspo a ion Resea ch P ocedia, 13,
134–144. h ps://doi.o g/10.1016/j. p o.2016.05.014
Linnan, L., & S eckle , A. (2002). P ocess e alua ion o public heal h in e en ions and esea ch. Jossey-
Bass.
Moo e, G. F., Aud ey, S., Ba ke , M., Bond, L., Bonell, C., Ha deman, W., … Bai d, J. (2015). P ocess
e alua ion o complex in e en ions: Medical Resea ch Council guidance. BMJ, 350, h1258.
h ps://doi.o g/10.1136/bmj.h1258
Mo eno, C., Allam, Z., Chabaud, D., Gall, C., & P a long, F. (2021). In oducing he "15-minu e ci y":
Sus ainabili y, esilience and place iden i y in u u e pos -pandemic ci ies. Sma Ci ies, 4(1), 93-111.
h ps://doi.o g/10.3390/sma ci ies4010006
Pozoukidou, G., & Cha ziyiannaki, Z. (2021). 15-minu e ci y: Decomposing he new u ban planning
eu opia. Sus ainabili y, 13(2), 928. h ps://doi.o g/10.3390/su13020928
Saunde s, R. P., E ans, M. H., & Joshi, P. (2005). De eloping a p ocess-e alua ion plan o assessing heal h
p omo ion p og am implemen a ion: A how- o guide. Heal h P omo ion P ac ice, 6(2), 134–147.
h ps://doi.o g/10.1177/1524839904273387
e Bo eld , G., Kese u, I., & Macha is, C. (2022). When mone a isa ion and anking a e no app op ia e.
A no el s akeholde -based app aisal me hod. T anspo a ion Resea ch Pa A: Policy and P ac ice, 156,
192– 205. h ps://doi.o g/10.1016/j. a.2021.12.004
Zhang, S., Zhen, F., Kong, Y., Lobsang, T., & Zou, S. (2022). Towa ds a 15-minu e ci y: A ne wo k-based
e alua ion amewo k. En i onmen and Planning B: U ban Analy ics and Ci y Science, 50(2), 357–375.
DOI/10.1177/23998083221118570
10 APPENDICES
10.1 Appendix I. Templa e o LL leade s
Task 6.1: Li ing Lab objec i es and KPIs empla e o LL leade s
1. Gene al In o ma ion
• Li ing Lab: (Budapes , B ussels, Munich, Pa is, U ech , Vienna
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• In e en ion ID/Name: (Unique name o code o he in e en ion, i.e. ‘Nede -O e -Heembeek Mo-
biTwin pilo , o iden i y he sepa a e in e en ions pe LL. I can also be he add ess.Wha e e you
hink wo ks he bes , bu no o ‘Pa is A, Pa is B’ e c as his is oo gene al.)
• Sho Desc ip ion: (B ie ly desc ibe he in e en ion)
• P ima y objec i es o he in e en ion:
2. Local Con ex and Objec i es
Please iden i y he p ojec al e na i es o op ions you a e awa e o .
Lis all possible op ions o he p ojec o indica e i only one op ion exis s. These may
include di e en designs, loca ions, policies, o app oaches.
This can o example be:
Al e na i e A: sha ed bikes a e placed in a cen al loca ion.
Al e na i e B: sha ed bikes and ca go-bikes a e placed in a cen al loca ion.
Al e na i e C: sha ed bikes a e placed in a cen al loca ion and h oughou he
neighbou hood.
Al e na i es can also be less simila o each o he :
Al e na i e D: sha ed ca s a e placed in a cen al loca ion
Al e na i e E: we hos a ca é o neighbou s.
These a e always connec ed o a baseline: he si ua ion wi hou any in e en ion.
Please ill ou any al e na i e pe baseline scena io. I you a e in ol ed in mul iple
in e en ions, you can copy + pas e he able pe in e en ion.
Baseline (please s a e):
Al e na i e A:
Al e na i e B:
E c.
3. Impac s, KPIs and measu emen s
• Baseline da a collec ion: (Explain wha ype o baseline da a is necessa y, wha i will be abou ,
and how i will be collec ed)
• Expec ed Impac s: (Lis 4 o 5 speci ic impac s, e.g., imp o ed ai quali y, inc eased walkabili y, eco-
nomic g ow h)
Then ill ou he es pe expec ed impac s in he able below:
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10.4 Appendix IV. Pos e empla es Vienna – pic u es o he wo kshop session
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He e you en e he weigh s ha indica e he impo ance o each ac o o each s akeholde . This is
usually based on inpu om he s akeholde s hemsel es. Assign a sco e be ween 10 (maximum
impo ance) and 0 (no impo an ). A common app oach is o s a by iden i ying he mos impo an
ac o and hen a ing he o he ac o s ela i e o ha one. I is possible o mul iple ac o s o ha e he
same weigh . I is also possible ha no ac o ecei es he maximum weigh .
Depending on whe he you selec ed “Yes” o “No” unde “Use indi idual ep esen a i es o s akeholde
g oups?” ( ab 1 ‘S a ’), you will assign weigh s ei he o he s akeholde g oup as a whole o o each
indi idual ep esen a i e o he g oup.
Tab: Compa e Resul s
Based on you inpu , his ab displays wo g aphs o compa ing he op ions:
To al ela i e impac sco e, b eakdown pe s akeholde : This shows he ex en o which s akeholde s
a e posi i ely o nega i ely a ec ed by each op ion.
To al ela i e impac sco e, b eakdown pe ac o : This shows he ex en o which each ac o
con ibu es posi i ely o nega i ely o he o al e ec .
In bo h g aphs, 100% ep esen s he maximum possible (posi i e o nega i e) e ec an op ion could
ha e ac oss all ac o s and all s akeholde s. The layou o he cha s can be cus omised. Fo cla i y, i is
ad isable o use one consis en colou pe s akeholde , ega dless o whe he he impac is posi i e o
nega i e.
Tabs: Resul s Op ion 1, 2, 3, …

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Each o hese abs p o ides a mo e de ailed analysis o he indi idual op ions (in e en ions) using wo
g aphs ha show how a speci ic in e en ion could be adjus ed o add ess he needs o conce ns o
s akeholde s:
Absolu e impac pe s akeholde : This shows he impac o he op ion on each ac o and displays he
s akeholde s o whom he impac is ele an . S akeholde s a e shown on he ho izon al axis. On he
e ical axis, a sco e o 1 co esponds o he maximum (posi i e o nega i e) impac o one s akeholde
on one ac o . The e o e, he mo e ele an ac o s he e a e pe s akeholde , he highe he po en ial
impac sco e.
Rela i e impac pe ac o : This shows he impac o he op ion on each ac o and he s akeholde s o
whom ha impac is ele an . 100% ep esen s he maximum possible impac pe ac o .
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SIS so wa e
S a
Go o www.c ispa-sis.eu. A e signing up, choose he op ion ‘SIS’ a he in o sc een.
In he nex sc een (My p ojec s), choose ‘+ Add new p ojec ’
Gi e you p ojec a name, goal (op ional) and choose an e alua ion op ion, i.e., he g anula i y o he
scale o he pe o mance a ing (s ep 4).
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You hen a i e in he ac ual SIS p ocess. The abs and sub abs ep esen he di e en s eps o SIS.
Tab: Basics
Op ions: En e he names o he op ions (in e en ions). Only en e he op ions ha a e no business-
as-usual scena ios (minimum 1). Unlike in mul i-c i e ia analysis, SIS esul s a e s ill meaning ul e en i
you ha e only one op ion.
S akeholde g oups: En e he names o he s akeholde g oups and hei membe s. I you only ha e
s akeholde s ha a e no g oups wi h membe s, lea e he ‘membe name’ box blank. By en e ing he
email add esses, you enable hem o p o ide hei inpu om hei own compu e .
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Impac Fac o s (indica o s): En e he ac o s ha can make an in e en ion bene icial o de imen al o
one o mo e s akeholde s. Aim o minimal ambigui y and o e lap be ween ac o s.
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Tab: Pe o mances
The op ions and impac ac o s you en e ed ea lie a e au oma ically illed in. You s ill need o p o ide
he ollowing inpu s:
Desc ibe he e ec s o he op ion: In he designa ed cells, desc ibe he e ec s o each op ion o each
ac o . How does he in e en ion di e om doing no hing? Be as ac ual as possible—use quan i a i e
da a i a ailable, o quali a i e desc ip ions o he wise. The desc ip ion has no e ec on he calcula ion,
bu you can show his sc een o he sake o anspa ency.
How posi i e o nega i e is he e ec ?: Indica e he deg ee o which he desc ibed e ec s a e nega i e,
posi i e, o neu al (compa ed o he do-no hing scena io), by selec ing om he d opdown menus. Fo
he calcula ion o impac sco es, hese quali a i e labels (nega i e–posi i e) a e con e ed in o
nume ical alues anging om -1 o +1.
Tab: Su eys
This ab is op ional. He e you can eques indi idual membe s o s akeholde g oups o pa icipa e in
he p ocess by email. The module allows you o selec indi idual ecipien s and se expi a ion da es.

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Tab: Weigh s
He e you o he s akeholde s hemsel es can assign weigh s o each o he impac ac o s e lec ing hei
ela i e impo ance. Assign a sco e be ween 10 (maximum impo ance) and 0 (no impo an ). A
common app oach is o s a by iden i ying he mos impo an ac o and hen a ing he o he ac o s
ela i e o ha one. I is possible o mul iple ac o s o ha e he same weigh . I is also possible ha no
ac o ecei es he maximum weigh .
Tab: Resul s
Unde his ab you ind he impac sco es and a ious isualisa ions o hese esul s. The e is a sub ab
‘Compa e op ions’ and one sub ab o one op ion each o mo e de ail.
Sub ab: Compa e op ions
Based on you inpu , his ab displays wo g aphs o compa ing he op ions:
To al ela i e impac sco e, b eakdown pe s akeholde : This shows he ex en o which s akeholde s
a e posi i ely o nega i ely a ec ed by each op ion.
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To al ela i e impac sco e, b eakdown pe ac o : This shows he ex en o which each ac o
con ibu es posi i ely o nega i ely o he o al e ec .
In bo h g aphs, 100% ep esen s he maximum possible (posi i e o nega i e) e ec an op ion could
ha e ac oss all ac o s and all s akeholde s. The layou o he cha s can be cus omised. Fo cla i y, i is
ad isable o use one consis en colou pe s akeholde , ega dless o whe he he impac is posi i e o
nega i e.
Op ion-speci ic sub abs
The op ion-speci ic sub abs allow you o see, o one op ion, wha i s (dis)ad an ages a e and o which
s akeholde hey a e ele an .
Absolu e impac sco e pe s akeholde , b eakdown by ac o : This shows he impac o he op ion on
each ac o and displays he s akeholde s o whom he impac is ele an . S akeholde s a e shown on
he ho izon al axis. On he e ical axis, a sco e o 1 co esponds o he maximum (posi i e o nega i e)
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impac o one s akeholde on one ac o . The e o e, he mo e ele an ac o s he e a e pe s akeholde ,
he highe he po en ial impac sco e.
Rela i e impac pe ac o : This shows he impac o he op ion on each ac o and he s akeholde s o
whom ha impac is ele an . 100% ep esen s he maximum possible impac pe ac o .
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Re e ences
e Bo eld , G., Kese u, I., & Macha is, C. (2022). When mone a isa ion and anking a e no app op ia e.
A no el s akeholde -based app aisal me hod. T anspo a ion Resea ch Pa A: Policy and P ac ice, 156,
192–205. h ps://doi.o g/10.1016/J.TRA.2021.12.004