P ojec numbe : F-DUT-2022-0088
D i ing Equi able and Accessible 15 Minu e
Neighbou hood T ans o ma ions
WP2. Re iew and compa a i e analysis
T2.3. Unde s anding and benchma king he exis ing a el and des ina ion selec ion
beha iou s
Deli e able 2.3
Unde s anding and benchma king he exis ing
a el and des ina ion selec ion beha iou s
Da e: 17/03/2025
Responsible pa ne : Uni e si ä ü Bodenkul u Wien (BOKU)
Au ho s:
Geo gia Cha alampidou, Uni e si ä ü Bodenkul u Wien (BOKU)
Roman Klemen schi z, Uni e si ä ü Bodenkul u Wien (BOKU)
Yusak Susilo, Uni e si ä ü Bodenkul u Wien (BOKU)
2
DOCUMENT CHANGE RECORD
Ve sion Da e S a us Au ho Desc ip ion
0.1 04/07/2024 D a Geo gia Cha alampidou (BOKU) Fi s esul s
0.2 23/07/2024 D a Geo gia Cha alampidou (BOKU) Adding esul s om
popula ion segmen s
0.3 15/11/2024 D a Roman Klemen schi z (BOKU),
Yusak Susilo (BOKU)
In e nal e iew, edi ,
e ise
0.4 09/12/2024 D a
Anna G igolon (UT),
Jel en Bague (Mpac )
Daniela A ias Molina es (UT),
Domokos Esz e gá -Kiss (BME)
Fi s ound o e iew
0.5 7/02/2025 D a Geo gia Cha alampidou (BOKU) Final e sion a e i s
ound o e iew
0.6 17/02/2025 D a
Daniela A ias Molina es (UT),
Ba an Ulak (UT),
Domokos Esz e gá -Kiss (BME),
Ana Cla a Szymanski (TUM),
Cha lo e an Vessem (VUB)
Second ound o e iew
1.0 17/03/2025 Final
e sion Geo gia Cha alampidou (BOKU) Final e sion a e he
e iew p ocess
The DUT Pa ne ship is suppo ed by he Eu opean Comission and unded unde he Ho izon Eu ope co- unded Pa ne ship scheme
(Topic HORIZON-CL5-2021-D2-01-16)
3
TABLE OF CONTENTS
DOCUMENT CHANGE RECORD ...................................................................................................... 2
TABLE OF CONTENTS ....................................................................................................................... 3
LIST OF FIGURES ............................................................................................................................... 5
LIST OF TABLES ............................................................................................................................... 10
1. EXECUTIVE SUMMARY ......................................................................................................... 14
2. INTRODUCTION .................................................................................................................... 15
3. METHODOLOGY .................................................................................................................... 16
4. VIENNA ................................................................................................................................... 19
4.1. Gene al cha ac e is ics o Vienna and LL loca ion ....................................................................................... 19
4.2. Desc ip i e s a is ical analysis ............................................................................................................................. 20
4.3. Modal spli .................................................................................................................................................................... 21
4.4. T ip Cha ac e is ics – Vienna ................................................................................................................................ 22
4.5. T ip Cha ac e is ics – Liesing ............................................................................................................................... 28
4.6. T a el beha iou ac oss di e en socioeconomic g oups ........................................................................ 34
5. UTRECHT ............................................................................................................................... 36
5.1. Gene al cha ac e is ics o U ech and LL loca ion...................................................................................... 36
5.2. Desc ip i e s a is ical analysis ............................................................................................................................. 37
5.3. Modal spli .................................................................................................................................................................... 38
5.4. T ip Cha ac e is ics – U ech .............................................................................................................................. 39
5.5. T ip Cha ac e is ics – O e ech ......................................................................................................................... 46
5.6. T a el beha iou ac oss di e en socioeconomic g oups ........................................................................ 50
6. BRUSSELS .............................................................................................................................. 52
6.1. Gene al cha ac e is ics o B ussels and LL loca ion .................................................................................... 52
6.2. Desc ip i e s a is ical analysis ............................................................................................................................. 53
6.3. Modal spli .................................................................................................................................................................... 54
6.4. T ip Cha ac e is ics – B ussels ............................................................................................................................ 55
6.5. T ip Cha ac e is ics – B ussels Ci y ................................................................................................................... 61
6.6. T a el beha iou ac oss di e en socioeconomic g oups ........................................................................ 66
7. BUDAPEST ............................................................................................................................. 68
7.1. Gene al cha ac e is ics o Budapes and LL loca ion .................................................................................. 68
7.2. Desc ip i e s a is ical analysis ............................................................................................................................. 68
7.3. Modal spli .................................................................................................................................................................... 70
7.4. T ip Cha ac e is ics – Budapes ........................................................................................................................... 71
7.5. T ip Cha ac e is ics – 16 h and 17 h dis ic .................................................................................................... 76
7.6. T a el beha iou ac oss di e en socioeconomic g oups ........................................................................ 79
4
8. ÎLE-DE-FRANCE ..................................................................................................................... 81
8.1. Gene al cha ac e is ics o Île-de-F ance and LL loca ion.......................................................................... 81
8.2. Desc ip i e s a is ical analysis ............................................................................................................................. 82
8.3. Modal spli .................................................................................................................................................................... 83
8.4. T ip Cha ac e is ics - Île-de-F ance ................................................................................................................... 84
8.5. T ip Cha ac e is ics – Essonne ............................................................................................................................. 91
8.6. T a el beha iou ac oss di e en socioeconomic g oups ........................................................................ 97
9. MUNICH ................................................................................................................................ 99
9.1. Gene al cha ac e is ics o Munich and LL loca ion ...................................................................................... 99
9.2. Desc ip i e s a is ical analysis ...........................................................................................................................100
9.3. Modal spli ..................................................................................................................................................................101
9.4. T ip Cha ac e is ics – Munich ............................................................................................................................102
9.5. T ip Cha ac e is ics – Dense Town a S-Bahn Te mini ............................................................................108
9.6. T a el beha iou ac oss di e en socioeconomic g oups ......................................................................114
10. COMPARISON ..................................................................................................................... 116
10.1. Ci y le el ..................................................................................................................................................................116
10.2. Ou ski s (Li ing Lab) le el .............................................................................................................................119
11. CONCLUSIONS .................................................................................................................... 122
12. REFERENCES ......................................................................................................................... 124
APPENDIX A ................................................................................................................................... 125
APPENDIX B ................................................................................................................................... 130
APPENDIX C ................................................................................................................................... 135
APPENDIX D ................................................................................................................................... 139
APPENDIX E ................................................................................................................................... 142
APPENDIX F ................................................................................................................................... 147
APPENDIX G ................................................................................................................................... 152
APPENDIX H ................................................................................................................................... 158
5
LIST OF FIGURES
Figu e 1: Loca ion o he Liesing dis ic (o ange line) and he Vienna Li ing Lab ( ed pin) (Sou ce:
OSM (2024)) ......................................................................................................................................................... 19
Figu e 2: Modal spli by ip pu pose - Vienna ........................................................................................... 21
Figu e 3: Modal spli by ip pu pose - Liesing ........................................................................................... 22
Figu e 4: Densi y plo o wo k ip du a ion (a) and dis ance (b) by anspo mode – Vienna .... 23
Figu e 5: Cumula i e dis ibu ion unc ion (CDF) o wo k ip du a ion (a, b) and dis ance (c, d)–
Vienna .................................................................................................................................................................... 23
Figu e 6: Densi y plo o educa ional ip du a ion (a) and dis ance (b) by anspo mode – Vienna
................................................................................................................................................................................. 24
Figu e 7: Cumula i e dis ibu ion unc ion (CDF) o educa ional ip du a ion (a, b) and dis ance
(c, d)– Vienna ....................................................................................................................................................... 25
Figu e 8: Densi y plo o shopping ip du a ion (a) and dis ance (b) by anspo mode – Vienna
................................................................................................................................................................................. 26
Figu e 9: Cumula i e dis ibu ion unc ion (CDF) o shopping ip du a ion (a, b) and dis ance (c,
d)– Vienna ............................................................................................................................................................. 26
Figu e 10: Densi y plo o leisu e ip du a ion (a) and dis ance (b) by anspo mode – Vienna 27
Figu e 11: Cumula i e dis ibu ion unc ion (CDF) o leisu e ip du a ion (a, b) and dis ance (c, d)–
Vienna .................................................................................................................................................................... 28
Figu e 12: Densi y plo o wo k ip du a ion (a) and dis ance (b) by anspo mode – Liesing ... 29
Figu e 13: Cumula i e dis ibu ion unc ion (CDF) o wo k ip du a ion (a, b) and dis ance (c, d)–
Liesing .................................................................................................................................................................... 29
Figu e 14: Densi y plo o educa ional ip du a ion (a) and dis ance (b) by anspo mode –
Liesing .................................................................................................................................................................... 30
Figu e 15: Cumula i e dis ibu ion unc ion (CDF) o educa ional ip du a ion (a, b) and dis ance
(c, d)– Liesing ....................................................................................................................................................... 31
Figu e 16: Densi y plo o shopping ip du a ion (a) and dis ance (b) by anspo mode – Liesing
................................................................................................................................................................................. 31
Figu e 17: Cumula i e dis ibu ion unc ion (CDF) o shopping ip du a ion (a, b) and dis ance (c,
d)– Liesing ............................................................................................................................................................. 32
Figu e 18: Densi y plo o leisu e ip du a ion (a) and dis ance (b) by anspo mode – Liesing 33
Figu e 19: Cumula i e dis ibu ion unc ion (CDF) o leisu e ip du a ion (a, b) and dis ance (c, d)–
Liesing .................................................................................................................................................................... 33
Figu e 20: Loca ion o he U ech Li ing Lab “O e ech ” (o ange do ) (Sou ce: OSM (2024)) ... 36
Figu e 21: Modal spli by ip pu pose – U ech ........................................................................................ 38
Figu e 22: Modal spli by ip pu pose - O e ech ................................................................................... 39
Figu e 23: Densi y plo o wo k ip du a ion (a) and dis ance (b) by anspo mode – U ech . 39
6
Figu e 24: Cumula i e dis ibu ion unc ion (CDF) o wo k ip du a ion (a, b) and dis ance (c, d)–
U ech ................................................................................................................................................................... 40
Figu e 25: Densi y plo o educa ional ip du a ion (a) and dis ance (b) by anspo mode –
U ech ................................................................................................................................................................... 41
Figu e 26: Cumula i e dis ibu ion unc ion (CDF) o educa ional ip du a ion (a, b) and dis ance
(c, d)– U ech ...................................................................................................................................................... 42
Figu e 27: Densi y plo o shopping ip du a ion (a) and dis ance (b) by anspo mode – U ech
................................................................................................................................................................................. 43
Figu e 28: Cumula i e dis ibu ion unc ion (CDF) o shopping ip du a ion (a, b) and dis ance (c,
d)– U ech ............................................................................................................................................................ 43
Figu e 29: Densi y plo o leisu e ip du a ion (a) and dis ance (b) by anspo mode – U ech
.................................................................................................................................................................................44
Figu e 30: Cumula i e dis ibu ion unc ion (CDF) o leisu e ip du a ion (a, b) and dis ance (c, d)–
U ech ................................................................................................................................................................... 45
Figu e 31: Densi y plo o wo k ip du a ion (a) and dis ance (b) by anspo mode – O e ech
................................................................................................................................................................................. 46
Figu e 32: Cumula i e dis ibu ion unc ion (CDF) o wo k ip du a ion (a) and dis ance (b)–
O e ech .............................................................................................................................................................. 46
Figu e 33: Densi y plo o shopping ip du a ion (a) and dis ance (b) by anspo mode –
O e ech .............................................................................................................................................................. 47
Figu e 34: Cumula i e dis ibu ion unc ion (CDF) o shopping ip du a ion (a, b) and dis ance (c,
d)– O e ech ....................................................................................................................................................... 48
Figu e 35: Densi y plo o leisu e ip du a ion (a) and dis ance (b) by anspo mode – O e ech
................................................................................................................................................................................. 49
Figu e 36: Cumula i e dis ibu ion unc ion (CDF) o leisu e ip du a ion (a, b) and dis ance (c, d)–
O e ech .............................................................................................................................................................. 49
Figu e 37: Loca ion o he Ci y o B ussels dis ic (o ange line) and he B ussels’ Li ing Lab ( ed
pins) (Sou ce: OSM (2024)) .............................................................................................................................. 52
Figu e 38: Modal spli by ip pu pose – B ussels ...................................................................................... 54
Figu e 39: Modal spli by ip pu pose – B ussels Ci y .............................................................................. 55
Figu e 40: Densi y plo o wo k ip du a ion (a) and dis ance (b) by anspo mode – B ussels 55
Figu e 41: Cumula i e dis ibu ion unc ion (CDF) o wo k ip du a ion (a, b) and dis ance (c, d)–
B ussels .................................................................................................................................................................. 56
Figu e 42: Densi y plo o educa ional ip du a ion (a) and dis ance (b) by anspo mode –
B ussels .................................................................................................................................................................. 57
Figu e 43: Cumula i e dis ibu ion unc ion (CDF) o educa ional ip du a ion (a, b) and dis ance
(c, d)– B ussels ..................................................................................................................................................... 57
Figu e 44: Densi y plo o shopping ip du a ion (a) and dis ance (b) by anspo mode – B ussels
................................................................................................................................................................................. 58
Figu e 45: Cumula i e dis ibu ion unc ion (CDF) o shopping ip du a ion (a, b) and dis ance (c,
d)– B ussels ........................................................................................................................................................... 59
7
Figu e 46: Densi y plo o leisu e ip du a ion (a) and dis ance (b) by anspo mode – B ussels
................................................................................................................................................................................. 60
Figu e 47: Cumula i e dis ibu ion unc ion (CDF) o leisu e ip du a ion (a, b) and dis ance (c, d)–
B ussels .................................................................................................................................................................. 60
Figu e 48: Densi y plo o wo k ip du a ion (a) and dis ance (b) by anspo mode – B ussels
Ci y .......................................................................................................................................................................... 61
Figu e 49: Cumula i e dis ibu ion unc ion (CDF) o wo k ip du a ion (a, b) and dis ance (c, d)–
B ussels Ci y ......................................................................................................................................................... 62
Figu e 50: Densi y plo o educa ional ip du a ion (a) and dis ance (b) by anspo mode –
B ussels Ci y ......................................................................................................................................................... 62
Figu e 51: Cumula i e dis ibu ion unc ion (CDF) o educa ional ip du a ion (a) and dis ance (b)–
B ussels Ci y ......................................................................................................................................................... 63
Figu e 52: Densi y plo o shopping ip du a ion (a) and dis ance (b) by anspo mode – B ussels
Ci y .......................................................................................................................................................................... 64
Figu e 53: Cumula i e dis ibu ion unc ion (CDF) o shopping ip du a ion (a, b) and dis ance (c,
d)– B ussels Ci y .................................................................................................................................................. 64
Figu e 54: Densi y plo o leisu e ip du a ion (a) and dis ance (b) by anspo mode – B ussels
Ci y .......................................................................................................................................................................... 65
Figu e 55: Cumula i e dis ibu ion unc ion (CDF) o leisu e ip du a ion (a, b) and dis ance (c, d)–
B ussels Ci y ......................................................................................................................................................... 66
Figu e 56: Loca ion o he Rákosmen e dis ic (o ange line) (Sou ce: OSM (2024)) ....................... 68
Figu e 57: Modal spli by ip pu pose – Budapes .................................................................................... 70
Figu e 58: Modal spli by ip pu pose – 16 h & 17 h Dis ic ..................................................................... 70
Figu e 59: Densi y plo o wo k ip du a ion by anspo mode – Budapes ................................... 71
Figu e 60: Cumula i e dis ibu ion unc ion (CDF) o wo k ip du a ion– Budapes ....................... 71
Figu e 61: Densi y plo o educa ional ip du a ion by anspo mode – Budapes ....................... 72
Figu e 62: Cumula i e dis ibu ion unc ion (CDF) o educa ional ip du a ion– Budapes .......... 73
Figu e 63: Densi y plo o shopping ip du a ion by anspo mode – Budapes ........................... 73
Figu e 64: Cumula i e dis ibu ion unc ion (CDF) o shopping ip du a ion– Budapes .............. 74
Figu e 65: Densi y plo o leisu e ip du a ion by anspo mode – Budapes ................................ 75
Figu e 66: Cumula i e dis ibu ion unc ion (CDF) o leisu e ip du a ion– Budapes .................... 75
Figu e 67: Densi y plo o wo k ip du a ion by anspo mode – 16 h & 17 h Dis ic .................... 76
Figu e 68: Cumula i e dis ibu ion unc ion (CDF) o wo k ip du a ion– 16 h & 17 h Dis ic ........ 76
Figu e 69: Densi y plo o shopping ip du a ion by anspo mode – 16 h & 17 h Dis ic ............ 77
Figu e 70: Cumula i e dis ibu ion unc ion (CDF) o shopping ip du a ion– 16 h & 17 h Dis ic 78
Figu e 71: Densi y plo o leisu e ip du a ion by anspo mode – 16 h & 17 h Dis ic .................. 78
Figu e 72: Cumula i e dis ibu ion unc ion (CDF) o leisu e ip du a ion– 16 h & 17 h Dis ic ..... 79
Figu e 73: Loca ion o he Essonne dis ic (o ange line) (Sou ce: OSM (2024)) ............................... 81
8
Figu e 74: Modal spli by ip pu pose - Île-de-F ance ............................................................................. 83
Figu e 75: Modal spli by ip pu pose - Essonne ....................................................................................... 84
Figu e 76: Densi y plo o wo k ip du a ion (a) and dis ance (b) by anspo mode – Île-de-
F ance ..................................................................................................................................................................... 84
Figu e 77: Cumula i e dis ibu ion unc ion (CDF) o wo k ip du a ion (a, b) and dis ance (c, d)–
Île-de-F ance ........................................................................................................................................................ 85
Figu e 78: Densi y plo o educa ional ip du a ion (a) and dis ance (b) by anspo mode – Île-
de-F ance .............................................................................................................................................................. 86
Figu e 79: Cumula i e dis ibu ion unc ion (CDF) o educa ional ip du a ion (a, b) and dis ance
(c, d)– Île-de-F ance ........................................................................................................................................... 87
Figu e 80: Densi y plo o shopping ip du a ion (a) and dis ance (b) by anspo mode – Île-de-
F ance ..................................................................................................................................................................... 88
Figu e 81: Cumula i e dis ibu ion unc ion (CDF) o shopping ip du a ion (a, b) and dis ance (c,
d)– Île-de-F ance ................................................................................................................................................. 88
Figu e 82: Densi y plo o leisu e ip du a ion (a) and dis ance (b) by anspo mode – Île-de-
F ance ..................................................................................................................................................................... 89
Figu e 83: Cumula i e dis ibu ion unc ion (CDF) o leisu e ip du a ion (a, b) and dis ance (c, d)–
Île-de-F ance ........................................................................................................................................................ 90
Figu e 84: Densi y plo o wo k ip du a ion (a) and dis ance (b) by anspo mode – Essonne 91
Figu e 85: Cumula i e dis ibu ion unc ion (CDF) o wo k ip du a ion (a, b) and dis ance (c, d)–
Essonne .................................................................................................................................................................. 92
Figu e 86: Densi y plo o educa ional ip du a ion (a) and dis ance (b) by anspo mode –
Essonne .................................................................................................................................................................. 93
Figu e 87: Cumula i e dis ibu ion unc ion (CDF) o educa ional ip du a ion (a, b) and dis ance
(c, d)– Essonne ..................................................................................................................................................... 93
Figu e 88: Densi y plo o shopping ip du a ion (a) and dis ance (b) by anspo mode – Essonne
................................................................................................................................................................................. 94
Figu e 89: Cumula i e dis ibu ion unc ion (CDF) o shopping ip du a ion (a, b) and dis ance (c,
d)– Essonne ........................................................................................................................................................... 95
Figu e 90: Densi y plo o leisu e ip du a ion (a) and dis ance (b) by anspo mode – Essonne
................................................................................................................................................................................. 96
Figu e 91: Cumula i e dis ibu ion unc ion (CDF) o leisu e ip du a ion (a, b) and dis ance (c, d)–
Essonne .................................................................................................................................................................. 96
Figu e 92: Loca ion o he Munich Li ing Labs ( ed pins) (Sou ce: OSM (2024)) ............................... 99
Figu e 93: Modal spli by ip pu pose – Munich ...................................................................................... 101
Figu e 94: Modal spli by ip pu pose – Dense Towns a S-Bahn Te mini ....................................... 102
Figu e 95: Densi y plo o wo k ip du a ion (a) and dis ance (b) by anspo mode – Munich 102
Figu e 96: Cumula i e dis ibu ion unc ion (CDF) o wo k ip du a ion (a, b) and dis ance (c, d)–
Munich ................................................................................................................................................................. 103
9
Figu e 97: Densi y plo o educa ional ip du a ion (a) and dis ance (b) by anspo mode –
Munich ................................................................................................................................................................. 104
Figu e 98: Cumula i e dis ibu ion unc ion (CDF) o educa ional ip du a ion (a, b) and dis ance
(c, d)– Munich .................................................................................................................................................... 104
Figu e 99: Densi y plo o shopping ip du a ion (a) and dis ance (b) by anspo mode – Munich
............................................................................................................................................................................... 105
Figu e 100: Cumula i e dis ibu ion unc ion (CDF) o shopping ip du a ion (a, b) and dis ance
(c, d)– Munich .................................................................................................................................................... 106
Figu e 101: Densi y plo o leisu e ip du a ion (a) and dis ance (b) by anspo mode – Munich
............................................................................................................................................................................... 107
Figu e 102: Cumula i e dis ibu ion unc ion (CDF) o leisu e ip du a ion (a, b) and dis ance (c,
d)– Munich .......................................................................................................................................................... 107
Figu e 103: Densi y plo o wo k ip du a ion (a) and dis ance (b) by anspo mode – Dense
Towns a S-Bahn Te mini ................................................................................................................................ 108
Figu e 104: Cumula i e dis ibu ion unc ion (CDF) o wo k ip du a ion (a, b) and dis ance (c, d)–
Dense Towns a S-Bahn Te mini ................................................................................................................... 109
Figu e 105: Densi y plo o educa ional ip du a ion (a) and dis ance (b) by anspo mode –
Dense Towns a S-Bahn Te mi ........................................................................................................................ 110
Figu e 106: Cumula i e dis ibu ion unc ion (CDF) o educa ional ip du a ion (a, b) and dis ance
(c, d)– Dense Towns a S-Bahn Te mini........................................................................................................ 110
Figu e 107: Densi y plo o shopping ip du a ion (a) and dis ance (b) by anspo mode – Dense
Towns a S-Bahn Te mi .................................................................................................................................... 111
Figu e 108: Cumula i e dis ibu ion unc ion (CDF) o shopping ip du a ion (a, b) and dis ance
(c, d)– Dense Towns a S-Bahn Te mini........................................................................................................ 112
Figu e 109: Densi y plo o leisu e ip du a ion (a) and dis ance (b) by anspo mode – Dense
Towns a S-Bahn Te mi .................................................................................................................................... 113
Figu e 110: Cumula i e dis ibu ion unc ion (CDF) o leisu e ip du a ion (a, b) and dis ance (c,
d)– Dense Towns a S-Bahn Te mini ............................................................................................................. 113
Figu e 111: Cumula i e dis ibu ion unc ion (CDF) o ip du a ion pe ip pu pose– Ci y le el 116
Figu e 112: Pe cen age o ips comple ed wi hin 15 minu es by ip pu pose - Ci y le el ............ 116
Figu e 113: Cumula i e dis ibu ion unc ion (CDF) o ip du a ion pe ip pu pose– Ou ski s
(Li ing Lab) le el ................................................................................................................................................ 119
Figu e 114: Pe cen age o ips comple ed wi hin 15 minu es by ip pu pose – Ou ski s (Li ing
Lab) le el .............................................................................................................................................................. 119
16
3. METHODOLOGY
Fo he compa a i e da a analysis, we used he exis ing household a el su eys om all he Li ing Lab
(LL) loca ions. Each LL had access o a leas one household a el su ey da ase . To gain a clea e
unde s anding o he scope and con en o hese su eys, a s uc u ed ques ionnai e was de eloped
(Appendix H). This ques ionnai e helped in collec ing all he ele an de ails and selec ing he mos
sui able da ase o he analysis. The speci ic in o ma ion we sough o ga he included he ollowing:
1. Gene al in o ma ion abou he su ey (e.g. name, yea , sample size, desc ip ion o he pu pose)
2. Da ase in o ma ion (e.g. a ailabili y es ic ions, o ma ype, language)
3. In o ma ion abou he a ibu es o households and people
4. In o ma ion abou he a ibu es o each epo ed ip
A e collec ing and e alua ing he ele an in o ma ion om all, a ailable o use, household a el
su eys, we selec ed he da ase s p esen ed in Table 1 o he analysis. Table 2 p o ides an o e iew o
he da ase cha ac e is ics and a iables.
Table 1: Household a el su ey selec ion
Coun y/Region T a el Su ey
Aus ia
Ös e eich Un e wegs 2013-14 (ÖU)
Ne he lands
Onde weg in Nede land 2021-22 (ODiN)
B ussels Onde zoek Ve plaa singsged ag 2021-22 (OVG)
Budapes Household Su ey o Uni ied Mac oscopic T anspo Model 2019
Île
-
de
-
F ance
Enquê e Globale T anspo 2018-20 (EGT)
Ge many
Mobili ä in Deu schland 2017 (MiD)
The goal o he compa a i e analysis, as p e iously ou lined in his documen , is o assess and enhance
he unde s anding o cu en a el pa e ns and beha io s among indi iduals li ing in he LL loca ions.
The e o e, he analysis ocused on he a el beha iou o indi iduals in hei local en i onmen .
Acco dingly, a speci ic me hodology has been implemen ed. Each da abase has been il e ed o ma ch
wi h he ollowing c i e ia:
1. All he epo ed ips ha e as o igin he esiden ial dis ic o he esponden .
2. All he epo ed ips ha e as des ina ion he same coun y, o a oid long ips ha could
in luence he inal ou pu o he analysis.
3. The pu pose o he epo ed ips is wo k, educa ion, shopping, and leisu e. The selec ion is
based on he p io i ies se ou in he 15-minu e-ci y concep and iden i ied in Deli e able
2.1 (1). Howe e , Deli e able 2.1 iden i ies 6 co e unc ions called: wo k, comme ce (he e,
shopping), educa ion, heal hca e and se ices. As no all da ase s include ips om he
heal hca e ca ego y, and ips ela ed o se ices canno be accu a ely iden i ied, hese wo
ip pu pose ca ego ies a e no included in he analysis.
4. The a el mode o he epo ed ips is pedes ian, bicycle, ca (d i e o passenge ), o
public anspo .
The c i e ia we e shaped based on he mu ual cha ac e is ics o he da ase s in use. As illus a ed in
Table 2, i becomes e iden ha he agg ega ion le el o he esiden egion o he esponden s a ies
ac oss he da ase s. Consequen ly, he dis ic le el was selec ed as i is consis en ac oss all da ase s. I
is no ewo hy ha he Aus ian and Ge man na ional household da ase s a e he mos ou da ed;
howe e , hey we e he only a ailable da ase s o analysis, hus necessi a ing hei use. Wi h ega d o
socioeconomic- ela ed a iables on indi idual le el, i is obse ed ha he B ussels da ase does no
include a subs an ial numbe o a iables pe inen o he analysis. Finally, in he Budapes da ase , he
ip du a ion and dis ance a iables we e no included, and hus, hey had o be calcula ed o he
analysis. The ip du a ion a iable was success ully calcula ed using he eco ded s a and end imes
o he ip; howe e , he ip dis ance a iable could no be calcula ed due o an absence o ele an da a.
A mo e ho ough exposi ion o he da a analysis cha ac e is ics o each ci y can be ound in he ollowing
sec ions.
Table 2: O e iew o he na ional household a el su ey cha ac e is ics and a iables
Aus ia The Ne he lands B ussels Budapes Île-de-F ance Ge many
A.
Gene al In o ma ion
Name
Ös e eich
Un e wegs (ÖU)
Onde weg in
Nede land (ODiN)
Onde zoek
Ve plaa singsged ag
(OVG)
Household su ey
o Uni ied
Mac oscopic
T anspo model
Enquê e Globale
T anspo 2020
(EGT
H2020)
Mobili ä in
Deu schland (MiD)
Yea
2013
-
2014
2021
-
2022
2021
-
2022
2019
2018
-
2020
2017
Numbe o epo ed days pe esponden
2 1 1 1 1 1
Type o epo ed days
All he days
All he days
All he days
Weekdays
Weekdays
All he days
Su ey pe iod
Oc obe 2013–
Decembe 2014
Janua y 2021 –
Decembe 2021
Ma ch 2021 –
Janua y 2022
Oc obe –
No embe 2019
Janua y 2018 –
Ma ch 2020
May 2016 –
Oc obe 2017
Ne sample size
17.070 Households
– 38.220
Indi iduals
48.000 Indi iduals 2.685 Indi iduals
4800 Households in
Budapes , 120
households in
Agglome a ion
4.800 Households,
10.470 Indi iduals
156.420
Households,
316.361 Indi iduals
Su ey a ea
Aus ia The Ne he lands B ussels Capi al
Region
Budapes and
Agglome a ion Île-de-F ance Ge many
De ini ion o epo ed ip
E e y ip ha uses
he public
space/ne wo k
Indi idual epo on
ac i i y o he
eques ed day
-
Doo o doo by
add esses o e e y
ips du ing one
wo kday
Indi idual epo o
all ips made
du ing he day
be o e he
in e iew
All ips made by
he membe s o a
household h ough
he epo ed day
Agg ega ion le el
Dis ic (Bezi k) Pos al code Pos al code Dis ic & Add ess Cou onne/ Dis ic
Add ess, Pos al
code, Municipali y,
Dis ic
B.
Household Cha ac e is ics
Li ing Loca ion
✓ ✓ ✓ ✓ ✓ ✓
Size
✓ ✓ ✓ ✓ ✓ ✓
Composi ion
✓ ✓ - ✓ ✓ -
Income
✓ ✓ - ✓ ✓ ✓
Num. and ype o p i a e anspo means
✓
✓
✓
✓
✓
✓
C. Indi iduals Cha ac e is ics
Age
✓
✓
✓
✓
✓
✓
Gende
✓
✓
✓
✓
✓
✓
Academic le el
✓
✓
-
✓
✓
✓
Occupa ion
✓
✓
-
✓
✓
✓
Income
✓
✓
-
✓
✓
-
PT Subsc ip ions
✓ ✓ - ✓ ✓ ✓
D i ing licence
✓ ✓ - ✓ ✓ ✓
A ailable means o anspo
✓ ✓ - ✓ ✓ ✓
18
To al a el dis ance pe pe son
✓
✓
- - - -
To al a el ime pe pe son
✓
✓
- -
✓
-
D.
T ips Cha ac e is ics
Agg ega ion le el o o igin and des ina ion
Pos al code,
Municipali y,
Dis ic
Pos al code Pos al code Add ess Cou onne/ Dis ic
Add ess, Pos al
code, Municipali y,
Dis ic
T ip pu pose
Wo k
✓
✓
✓
✓
✓
✓
Business ip
✓
✓
✓
✓
✓
✓
School/Educa ion
✓
✓
✓
✓
✓
✓
D opping o /picking up/accompanying people ✓ ✓ ✓ ✓ ✓ ✓
Shopping ✓ ✓ ✓ ✓ ✓ ✓
Running e ands ✓ ✓ ✓ ✓ ✓ ✓
Leisu e
✓
✓
✓
✓
✓
✓
Visi ing iends ✓ ✓ ✓ ✓ ✓ -
O he - Rec ea ional
walking
Rec ea ional
walking - - -
T ip mode
✓ ✓ ✓ ✓ ✓ ✓
T ip leng h
✓ ✓ ✓ - ✓ ✓
T ip du a ion
✓ ✓ ✓ - ✓ ✓
4. VIENNA
4.1. Gene al cha ac e is ics o Vienna and LL loca ion
Vienna is he capi al and one o he nine ede al s a es o Aus ia and consis s o 23 dis ic s (“Bezi ke”).
Wi h mo e han 2 million inhabi an s in 2024, i is he la ges ci y in Aus ia and one o he as es
g owing majo ci ies in Eu ope (2). Vienna has an ex ensi e public anspo in as uc u e consis ing
o 6 unde g ound lines, ailway, subu ban ailway, am, bus and bicycle in as uc u e. I also o e s ca
and mic omobili y sha ing se ices.
The Viennese Li ing Lab is Wiene Flu and i s su ounding neighbou hoods, which a e loca ed in he
23 d Dis ic o Vienna, known as "Liesing". Liesing is si ua ed in he sou h-wes o Vienna and has a
popula ion o app oxima ely 118.000 inhabi an s. Wiene Flu is p oxima e o he bo de o Lowe
Aus ia and cons i u es he la ges public housing de elopmen in he o me illage o Siebenhi en in
Liesing. The a ea is se ed by he U6 unde g ound line, a am line, bus lines and ca /bike sha ing
se ices.
Figu e 1 shows he map o Vienna and he loca ion o he Viennese Li ing Lab “Wiene Flu ” ( ed pin).
Figu e 1: Loca ion o he Liesing dis ic (o ange line) and he Vienna Li ing Lab ( ed pin) (Sou ce: OSM (2024))
20
4.2. Desc ip i e s a is ical analysis
The analysis begins wi h an o e iew o he socioeconomic cha ac e is ics o households and
indi iduals. A sho lis o a iables has been selec ed om he da ase “Ös e eich Un e wegs 2013/14”
(2), o help us pic u e and unde s and he cha ac e is ics o esiden s, bo h a he ci y le el and a he
dis ic le el o he Li ing Lab loca ion. Table 3 shows he socioeconomic cha ac e is ics o households,
while Table 4 ou lines he socioeconomic cha ac e is ics o indi iduals.
I should be no ed ha he in o ma ion on he esponden 's place o esidence is p o ided by he da ase
ÖU a he dis ic le el (Bezi ke), and he e o e o he case o he LL loca ion "Wiene Flu " we analyse
he whole a ea o Liesing. The sample used o his pa o he analysis is he o al esiden popula ion
wi hin he a ea (Vienna o Liesing), wi h no il e ing o speci ic ip pu poses. Fu he mo e, he sample
o su ey esponden s who did no p o ide a alid esponse o one o mo e o he selec ed ques ions
was excluded om he sample.
Table 3: Socioeconomic cha ac e is ics o households (Vienna & Liesing) – Sou ce: ÖU 2013/14
Socioeconomic Cha ac e is ics o Households
Vienna
LL Loca ion (Liesing)
n
%
n
%
Household size
1 Pe son
970
31.9
52
27.4
2 Pe sons
1230
40.4
79
41.6
3 Pe sons 446 14.6 22 11.6
4+ Pe sons
399
13.1
37
19.5
Economic si ua ion (Sel es ima ion o
esponden s)
Ve y
poo
43
1.5
2
1.1
Poo 183 6.2 5 2.7
A e age
1334
45.1
95
51.1
Good
1089
36.8
69
37.1
Ve y good
307 10.4 15 8.1
Ca owne ship
0
620
23.1
20
11.5
1
1594
59.5
110
63.2
2 399 14.9 39 22.4
3
57
2.1
5
2.9
4+
10
0.4
-
-
Table 4: Socioeconomic cha ac e is ics o indi iduals (Vienna & Liesing) - – Sou ce: ÖU 2013/14
Socioeconomic Cha ac e is ics o Indi iduals
Vienna
LL Loca ion (Liesing)
n % n %
Gende
Male 2734 46.3 181 44.9
Female
3173
53.7
222
55.1
Age Ca ego y (y.o.)
6
–
14
368
6.2
35
8.7
15 – 19 324 5.5 30 7.4
20
–
24
332
5.6
16
4.0
25
–
34
813
13.8
46
11.4
35 – 44
783 13.3 47 11.7
45
–
54
1060
17.9
64
15.9
55
–
64
837
14.2
56
13.9
65+ 1390 23.5 109 27.0
Occupa ion
S uden
1011
17.1
85
21.1
Employed
2606
44.1
154
38.2
Pensione
1650
27.9
127
31.5
O he
640
10.8
37
9.2
Ca D i ing License
Yes
4256
80.9
295
84.8
No
1004
1
9.1
53
15.2
A ailabili y o bike
Yes
3195
62.5
252
71.2
No
1919
3
7.5
102
28.8
A ailabili y o ca
Always 2797 57.4 222 67.3
Occasionally
806
16.5
42
12.7
Ne e
1272
26.1
66
20.0
21
The desc ip i e s a is ical analysis p o ides a comp ehensi e insigh in o he demog aphic
cha ac e is ics o he esiden s o Vienna and Liesing. Fi s ly, he sample o women is sligh ly la ge han
ha o men. Compa ing he dis ibu ion wi h he o icial s a is ics (51% emales in Vienna and 52% in
Liesing), bo h o Vienna and Liesing he e is only a small o e sampling o women in he sample (3, 4).
This demons a es ha he su ey's sample ep esen s su icien ly he ac ual popula ion. Secondly,
esiden s o Liesing ha e a g ea e a ailabili y o ca s and bicycles, while sligh ly la ge p opo ion o
households in Liesing belong o he a e age income ca ego y. In addi ion, middle-aged and olde adul s,
as well as people in wo k and e i emen , a e mo e s ongly ep esen ed in he sample.
4.3. Modal spli
Figu e 2 illus a es he modal spli by ip pu pose o he ci y o Vienna. I is e iden ha Viennese
ci izens p e e by a he use o public anspo o hei educa ional and wo k ips. Rega ding leisu e
and shopping ips, he mos p e alen a el modes a e walking and public anspo . Ca use is also
popula , pa icula ly o shopping and wo k- ela ed ips, while bike use is among he leas popula
modes o anspo o all ip pu poses.
Figu e 2: Modal spli by ip pu pose - Vienna
In Liesing, he modal spli esul s show a p e e ence in ca use and public anspo , pa icula ly o
educa ion and wo k- ela ed ips (Figu e 3). Howe e , Liesing’s esiden s p e e o d i e mo e han
using public anspo o hei wo k commu es. This is la gely due o Liesing’s loca ion on he Viennese
ou ski s, whe e he public anspo ne wo k may be less ex ensi e, and many esiden s wo k in a eas
ou side o Liesing, which a e no easily accessible by modes o he han ca . As o shopping- ela ed ips,
he ca is also he dominan mode o anspo , highligh ing he lack o shopping oppo uni ies
accessible by o he mo e sus ainable modes. Bike use emains low on he lis o p e e ences among
Liesing’s esiden s. I is impo an o highligh ha he sample size o he a ea o Liesing is smalle han
ha o Vienna, and his may a ec he ep esen a i eness o he esul s. This is also e lec ed in he e o
ba s shown in he plo s.
22
Figu e 3: Modal spli by ip pu pose - Liesing
4.4. T ip Cha ac e is ics – Vienna
4.4.1. Wo k ips
The ollowing densi y plo s (Figu e 4) illus a e he dis ibu ion o he ip du a ion and ip dis ance
ac oss he 5 di e en anspo modes, while Table 5 p esen s he wo king ip du a ion and dis ance
s a is ics ac oss modes in Vienna. To gain a mo e comp ehensi e unde s anding o he ip
cha ac e is ics, he Cumula i e Dis ibu ion Func ion (CDF) has been calcula ed o bo h he a el
dis ance and du a ion. This unc ion enables he calcula ion o he pe cen age (%) o wo king ips
conduc ed up o a ce ain amoun o ime o dis ance, and helps he eade unde s and whe he o no
he a el beha iou o he people li ing in Vienna is in line wi h he 15mC concep . Figu e 5 illus a es
he CDF unc ions o wo king ip du a ion and dis ance in Vienna.
In Vienna, he a e age wo k ip du a ion is app oxima ely 30 minu es, wi h an a e age dis ance o
almos 10 kilome es. Acco ding o Table 6 only he 27% o wo k ips in Vienna a e comple ed in less
han 15 minu es. The high s anda d de ia ion (SD) sugges s signi ican a iabili y in he sample,
indica ing ha some ips a e conside ably longe o sho e han he a e age. Wo k- ela ed ips in
Vienna conduc ed by public anspo , he mos p e e ed a el mode o he Viennese esiden s o his
ip pu pose, ha e an a e age du a ion o 37 minu es while less han 10% o hese ips a e comple ed
in unde 15 minu es (see Table 6). Wo k ela ed ca ips in Vienna, ei he as d i e o passenge , a e
sho e in du a ion han he a e age, al hough he dis ances co e ed a e g ea e . Fu he mo e, mo e
han 50% o he ips unde aken by ca as a passenge las ed less han 15 minu es, while o he ips
conduc ed as a d i e his igu e app oaches 30%. Wo k ela ed walking ips in Vienna a e he sho es
in bo h du a ion and dis ance, and mo e han 80% o hem las up o 15 minu es.
23
(a) Du a ion by mode o anspo
(b) Dis ance by mode o anspo
Figu e 4: Densi y plo o wo k ip du a ion (a) and dis ance (b) by anspo mode – Vienna
Table 5: Wo k ip s a is ics by anspo mode - Vienna
T anspo Modes Sample (n) Du a ion (min) Dis ance (km)
Mean Median SD Mean Median SD
All Modes 1823 29.45 30.0 19.81 9.56 6.7 12.77
Pedes ians 197 11.87 10.0 10.33 0.93 0.5 1.04
Bicycle 114 18.48 15.0 11.18 3.77 3.0 2.75
Ca (as D i e )
532
25.34
25.0
13.63
12.01
9.0
10.69
Ca (as Passenge ) 47 23.38 15.0 21.92 15.64 6.0 36.23
Public T anspo 933 37.15 34.0 21.19 10.40 7.6 12.73
(a) Du a ion ac oss all modes (b) Du a ion by mode o anspo
(c) Dis ance ac oss all modes (d) Dis ance by mode o anspo
Figu e 5: Cumula i e dis ibu ion unc ion (CDF) o wo k ip du a ion (a, b) and dis ance (c, d)– Vienna
24
Table 6: Pe cen age o wo k ips conduc ed o di e en ime s amps and modes - Vienna
T anspo modes Sha e o ips wi h a du a ion less han (min)
10 15 20 30
All Modes 14.3% 26.9% 38.6% 65.3%
Pedes ians 62.4% 83.2% 90.4% 96.4%
Bicycle 33.3% 56.1% 68.4% 88.6%
Ca (as D i e ) 14.1% 29.9% 46.8% 76.3%
Ca (as Passenge ) 21.2% 53.2% 65.9% 85.1%
Public T anspo 1.6% 8.5% 18.0% 48.6%
4.4.2. Educa ional ips
Acco ding o Table 7, he a e age du a ion o an educa ional ip in Vienna is app oxima ely 25 minu es,
wi h an a e age dis ance o 6.2 kilome es. A high p opo ion (41%) o educa ion ips a e comple ed in
less han 15 minu es (see Table 8). Simila ly o he wo k- ela ed ips, he high s anda d de ia ion (SD)
o educa ion- ela ed ips sugges s signi ican a iabili y in he sample. This is due o he ac ha his
ca ego y includes no only ips o educa ional ins i u ions bu also o uni e si ies, which a e mos ly
loca ed in he ci y cen e o Vienna, necessi a ing longe a el dis ances. T ips conduc ed by public
anspo , which is he mos p e e ed mode o anspo o his pu pose, ha e an a e age du a ion o
32 minu es, while less han 20% o hese ips a e made in less han 15 minu es. Walking ips a e also
popula and a e much sho e (11 minu es) han a e age. Mo eo e , mo e han 90% o walking ips
a e comple ed in less han 15 minu es, indica ing a high le el o accessibili y o educa ional acili ies.
(a) Du a ion by mode o anspo
(b) Dis ance by mode o anspo
Figu e 6: Densi y plo o educa ional ip du a ion (a) and dis ance (b) by anspo mode – Vienna
Table 7: Educa ional ip s a is ics by anspo mode - Vienna
T anspo Modes Sample (n) Du a ion (min) Dis ance (km)
Mean Median SD Mean Median SD
All Modes 674 24.79 20.0 17.08 6.15 3.9 9.17
Pedes ians 149 10.67 10.0 6.21 0.81 0.5 0.66
Bicycle 24 15.37 15.0 8.57 3.09 2.0 2.47
Ca (as D i e ) 37 24.22 20.0 13.45 9.93 8.0 8.57
Ca (as Passenge ) 51 14.96 10.8 10.69 5.25 3.0 5.79
Public T anspo
413
31.70
30.0
17.08
8.02
5.0
10.52
25
(a) Du a ion ac oss all modes (b) Du a ion by mode o anspo
(c) Dis ance ac oss all modes (d) Dis ance by mode o anspo
Figu e 7: Cumula i e dis ibu ion unc ion (CDF) o educa ional ip du a ion (a, b) and dis ance (c, d)– Vienna
Table 8: Pe cen age o educa ion ips conduc ed o di e en ime s amps and modes - Vienna
T anspo Modes Sha e o ips wi h a du a ion less han (min)
10
15
20
30
All Modes 24.6% 40.5% 53.0% 74.0%
Pedes ians
67.8
%
92.6
%
96.6
%
99.3
%
Bicycle 33.3% 66.7% 83.3% 95.8%
Ca (as D i e )
21.6
%
35.1
%
54.1
%
75.7
%
Ca (as Passenge ) 49.0% 70.6% 86.3% 94.1%
Public T anspo
5.8
%
16.9
%
31.2
%
61.0
%
4.4.3. Shopping ips
Table 9, e eals ha on a e age Viennese ci izens make sho ips (16.5 minu es) o ul il hei shopping
needs. Acco ding o Table 10, 70% o shopping ips a e comple ed wi hin 15 minu es, indica ing a dense
ne wo k o shopping loca ions ac oss Vienna. Walking is he mos common mode o shopping ips,
wi h an a e age du a ion o 13 minu es, while mo e han 80% las ing up o 15 minu es. In addi ion,
shopping ips made by ca o public anspo a e equen in he sample, wi h an a e age ip du a ion
o 16 and 26 minu es espec i ely. I should be no ed ha he shopping ips included in his ca ego y
a e no only o daily needs bu also o addi ional pu chases, such as clo hing o home equipmen . This
may in luence he a e age ip du a ion as people may a el longe o each bigge e ail acili ies.
32
Table 17: Shopping ip s a is ics by anspo mode - Liesing
T anspo Modes Sample (n) Du a ion (min) Dis ance (km)
Mean Median SD Mean Median SD
All Modes 96 20.52 10.0 43.62 5.47 2.5 15.58
Pedes ians 27 32.06 15.0 77.17 1.15 1.0 0.92
Bicycle Insu icien sample size o analysis
Ca (as D i e ) 42 14.94 10.0 16.29 6.66 3.5 16.61
Ca (as Passenge ) 22 17.77 10.0 21.41 9.0 3.5 22.68
Public T anspo Insu icien sample size o analysis
(a) Du a ion ac oss all modes (b) Du a ion by mode o anspo
(c) Dis ance ac oss all modes (d) Dis ance by mode o anspo
Figu e 17: Cumula i e dis ibu ion unc ion (CDF) o shopping ip du a ion (a, b) and dis ance (c, d)– Liesing
Table 18: Pe cen age o shopping ips conduc ed o di e en ime s amps – Liesing
T anspo Modes Sha e o ips wi h a du a ion less han (min)
10
15
20
30
All Modes 52.1% 71.9% 79.2% 93.8%
Pedes ians
44.4%
70.4%
74.1%
92.6%
Bicycle Insu icien sample size o analysis
Ca (as D i e )
57.1%
76.2%
83.3%
95.2%
Ca (as Passenge ) 54.5% 72.7% 81.8% 90.9%
Public T anspo Insu icien sample size o analysis
4.5.4. Leisu e ips
Fo leisu e ips, he a e age ip du a ion is 34 minu es and dis ance 10 kilome es (Table 19). These
esul s do no di e as ly om he ones o Vienna, whe e he a e age ip du a ion is 33 minu es. In
Liesing, walking is he mos p e e ed mode o his ip pu pose wi h an a e age ip du a ion o 42
minu es. Howe e , acco ding o Table 20 only he 28% o walking ips las up o 15 minu es (bu
impo an o men ion, in his ca ego y walking ips o pleasu e i sel and walking o a speci ic enue
o leisu e ac i i y (e.g. public pool, gym) a e included). Due o he loca ion o Liesing, people may
p e e o ei he isi a na u al pa k nea by o use hei p i a e ehicle o access a leisu e acili y
ou side o Vienna.
33
(a) Du a ion by mode o anspo (b) Dis ance by mode o anspo
Figu e 18: Densi y plo o leisu e ip du a ion (a) and dis ance (b) by anspo mode – Liesing
Table 19: Leisu e ip s a is ics by anspo mode - Liesing
T anspo Modes Sample (n)
Du a ion (min)
Dis ance (km)
Mean Median SD Mean Median SD
All Modes
92
34.03
30.0
24.43
10.13
4.7
14.78
Pedes ians 32 41.72 37.5 26.97 2.79 2.0 2.17
Bicycle Insu icien sample size o analysis
Ca (as D i e ) 22 24.68 20.0 14.73 13.27 9.0 14.69
Ca (as Passenge ) Insu icien sample size o analysis
Public T anspo
(a) Du a ion ac oss all modes (b) Du a ion by mode o anspo
(c) Dis ance ac oss all modes (d) Dis ance by mode o anspo
Figu e 19: Cumula i e dis ibu ion unc ion (CDF) o leisu e ip du a ion (a, b) and dis ance (c, d)– Liesing
34
Table 20: Pe cen age o leisu e ips conduc ed o di e en ime s amps – Liesing
T anspo Modes Sha e o ips wi h a du a ion less han (min)
10
15
20
30
All Modes 10.6% 35.1% 42.6% 58.5%
Pedes ians
6.3%
28.1%
28.1%
46.8%
Bicycle Insu icien sample size o analysis
Ca (as D i e )
18.2%
45.5%
54.5%
77.3%
Ca (as Passenge ) Insu icien sample size o analysis
Public T anspo
4.6. T a el beha iou ac oss di e en socioeconomic g oups
The p esen sec ion o he analysis is conce ned wi h an examina ion o modal spli and ip
cha ac e is ics o di e en socioeconomic g oups in Vienna. The main indings o he analysis a e
p esen ed he e, bu he de ailed esul s o he analysis can be ound in Appendix A and G.
4.6.1. Gende
Wo k ips:
Public anspo is he mos u ilised mode o bo h gende s.
Men ha e a ma ginally highe sha e o ca ips compa ed o women.
Women a el sho e dis ances han men bu wi h simila a el imes.
Educa ional ips:
Public anspo is he leading mode o bo h gende s.
T a el pa e ns o educa ion ips a e nea ly iden ical be ween men and women.
Shopping ips:
Walking is he dominan mode o bo h gende s.
Women a e mo e likely o a el as ca passenge s o shopping.
Leisu e ips:
Walking and public anspo a e he wo mos used modes o bo h gende s.
4.6.2. Income
The da ase ca ego izes he economic si ua ion o households as e y poo , poo , a e age, good, and
e y good. Fo he pu pose o he analysis, we ha e been me ged he i s wo ca ego ies ( e y poo and
poo ) in o a single ca ego y called low income, and he las wo ca ego ies (good and e y good) in o a
single ca ego y called high income.
Wo k ips:
Low-income indi iduals ely mo e on public anspo and walking.
High-income indi iduals use ca s mo e equen ly o wo k ips.
T a el imes a e simila , bu low-income indi iduals a el sho e dis ances.
Educa ional ips:
Low-income indi iduals demons a e a g ea e eliance on walking and public anspo .
Ca use is low ac oss all income g oups o educa ion ips.
Shopping ips:
Low-income indi iduals use walking and public anspo mo e equen ly.
High-income indi iduals p e e using ca s o shopping ips.
Walking and public anspo emain p e alen ac oss all income g oups
Leisu e ips:
Low-income indi iduals p e e walking, public anspo , and bicycles.
High-income indi iduals a el longe dis ances and use ca s mo e equen ly o leisu e
ac i i ies.
35
4.6.3. Age
In o de o analyse a el beha iou ac oss age in Vienna, he sample has been di ided in o ou g oups.
The g oups a e he ollowing:
1. Child en/S uden s (up o 18 yea s old)
2. Young adul s (19 o 39 yea s old)
3. Middle-aged adul s (40 o 59 yea s old)
4. Old adul s (o e 60 yea s old)
Wo k ips:
Child en/S uden s alloca e he mos ime o commu ing ye a el sho e dis ances.
Young adul s demons a e a highe p e e ence o ca use, ye hey also u ilize public
anspo and walking.
Middle-aged adul s exhibi a s ong p e e ence o ca use o wo k- ela ed ips.
Fo olde adul s, he ca is he dominan mode o wo k- ela ed ips.
Educa ional ips:
Child en/S uden s ely hea ily on public anspo and walking.
Young and middle-aged adul s a el longe dis ances o educa ion.
Shopping ips:
Walking is he dominan mode ac oss all age g oups.
Young and middle-aged adul s ha e he highes p opo ion o shopping ips made on
oo .
Middle-aged adul s end o a el sligh ly longe dis ances o shopping.
Leisu e ips:
Young adul s exhibi a highe p e e ence o ca use in ela ion o leisu e ips.
Middle-aged adul s alloca e he mos ime o leisu e a el.
Olde adul s demons a e a signi ican ly educed p opensi y o a el o leisu e
ac i i ies.
36
5. UTRECHT
5.1. Gene al cha ac e is ics o U ech and LL loca ion
The Municipali y o U ech is loca ed in he P o ince o U ech , which is one o he 12 p o inces ha
cons i u e he Ne he lands. The ci y o U ech is he ou h mos populous ci y in he Ne he lands, wi h
an es ima ed popula ion o app oxima ely 375,000 inhabi an s. The ci y's epu a ion is la gely buil on
i s ex ensi e cycling in as uc u e and public anspo sys em, o e ing seamless connec ions o all
majo ci ies and owns in he coun y.
U ech ’s Li ing Lab is “O e ech Noo d” and is loca ed in he No heas o U ech . The a ea has a
popula ion o app oxima ely 35,000 inhabi an s, and i is se ed by he local public anspo sys em. In
addi ion, i o e s a wide ange o cycling- ela ed se ices.
Figu e 20 shows he map o U ech and he loca ion o he U ech Li ing Lab “O e ech ” (o ange do ).
Figu e 20: Loca ion o he U ech Li ing Lab “O e ech ” (o ange do ) (Sou ce: OSM (2024))
37
5.2. Desc ip i e s a is ical analysis
Fo he desc ip i e s a is ical analysis o he ci y o U ech and U ech ’s LL loca ion, he da ase
“Onde weg in Nede land 2021 (ODiN)” (5) was used. A lis o socioeconomic a iables, bo h o
households and indi iduals, was selec ed and p esen ed in Tables Table 21 and Table 22 espec i ely.
I is impo an o acknowledge he limi a ions imposed by he ela i ely modes sample size o ips
conduc ed by he esiden s o he "O e ech Noo d" egion. This es ic s he scope and gene alisabili y
o he analysis' esul s. To mi iga e hese limi a ions, a comp ehensi e analysis o he en i e O e ech
a ea is conduc ed, encompassing bo h he no he n and sou he n egion.
The sample used o his pa o he analysis is he o al esiden popula ion wi hin he a ea (U ech o
O e ech ), wi h no il e ing o speci ic ip pu poses. Fu he mo e, he sample o su ey esponden s
who did no p o ide a alid esponse o one o mo e o he selec ed ques ions was excluded om he
sample.
Table 21: Socioeconomic cha ac e is ics o households (U ech & O e ech ) – Sou ce: ODiN 2021
Socioeconomic Cha ac e is ics o Households
U ech
LL Loca ion
(
O e ech
)
n
%
n
%
Household size
1 Pe son
1
302
17.2
48
30.8
2 Pe sons
2
587
34.1
49
31.4
3 Pe sons 1074 14.2 17 10.9
4+ Pe sons
2615
34.5
42
26.9
Ca
owne ship
0
1178
15.5
59
37.8
1 3653 48.2 75 48.1
2
2145
28.3
18
11.5
3
449
5.9
3
1.9
4+ 153 2.0 1 0.6
Numbe o ca d i ing license pe household
0
425
5.6
28
17.9
1
1920
25.4
56
35.9
2 4398 58.0 63 40.4
3
605
8.0
5
3.2
4+
230
3.0
4
2.6
Table 22: Socioeconomic cha ac e is ics o indi iduals (U ech & O e ech ) – Sou ce: ODiN 2021
Socioeconomic Cha ac e is ics o Indi iduals
U ech
LL Loca ion (
O e ech
)
n
%
n
%
Gende
Male
3750
49.5
85
54.5
Female
3828
50.5
71
45.5
Age Ca ego y (y.o.)
6 – 14 775 10.2 12 7.7
15
–
19
461
6.1
9
5.8
20
–
24
486
6.4
12
7.7
25 – 34 1323 17.5 48 30.8
35
–
44
1070
14.1
23
14.7
45
–
54
1202
15.9
18
11.5
55
–
64
903
11.9
14
9.0
65+
1358
17.9
20
12.8
Occupa ion
S uden
1558
20.6
31
19.9
Employed
4126
54.4
82
52.6
Pensione
1184
15.6
18
11.5
O he
710
9.4
25
16.0
38
The desc ip i e s a is ical analysis o e s a de ailed o e iew o he demog aphic p o iles o esiden s
in U ech and O e ech egion. Wi h espec o gende , he popula ion in he sample is almos equally
dis ibu ed in U ech , in O e ech howe e , he sample o men is la ge han ha o women by 10%.
Fu he mo e, a signi ican dispa i y is obse ed in he owne ship o ehicles be ween he wo a eas.
While he majo i y o households in U ech possess a leas one ca , in O e ech , he p opo ion o
households wi hou ca s is highe . Rega ding occupa ion, bo h samples a e p edominan ly comp ised
o employed indi iduals and s uden s.
5.3. Modal spli
As illus a ed in Figu e 21, he modal spli by ip pu pose o he ci y o U ech e eals dis inc pa e ns
in anspo a ion choices. Fo commu ing o wo k, d i ing is he mos p e e ed mode o U ech
esiden s, ollowed by cycling. When i comes o educa ional ips, cycling s ands as he clea a ou i e.
As o shopping ips, cycling is he dominan mode, bu he e is also a high sha e o ips made by oo
o ca . Wi h espec o leisu e ips, he e walking eme ges as he p edominan mode wi h 43%, ollowed
by bicycle and ca usage. I is impo an o be no ed ha in he leisu e ips ca ego y a e included
walking ips o ec ea ion, so his migh s ongly a ec modal spli . Fu he mo e, he indings indica e
ha public anspo a ion is ema kably unde u ilized o daily a el in U ech .
Figu e 21: Modal spli by ip pu pose – U ech
The esul s o he modal spli analysis in O e ech , p esen ed in Figu e 22, indica e a p e e ence o
cycling and walking, pa icula ly o shopping and leisu e ips. Con e sely, commu es a e
p edominan ly pe o med by ca and bicycle, mi o ing he modal spli obse ed in U ech . Cycling
eme ges as he p edominan mode o educa ional ips, ollowed by public anspo a ion. Howe e ,
he small sample size o he O e ech a ea may impac he ep esen a i eness o he esul s. This
limi a ion is also e lec ed in he e o ba s shown in he plo s.
39
Figu e 22: Modal spli by ip pu pose - O e ech
5.4. T ip Cha ac e is ics – U ech
5.4.1. Wo k ips
The mean du a ion o a wo k ip in U ech is app oxima ely 26 minu es, wi h an a e age dis ance o
15 kilome es. As indica ed in Table 24, nea ly 41% o he wo k ips in U ech a e comple ed in less
han 15 minu es. D i ing is he mos p e alen a el mode o wo k- ela ed ips, wi h an a e age
du a ion o 27 minu es, while only 30% o hese ips a e comple ed in unde 15 minu es. This migh be
a ibu ed o he ac ha a high sha e o wo k acili ies is no loca ed in he ci y cen e, necessi a ing
longe commu es. Cycling is also a popula ip mode o wo k ips, wi h an a e age du a ion o 20
minu es, and app oxima ely 57% o hese commu es las ing up o 15 minu es. In he case o public
anspo commu es, he a e age du a ion is close o 56 minu es, wi h nea ly 3% o hese ips a e
comple ed in less han 15 minu es. Finally, he a el mode wi h he highes p opo ion o comple ed
ips in less han 15 minu es is walking (82.3%).
(a) Du a ion by mode o anspo
(b) Dis ance by mode o anspo
Figu e 23: Densi y plo o wo k ip du a ion (a) and dis ance (b) by anspo mode – U ech
40
Table 23: Wo k ip s a is ics by anspo mode - U ech
T anspo Modes Sample (n) Du a ion (min) Dis ance (km)
Mean Median SD Mean Median SD
All Modes 2579 26.01 20.00 22.52 15.29 8.00 18.56
Pedes ians 130 11.18 5.00 12.44 0.94 0.55 1.20
Bicycle 913 20.04 15.00 19.78 4.65 3.40 4.26
Ca (as D i e ) 1266 27.31 25.00 21.01 22.20 17.00 20.47
Ca (as Passenge ) 77 26.47 20.00 17.36 16.23 12.00 16.96
Public T anspo 193 55.50 50.00 24.87 29.62 23.60 21.58
(a)
Du a ion ac oss all modes
(b) Du a ion by mode o anspo
(c) Dis ance ac oss all modes (d) Dis ance by mode o anspo
Figu e 24: Cumula i e dis ibu ion unc ion (CDF) o wo k ip du a ion (a, b) and dis ance (c, d)– U ech
Table 24: Pe cen age o wo k ips conduc ed o di e en ime s amps – U ech
T anspo Modes Sha e o ips wi h a du a ion less han (min)
10
15
20
30
All Modes 23.3% 40.5% 52.2% 75.8%
Pedes ians 70.0% 82.3% 89.2% 95.4%
Bicycle
34.5%
56.7%
68.2%
85.4%
Ca (as D i e ) 14.6% 30.9% 44.2% 75.6%
Ca (as Passenge ) 13.0% 31.2% 51.9% 81.8%
Public T anspo 0.5% 2.6% 4.1% 15.5%
41
5.4.2. Educa ional ips
In U ech , he a e age du a ion o he educa ional ips is close o 22 minu es and he mos p e alen
a el mode o his ca ego y is cycling. Cycling ips las on a e age 18 minu es and mo e han 60% o
hese ips a e comple ed in less han 15 minu es. Acco ding o Table 25, modes such as public anspo
and ca a e p e e ed o longe ips o educa ional ins i u ions, while he sha e o ips o less han 15
minu es is 3.5% and 21% espec i ely. Mo eo e , walking is he mode wi h he highes sha e o ips
comple ed up o 15 minu es. O e all, he esul s show a high deg ee o p oximi y o educa ional
ins i u ions a ac ha allows he use o sus ainable modes such as walking and cycling.
(a) Du a ion by mode o anspo
(b) Dis ance by mode o anspo
Figu e 25: Densi y plo o educa ional ip du a ion (a) and dis ance (b) by anspo mode – U ech
Table 25: Educa ional ip s a is ics by anspo mode - U ech
T anspo Modes Sample (n)
Du a ion (min)
Dis ance (km)
Mean Median SD Mean Median SD
All Modes
1208
21.58
15.00
23.02
6.99
2.50
12.53
Pedes ians 155 8.97 5.00 7.94 0.77 0.50 0.87
Bicycle
755
17.69
15.00
19.10
3.38
2.30
3.20
Ca (as D i e ) 55 31.02 25.00 20.77 21.64 14.00 21.59
Ca (as Passenge )
106
17.74
13.50
15.67
8.05
3.05
11.58
Public T anspo 137 56.47 54.00 26.66 27.25 21.50 20.74
48
(a) Du a ion ac oss all modes (b) Du a ion by mode o anspo
(c) Dis ance ac oss all
modes
(d) Dis ance by mode o anspo
Figu e 34: Cumula i e dis ibu ion unc ion (CDF) o shopping ip du a ion (a, b) and dis ance (c, d)– O e ech
Table 34: Pe cen age o shopping ips conduc ed o di e en ime s amps – O e ech
T anspo Modes Sha e o ips wi h a du a ion less han (min)
10 15 20 30
All Modes 62.8% 81.9% 89.4% 97.9%
Pedes ians 73.3% 88.9% 93.3% 97.8%
Bicycle 74.1% 77.8% 88.9% 88.9%
Ca (as D i e )
Insu icien sample size o analysis Ca (as Passenge )
Public T anspo
5.5.4. Leisu e ips
The mean du a ion o a leisu e ip in O e ech is app oxima ely 53 minu es, while he mean dis ance
is almos 10 kilome es. Walking is again he p e alen mode o leisu e ips, ollowed by cycling. A
leisu e ip made by oo las s on a e age 57 minu es, while ips made by bicycle a e sho e in du a ion
bu sligh ly longe in dis ance. Hal o he leisu e ips made by bicycle las up o 15 minu es, whe eas
o walking ips his pe cen age is ela i ely low (22%). I is no ewo hy, ha his ip pu pose ca ego y
includes ips o ei he social ec ea ion o ec ea ional walking, which migh cause longe ips. In
gene al, ewe leisu e ips in O e ech a e comple ed in less han 15 minu es (32.5%) han in U ech
as a whole (43%).
49
(a) Du a ion by mode o anspo
(b) Dis ance by mode o anspo
Figu e 35: Densi y plo o leisu e ip du a ion (a) and dis ance (b) by anspo mode – O e ech
Table 35: Leisu e ip s a is ics by anspo mode - O e ech
T anspo Modes Sample (n)
Du a ion (min)
Dis ance (km)
Mean Median SD Mean Median SD
All Modes 120 53.87 30.0 67.1 9.51 3.5 20.97
Pedes ians
63
57.29
45.0
64.63
3.56
2.0
3.52
Bicycle 28 42.86 17.5 61.8 4.88 2.95 4.44
Ca (as D i e )
Insu icien sample size o analysis Ca (as Passenge )
Public T anspo
(a) Du a ion ac oss all modes
(b)
Du a ion by mode o anspo
(c) Dis ance ac oss all modes
(d) Dis ance by mode o anspo
Figu e 36: Cumula i e dis ibu ion unc ion (CDF) o leisu e ip du a ion (a, b) and dis ance (c, d)– O e ech
50
Table 36: Pe cen age o leisu e ips conduc ed o di e en ime s amps – O e ech
T anspo Modes Sha e o ips wi h a du a ion less han (min)
10
15
20
30
All Modes 17.5% 32.5% 40.0% 55.0%
Pedes ians
17.5%
22.2%
31.8%
46.0%
Bicycle 17.9% 50.0% 57.1% 67.9%
Ca (as D i e )
Insu icien sample size o analysis Ca (as Passenge )
Public T anspo
5.6. T a el beha iou ac oss di e en socioeconomic g oups
The p esen sec ion o he analysis is conce ned wi h an examina ion o modal spli and ip
cha ac e is ics o di e en socioeconomic g oups in U ech . The main indings o he analysis a e
p esen ed he e, bu he de ailed esul s o he analysis can be ound in Appendix B and G.
5.6.1. Gende
Wo k ips:
Men a el signi ican ly longe dis ances han women o wo k- ela ed ips, despi e
simila a el imes, and use hei ca s mo e.
Women cycle o wo k mo e han men.
Educa ional ips:
Bo h sexes a el simila dis ances, p obably due o he p oximi y o educa ional
ins i u ions.
Men cycle and walk sligh ly mo e han women o educa ional ips.
Women a e mo e likely o use public anspo o educa ion.
Shopping ips:
T a el imes and dis ances a e simila o bo h sexes.
Men a e mo e likely han women o use a ca o shopping, while women a e mo e likely
o use a bicycle.
Walking is a popula mode o anspo o shopping ips.
Leisu e ips:
Men and women spend oughly he same amoun o ime and co e simila dis ances on
leisu e ips.
Walking is he dominan mode o anspo o leisu e ips o bo h sexes.
Men a e mo e likely han women o cycle and d i e o leisu e ips.
5.6.2. Income
The da ase ca ego izes he economic si ua ion o households in U ech based on he s anda dised
disposable income o he household (10% g oups). In he Ne he lands, households a e de ided by
income le el in o en g oups (deciles) wi h an equal numbe o households. The income limi s be ween
hese 10% g oups a y om yea o yea .
(h ps://openda a.cbs.nl/s a line/?dl=D4D1#/CBS/nl/da ase /83931NED/ able ). Fo he pu pose o
he analysis, we ha e been me ged he i s i e g oups ( i s 10% g oup – i h 10% g oup) in o a single
ca ego y called low income, and he las i e g oups (six h 10% g oup – en h 10% g oup) in o a single
ca ego y called high income.
Wo k ips:
High income a elle s co e longe dis ances o wo k- ela ed ips.
High-income indi iduals p edominan ly op o ca , low-income indi iduals
demons a e a highe p e e ence o bicycles.
Educa ional ips:
The mean ip dis ance o educa ional pu poses is ound o be simila ac oss di e en
income g oups.
51
Bicycle is he mos u ilised a el mode ac oss bo h income g oups.
Public anspo usage is sligh ly highe o low-income indi iduals compa ed o high-
income indi iduals.
Shopping ips:
High-income indi iduals a el signi ican ly longe dis ances han low-income
indi iduals.
Low-income indi iduals usually walk o cycle o hei shopping ips, while high-
income indi iduals use hei ca and bicycle.
Leisu e ips:
Indi iduals o a lowe socio-economic s a us end o unde ake signi ican ly longe
jou neys o engage in leisu e ac i i ies in compa ison o hei high-income coun e pa s.
The e a e no no able di e ences in e ms o modal spli ac oss he wo income g oups.
5.6.3. Age
In o de o analyse a el beha iou ac oss age in U ech , he sample has been di ided in o ou g oups.
The g oups a e he ollowing:
1. Child en/S uden s (up o 18 yea s old)
2. Young adul s (19 o 39 yea s old)
3. Middle-aged adul s (40 o 59 yea s old)
4. Old adul s (o e 60 yea s old)
Wo k ips:
Child en/S uden s a el he leas o wo k.
Middle-aged adul s and old adul s a el sho e dis ances and less ime han young
adul s.
The bicycle is he p edominan mode o wo k ips unde aken by child en/s uden s,
while olde adul s a e mo e likely o use he ca .
Educa ional ips:
Young adul s a el he longes and a hes o educa ion- ela ed ips.
Young adul s use public anspo mo e han indi iduals in o he age g oups.
Shopping ips:
Child en/S uden s ha e he highes a el ime and he longes dis ance.
Olde age g oups ha e simila a el imes and dis ances.
Young adul s like o walk mo e when hey go shopping. People in o he age g oups end
o use ca s and bicycles mo e.
Leisu e ips:
Child en/S uden s spend mo e ime a eling bu co e sho e dis ances.
The p edominan mode o anspo a ion o leisu e ips among age g oups 1, 2, and 3
is walking. Fo child en and s uden s, he p edominan mode o anspo a ion is bicycle.
52
6. BRUSSELS
6.1. Gene al cha ac e is ics o B ussels and LL loca ion
The B ussels Capi al Region (he ea e , B ussels) is one o h ee Regions o Belgium, he o he s being
Flande s and Wallonia. I is comp ised o 19 municipali ies and has a popula ion o o e 1.2 million
inhabi an s. I is loca ed a he co e o he Belgian anspo ne wo k, o e ing nume ous highways and
ailways o connec ions wi h o he Eu opean ci ies. Mo eo e , B ussels boas s an ex ensi e public
anspo in as uc u e, comp ising unde g ound lines, ams, buses and bicycle in as uc u e.
Addi ionally, he ci y o e s ca , mic omobili y and ca go bike sha ing se ices, he eby p omo ing
sus ainable u ban mobili y op ions.
The Li ing Labs o B ussels a e loca ed in wo pe iphe al neighbo hoods in he no he n pa o
B ussels, namely Nede -o e -Heembeek and Ha en. Adminis a i ely, hey a e pa o he municipali y
o he Ci y o B ussels, bu hey a e loca ed on he no he n pe iphe y o he egion, ex ending beyond
he immedia e cen al zone. Access o hese Li ing Labs is acili a ed by he local public anspo
sys em, p edominan ly h ough bus se ices. Finally, hey o e limi ed ca and mic omobili y sha ing
se ices.
Figu e 37 shows he map o B ussels and he loca ion o he Li ing Labs “Nede -o e -Heembeek” and
“Ha en” ( ed pins)
Figu e 37: Loca ion o he Ci y o B ussels dis ic (o ange line) and he B ussels’ Li ing Lab ( ed pins) (Sou ce: OSM (2024))
53
6.2. Desc ip i e s a is ical analysis
Fo he desc ip i e s a is ical analysis o B ussels Capi al Region (he ea e , B ussels) and he LL
loca ion, he da ase “Onde zoek Ve plaa singsged ag (OVG) 2021” (6) was used. A lis o socioeconomic
a iables, bo h o households and indi iduals, was selec ed and p esen ed in Tables Table 37 and Table
38 espec i ely.
I is impo an o acknowledge he limi a ions imposed by he ela i ely modes sample size o ips
unde aken by he esiden s o he “Nede -o e -Heembeek” and “Ha en” egions. This es ic s he
scope and gene alisabili y o he analysis' esul s. To add ess hese limi a ions, a comp ehensi e
analysis o he en i e municipali y Ci y o B ussels (he ea e , B ussels Ci y) is conduc ed.
The sample used o his pa o he analysis is he o al esiden popula ion wi hin he a ea (B ussels o
B ussels Ci y), wi h no il e ing o speci ic ip pu poses. Fu he mo e, he sample o su ey
esponden s who did no p o ide a alid esponse o one o mo e o he selec ed ques ions was excluded
om he sample.
Table 37 Socioeconomic cha ac e is ics o households (B ussels & B ussels Ci y) – Sou ce: OVG 2021
Socioeconomic Cha ac e is ics o Households
B ussels LL Loca ion (B ussels Ci y)
n % n %
Household size
1 Pe son
557
20.7
84
23.9
2 Pe sons
673
25.1
87
24.7
3 Pe sons
442
16.5
50
14.2
4 Pe sons
507
18.9
59
16.8
5+ Pe sons
506
18.8
72
20.5
Ca owne ship
0
914
34
128
36.4
1
1367
50.9
187
53.1
2
360
13.4
35
9.9
3
33
1.2
2
0.6
4+ 11 0.4 - -0
Table 38: Socioeconomic cha ac e is ics o indi iduals (B ussels & B ussels Ci y) – Sou ce: OVG 2021
Socioeconomic Cha ac e is ics o Indi iduals
B ussels
LL
Loca ion (B ussels Ci y)
N
%
n
%
Gende
Male
1234
46.1
179
51.3
Female 1443 53.9 170 48.7
Age Ca ego y (y.o.)
6
–
11
259
9.6
36
10.2
12
–
17
232
8.6
26
7.4
18 – 24
201 7.5 23 6.5
25
–
34
460
17.1
80
22.7
35
–
44
440
16.4
70
19.9
45 – 54 380 14.2 45 12.8
55
–
64
304
11.3
37
10.5
65+
409
15.2
35
9.9
The desc ip i e s a is ical analysis p o ides a aluable pe spec i e on he demog aphic cha ac e is ics
o he B ussels and B ussels Ci y popula ions. Wi h espec o ca owne ship, he majo i y o households
in bo h egions possess a leas one ca . The B ussels sample e eals a sligh p eponde ance o emale
ep esen a ion, while he B ussels Ci y sample shows a mo e balanced gende dis ibu ion, wi h males
and emales ep esen ed equally. Wi h espec o age, indi iduals olde han 25 yea s old a e mo e
ep esen ed in he sample o bo h egions. Howe e , he OVG su ey lacks a iables ela ed o
occupa ion ype and income, a limi a ion ha would enhance he esul s.
54
6.3. Modal spli
Figu e 38 illus a es he modal spli by ip pu pose o B ussels. Fo commu e s, public anspo a ion
is he p edominan mode o anspo a ion, ollowed by walking and d i ing. Fo educa ional- ela ed
ips, public anspo a ion eme ges as he p edominan mode o anspo a ion, ollowed by walking.
Con e sely, shopping ips a e p edominan ly unde aken by walking, hough ca use and public
anspo a ion also eme ge as popula modes. In ega d o leisu e ips, walking eme ges as he
p edominan mode. The analysis indica es a p e e ence among B ussels esiden s o walking and public
anspo a ion when unde aking daily commu es. Addi ionally, bicycle usage is no as p e alen in
B ussels.
Figu e 38: Modal spli by ip pu pose – B ussels
An analysis o he modal spli in he B ussels Ci y a ea e eals ha he e a e no no able dispa i ies when
compa ed wi h he modal spli o B ussels i sel . Acco ding o he esul s illus a ed in Figu e 39,
walking and public anspo a e he dominan modes o all ip ca ego ies, while he u ilisa ion o
bicycles emains low in p e e ence. Howe e , a decline in ca usage is e iden o wo k- and shopping-
ela ed ips, sugges ing ha he esiden s o he B ussels Ci y a ea a e able o sa is y hei daily needs
h ough he u ilisa ion o mo e sus ainable anspo a ion modes.
55
Figu e 39: Modal spli by ip pu pose – B ussels Ci y
6.4. T ip Cha ac e is ics – B ussels
6.4.1. Wo k ips
The a e age commu e in B ussels las s 26 minu es and is 8.5 kilome es long. Table 40 shows ha
almos 36% o he commu es in B ussels a e made in less han 15 minu es. Public anspo is he mos
used a el mode o commu ing, wi h an a e age commu e ime o 40 minu es, while only 5% o hese
commu es a e comple ed in 15 minu es. Walking is also a popula ip mode o commu ing o wo k,
wi h an a e age du a ion o 11 minu es, and app oxima ely 80% o hese commu es las up o 15
minu es. Fo ca ips, he a e age du a ion is app oxima ely 28 minu es, wi h nea ly 24% o hese ips
las ing up o 15 minu es. This migh be a ibu ed o he ac ha a high sha e o wo k acili ies is no
loca ed in he ci y cen e, equi ing longe commu es.
(a) Du a ion by mode o anspo (b) Dis ance by mode o anspo
Figu e 40: Densi y plo o wo k ip du a ion (a) and dis ance (b) by anspo mode – B ussels
56
Table 39: Wo k ip s a is ics by anspo mode - B ussels
T anspo Modes Sample (n) Du a ion (min) Dis ance (km)
Mean Median SD Mean Median SD
All Modes 604 26.07 21.0 20.86 8.51 4.5 17.65
Pedes ians 155 11.12 10.0 8.86 0.81 0.6 0.71
Bicycle 93 18.58 15.0 11.32 4.70 3.5 3.75
Ca (as D i e ) 144 27.67 24.0 23.38 17.09 9.0 30.07
Ca (as Passenge ) Insu icien sample size o analysis
Public T anspo 202 39.56 36.0 19.97 9.28 6.3 11.90
(a) Du a ion ac oss all modes (b) Du a ion by mode o anspo
(c) Dis ance ac oss all modes (d) Dis ance by mode o anspo
Figu e 41: Cumula i e dis ibu ion unc ion (CDF) o wo k ip du a ion (a, b) and dis ance (c, d)– B ussels
Table 40: Pe cen age o wo k ips conduc ed o di e en ime s amps – B ussels
T anspo Modes
Sha e o ips wi h a du a ion less han (min)
10 15 20 30
All Modes
23.5%
35.9%
49.5%
68.5%
Pedes ians 63.9% 79.4% 89.0% 98.1%
Bicycle
28.0%
51.6%
72.0%
86.0%
Ca (as D i e ) 9.7% 23.6% 44.4% 72.9%
Ca (as Passenge )
Insu icien sample size o analysis
Public T anspo 1.0% 5.0% 13.4% 34.7%
6.4.2. Educa ional ips
On a e age, educa ional ips in B ussels las app oxima ely 24 minu es and a e 5.4 kilome es long. In
his ip pu pose ca ego y, almos 50 pe cen o ips las up o 15 minu es, sugges ing a a he high
le el o p oximi y o all ypes o educa ional ins i u ions. Public anspo is he mos used mode,
ollowed by walking. Public anspo ips ha e an a e age du a ion o 39.2 minu es, while only 10%
comple ed wi hin 15 minu es. Walking ips o educa ional ins i u ions las on a e age 11 minu es and
81.5% a e comple ed wi hin 15 minu es. This unde sco es he accessibili y o nea by educa ional
ins i u ions o pedes ians. Cycling ips a e simila o walking ips in e ms o du a ion, al hough hey
co e longe dis ances.
57
(a) Du a ion by mode o anspo
(b) Dis ance by mode o anspo
Figu e 42: Densi y plo o educa ional ip du a ion (a) and dis ance (b) by anspo mode – B ussels
Table 41: Educa ional ip s a is ics by anspo mode - B ussels
T anspo Modes Sample (n)
Du a ion (min)
Dis ance (km)
Mean Median SD Mean Median SD
All Modes 353 24.2 17.0 22.43 5.44 2.2 16.58
Pedes ians 119 11.2 10.0 7.63 0.82 0.7 0.72
Bicycle 29 11.3 10.0 7.43 2.09 1.6 1.72
Ca (as D i e ) Insu icien sample size o analysis
Ca (as Passenge ) 54 18.1 15.0 12.84 3.78 2.5 3.74
Public T anspo
142
39.2
36.0
23.12
10.10
5.2
24.76
(a) Du a ion ac oss all modes (b) Du a ion by mode o anspo
(c) Dis ance ac oss all modes (d) Dis ance by mode o anspo
Figu e 43: Cumula i e dis ibu ion unc ion (CDF) o educa ional ip du a ion (a, b) and dis ance (c, d)– B ussels
64
(a) Du a ion by mode o anspo
(b) Dis ance by mode o anspo
Figu e 52: Densi y plo o shopping ip du a ion (a) and dis ance (b) by anspo mode – B ussels Ci y
Table 51: Shopping ip s a is ics by anspo mode – B ussels Ci y
T anspo Modes Sample (n)
Du a ion (min)
Dis ance (km)
Mean Median SD Mean Median SD
All Modes 121 16.65 12.0 13.81 2.87 1.0 5.01
Pedes ians 76 12.04 10.0 10.84 0.86 0.6 0.83
Bicycle
Insu icien sample size o analysis Ca (as D i e )
Ca (as Passenge )
Public T anspo
21
30.14
30.0
10.31
5.28
3.2
3.78
(a) Du a ion ac oss all modes
(b) Du a ion by mode o
anspo
(c) Dis ance ac oss all modes (d) Dis ance by mode o anspo
Figu e 53: Cumula i e dis ibu ion unc ion (CDF) o shopping ip du a ion (a, b) and dis ance (c, d)– B ussels Ci y
65
Table 52: Pe cen age o shopping ips conduc ed o di e en ime s amps – B ussels Ci y
T anspo Modes Sha e o ips wi h a du a ion less han (min)
10 15 20 30
All Modes 48.8% 60.3% 71.1% 86.8%
Pedes ians 63.2% 80.3% 88.2% 94.7%
Bicycle
Insu icien sample size o analysis Ca (as D i e )
Ca (as Passenge )
Public T anspo - 4.8% 14.3% 57.1%
6.5.4. Leisu e ips
The du a ion o leisu e ips in B ussels Ci y las on a e age 27 minu es, while acco ding o Table 54,
42% o hem a e comple ed wi hin 15 minu es. The mos equen ly u ilised mode o anspo a ion o
his pu pose is walking, wi h an a e age du a ion o 20 minu es and a dis ance co e ed o 1.3 kilome es.
In compa ison o leisu e ips unde aken by oo in B ussels, hose in his a ea a e sho e on a e age,
indica ing a high le el o accessibili y o leisu e acili ies in he a ea. Un o una ely, he indings o he
analysis a e limi ed due o an inadequa e sample size.
(a) Du a ion by mode o anspo (b) Dis ance by mode o anspo
Figu e 54: Densi y plo o leisu e ip du a ion (a) and dis ance (b) by anspo mode – B ussels Ci y
Table 53: Leisu e ip s a is ics by anspo mode – B ussels Ci y
T anspo Modes Sample (n) Du a ion (min) Dis ance (km)
Mean
Median
SD
Mean
Median
SD
All Modes 107 26.93 20.0 24.99 7.26 1.9 17.71
Pedes ians
60
20.37
12.0
23.56
1.28
0.8
1.62
Bicycle
Insu icien sample size o analysis
Ca (as D i e )
Ca (as Passenge )
Public
T anspo
66
(a) Du a ion ac oss all modes (b) Du a ion by mode o anspo
(c) Dis ance ac oss all modes
(d) Dis ance by mode o anspo
Figu e 55: Cumula i e dis ibu ion unc ion (CDF) o leisu e ip du a ion (a, b) and dis ance (c, d)– B ussels Ci y
Table 54: Pe cen age o leisu e ips conduc ed o di e en ime s amps – B ussels Ci y
T anspo Modes Sha e o ips wi h a du a ion less han (min)
10 15 20 30
All
Modes
29.9%
42.1%
54.2%
73.8%
Pedes ians 46.7% 61.7% 71.7% 85.0%
Bicycle
Insu icien sample size o analysis
Ca (as D i e )
Ca (as Passenge )
Public T anspo
6.6. T a el beha iou ac oss di e en socioeconomic g oups
The p esen sec ion o he analysis is conce ned wi h an examina ion o modal spli and ip
cha ac e is ics o di e en socioeconomic g oups in B ussels. The main indings o he analysis a e
p esen ed he e, bu he de ailed esul s o he analysis can be ound in Appendix C and G.
6.6.1. Gende
Wo k, educa ion, and shopping ips show no signi ican gende di e ences in a el beha iou .
Leisu e ips a e signi ican ly longe o males, bo h in e ms o dis ance and ime a elled.
Women ely mo e on public anspo ac oss all ip pu poses compa ed o men.
Men use bicycles mo e han women, especially o leisu e and shopping ips.
Ca mode is mo e dominan among men o wo k and shopping ips.
Pedes ian a el is sligh ly mo e common among women, especially o educa ion and leisu e
ips.
6.6.2. Age
In o de o analyse a el beha iou by age in B ussels, he sample has been di ided in o ou age g oups.
The age dis ibu ion in each g oup is di e s sligh ly om he one used o he o he ci ies. This is due o
67
he ac ha he da ase is al eady ca ego ising he esponden s in hese g oups. The g oups a e he
ollowing:
1. Child en/S uden s (up o 17 yea s old)
2. Young adul s (18 o 34 yea s old)
3. Middle-aged adul s (35 o 64 yea s old)
4. Old adul s (o e 65 yea s old)
Educa ion ips show he s onges a ia ion ac oss age g oups, wi h young adul s a eling
signi ican ly longe dis ances.
Leisu e ips a e signi ican ly longe o olde adul s, indica ing a shi in a el pa e ns.
Wo k and shopping ips show no signi ican a ia ion ac oss age g oups.
Va iabili y in a el imes inc eases wi h age, especially o educa ion and leisu e ips.
68
7. BUDAPEST
7.1. Gene al cha ac e is ics o Budapes and LL loca ion
Budapes is he capi al o Hunga y and consis s o 23 dis ic s. Wi h app oxima ely 1.685 million
inhabi an s (7), i is he la ges ci y in Hunga y. Budapes has an e icien and public anspo ne wo k
ha includes unde g ound lines, am, olleybuses, and subu ban ailway lines. I also o e s ca and
mic omobili y sha ing se ices.
The Budapes Li ing Lab is loca ed in he 17 h dis ic o Budapes called Rákosmen e. Rákosmen e is a
subu ban dis ic o Budapes in he eas e n pa o he ci y, and has a popula ion o abou 90,000
ihabi an s. In Rákosmen e, people ely hea ily on p i a e ca use, while he equency o public anspo
is low.
Figu e 56 shows he map o Budapes and he loca ion o he Rákosmen e dis ic .
Figu e 56: Loca ion o he Rákosmen e dis ic (o ange line) (Sou ce: OSM (2024))
7.2. Desc ip i e s a is ical analysis
Fo he desc ip i e s a is ical analysis o he ci y o Budapes and he Budapes ’s LL egion he da ase
“Household Su ey o Uni ied Mac oscopic T anspo Model 2019” (8) was used. A lis o
socioeconomic a iables, bo h o households and indi iduals, was selec ed and p esen ed in Tables
Table 55 and Table 56 espec i ely.
I is impo an o acknowledge he limi a ions imposed by he ela i ely modes sample size o ips
made by esiden s o he Rákosmen e egion. This limi s he scope and gene alisabili y o he esul s o
he analysis. In o de o add ess hese limi a ions, a comp ehensi e analysis o he 16 h and 17 h
dis ic s is ca ied ou . The 16 h dis ic o Budapes is loca ed nex o he 17 h dis ic o Budapes
(Rákosmen e) and sha es common socio-economic and a el cha ac e is ics.
The sample used o his pa o he analysis is he o al esiden popula ion wi hin he a ea (Budapes
o Budapes ’s LL egion), wi h no il e ing o speci ic ip pu poses. Fu he mo e, he sample o su ey
69
esponden s who did no p o ide a alid esponse o one o mo e o he selec ed ques ions was excluded
om he sample.
Table 55: Socioeconomic cha ac e is ics o households (Budapes & Budapes LL loca ion) – Sou ce: HSUMTM 2019
Socioeconomic Cha ac e is ics o Households
Budapes
LL Loca ion (16
h
& 17
h
Dis ic )
n
%
n
%
Household size
1 Pe son
1307
38
101
28.5
2 Pe sons 988 28.7 100 28.2
3 Pe sons
604
17.6
77
21.7
4+ Pe sons
540
15.7
77
21.7
Economic si ua ion
Less han 50.000 F 19 0.8 14 4.5
50.001
-
100.000 F
163
7
17
5.5
100.001
-
150.000 F
647
27.9
54
17.4
150.001 - 250.000 F 982 42.3 185 59.5
250.001
-
350.000 F
338
14.6
31
10
350.001
-
450.000 F
108
4.7
8
2.6
Mo e han 450.000 F 64 2.8 2 0.6
Ca owne ship
0
1240
36.1
171
48.2
1
1781
51.8
162
45.6
2 396 11.5 21 5.9
3
19
0.6
1
0.3
Bike a ailabili y
0
2047
59.5
242
68.2
1 814 23.7 58 16.3
2
380
11.0
27
7.6
3
124
3.6
14
3.9
3+
74
2.2
14
3.9
Table 56: Socioeconomic cha ac e is ics o indi iduals (Budapes & Budapes LL loca ion) – Sou ce: HSUMTUM 2019
Socioeconomic Cha ac e is ics o Indi iduals
Budapes
LL Loca ion (16
h
& 17
h
Dis ic )
n
%
n
%
Gende
Male
2123
61.7
242
68.2
Female
1316
38.3
113
31.8
Age Ca ego y (y.o.)
6
–
14
-
-
-
-
15
–
19
10
0.3
-
-
20
–
24
106
3.1
1
0.3
25
–
34
563
16.4
29
8.2
35
–
44
783
22.8
73
20.6
45
–
54
795
23.1
74
20.8
55 – 64 543 15.8 82 23.1
65+
639
18.6
96
27
Occupa ion
Employed
2733
79.5
321
90.4
S uden - - - -
Pensione
675
19.6
34
9.6
O he
31
0.9
-
-
Ca D i ing License
No 1035 30.1 160 45.1
Yes
2404
69.9
195
54.9
The desc ip i e s a is ical analysis p o ides a de ailed o e iew o he demog aphic p o ile o esiden s
in Budapes and he Budapes LL egion. Wi h espec o gende , males a e o e ep esen ed in he
sample. Howe e , i is e iden ha he gende dis ibu ion wi hin he sample de ia es om he o icial
s a is ics o Budapes . Acco ding o he s a is ics p o ided by he Hunga ian Cen al S a is ical O ice (9)
o he yea o 2019, males ep esen ed 47% o he o al popula ion o Budapes . Wi h ega d o age, he
sample is p edominan ly composed o indi iduals o e he age o 25, and especially o people in he age
g oup 34 o 54 yea s old. n ela ion o he subjec s' occupa ions, he sample consis s p ima ily o hose
cu en ly in employmen and e i ed indi iduals, as well as hose in eceip o a s a e pension. I is
no ewo hy ha he sample is lacking in s uden s, a phenomenon ha is also associa ed wi h he age
dis ibu ion o he sample. Conce ning he a ailabili y o bicycles, i is obse ed ha many households
in Budapes do no possess a bicycle, in con as o he p e alence o ca owne ship, whe e o e 60% o
households own a leas one ca .
70
7.3. Modal spli
As demons a ed in Figu e 57, he modal spli esul s o he ci y o Budapes e eal ha he majo i y o
commu e s u ilise p i a e ehicles and public anspo . This end ex ends o educa ional ips as well,
howe e , he limi ed numbe o educa ional ips included in he da ase may ha e in luenced he
analysis' ou comes. In con as , when i comes o shopping and leisu e ips, walking eme ges as he
p edominan mode, ollowed by d i ing and public anspo . No ably, bicycle usage emains minimal
in Budapes .
Figu e 57: Modal spli by ip pu pose – Budapes
The esul s o he modal spli analysis in he 16 h and 17 h Dis ic o Budapes , as p esen ed in Figu e
58, indica e a p e e ence o d i ing and public anspo , pa icula ly o shopping and wo k- ela ed
ips. Fu he mo e, i is obse ed ha leisu e ips a e p edominan ly unde aken by ca , on oo , and
by public anspo , which mi o s he modal spli obse ed in Budapes . Howe e , an inc ease in ca
usage is obse ed in shopping and leisu e ips, while a dec ease is obse ed o wo k- ela ed ips. I
is also no ed ha bicycle usage emains low. Mo eo e , he lack o da a om educa ional ips limi s he
analysis o he modal spli o his ip ca ego y.
Figu e 58: Modal spli by ip pu pose – 16 h & 17 h Dis ic
71
7.4. T ip Cha ac e is ics – Budapes
7.4.1. Wo k ips
In Budapes , he a e age commu e las s app oxima ely 36 minu es, while only he 17.4% o hese ips
a e comple ed wi hin 15 minu es. The high s anda d de ia ion (SD) sugges s conside able a iabili y in
he sample, indica ing ha some ips a e conside ably longe o sho e han he a e age. The majo i y
o he wo k- ela ed ips in Budapes a e made by ca . The a e age du a ion o hese jou neys is 36
minu es, wi h only 12.3% o ips las ing up o 15 minu es. This sugges s a limi ed le el o p oximi y o
wo k- ela ed acili ies, pa icula ly o hose who op o sus ainable anspo a ion modes.
Addi ionally, commu es unde aken by public anspo a e p e alen , hough hey end o be
signi ican ly longe han hose made by ca . Fu he mo e, only he 4.4% o hese commu es a e
comple ed wi hin 15 minu es. Consequen ly, he analysis indica es a high deg ee o ca dependency
among indi iduals in Budapes , which con ibu es o he o e all leng h o commu es.
Figu e 59: Densi y plo o wo k ip du a ion by anspo mode – Budapes
Table 57: Wo k ip s a is ics by anspo mode – Budapes
T anspo Modes Sample (n) Du a ion (min)
Mean
Median
SD
All Modes 2366 35.88 32.0 26.90
Pedes ians
233
11.74
10.0
9.18
Bicycle 110 27.12 20.0 23.77
Ca (as D i e )
1187
35.91
30.0
26.23
Ca (as Passenge ) 43 38.23 40.0 15.94
Public T anspo
793
44.01
40.0
27.67
(a) Du a ion ac oss all modes (b) Du a ion by mode o anspo
Figu e 60: Cumula i e dis ibu ion unc ion (CDF) o wo k ip du a ion– Budapes
72
Table 58: Pe cen age o wo k ips conduc ed o di e en ime s amps – Budapes
T anspo Modes Sha e o ips wi h a du a ion less han (min)
10 15 20 30
All Modes 10.5% 17.4% 27.8% 49.6%
Pedes ians 67.8% 82.8% 93.1% 98.3%
Bicycle 10.9% 28.2% 51.8% 86.4%
Ca (as D i e ) 5.2% 12.3% 23.4% 50.7%
Ca (as Passenge ) 7.0% 14.0% 18.6% 30.2%
Public T anspo 1.8% 4.4% 12.4% 29.6%
7.4.2. Educa ional ips
The mean du a ion o educa ional ips in Budapes is 31.4 minu es, and acco ding o Table 60, almos
22% o hese ips a e comple ed wi hin 15 minu es. Public anspo is he p edominan mode o
educa ion- ela ed ips in Budapes , ollowed by ca . Public anspo ips las on a e age 35 minu es,
while almos 8% o hem las up o 15 minu es. I is impo an o no e ha he age g oup o indi iduals
younge han 19 y.o. is no ep esen ed success ully in he sample, he e o e, he majo i y o educa ional
ips in Budapes ha e as a des ina ion e ia y educa ional acili ies. The esul s indica e an o e all low
le el o p oximi y o educa ional ins i u ions in Budapes . This has esul ed in a shi away om mo e
sus ainable means o anspo like walking o cycling.
Figu e 61: Densi y plo o educa ional ip du a ion by anspo mode – Budapes
Table 59: Educa ional ip s a is ics by anspo mode – Budapes
T anspo Modes Sample (n) Du a ion (min)
Mean Median SD
All Modes
74
31.39
30.0
15.34
Pedes ians
Insu icien sample size o analysis
Bicycle
Ca (as D i e ) 26 25.42 20.0 18.08
Ca (as Passenge )
Insu icien sample size o analysis
Public T anspo 38 35.84 33.5 12.14
73
(a) Du a ion ac oss all modes (b) Du a ion by mode o anspo
Figu e 62: Cumula i e dis ibu ion unc ion (CDF) o educa ional ip du a ion– Budapes
Table 60: Pe cen age o educa ional ips conduc ed o di e en ime s amps – Budapes
T anspo Modes Sha e o ips wi h a du a ion less han (min)
10
15
20
30
All Modes 8.1% 21.6% 35.1% 56.8%
Pedes ians Insu icien sample size o analysis
Bicycle
Ca (as D i e ) 19.2% 38.5% 65.4% 73.1%
Ca (as Passenge ) Insu icien sample size o analysis
Public T anspo 7.9% 13.2% 47.4%
7.4.3. Shopping ips
Shopping ips in Budapes las on a e age 20 minu es, while 55% o hem a e comple ed wi hin 15
minu es. The mos used anspo mode o shopping- ela ed ips in Budapes is walking, ollowed by
ca and public anspo . Acco ding o he esul s p esen ed in Table 61 and Table 62, walking ips o
shopping acili ies las on a e age 11.8 minu es and almos 82% o hem las up o 15 minu es. In
addi ion, ca jou neys o shopping acili ies a e on a e age longe han walking jou neys, and he high
a iance in he sample shows ha ca jou neys a e p e e ed o shopping des ina ions ha a e a om
home and ha may o e a wide a ie y o p oduc s. The same applies o shopping ips made by public
anspo . Howe e , only 24% o public anspo ips a e comple ed wi hin 15 minu es, compa ed o
48% o ca ips. O e all, indi iduals in Budapes a e choosing mo e sus ainable modes o anspo o
mee hei daily shopping needs, a inding ha indica es a good le el o p oximi y o shopping acili ies.
Figu e 63: Densi y plo o shopping ip du a ion by anspo mode – Budapes
80
1. Young adul s (19 o 39 yea s old)
2. Middle-aged adul s (40 o 59 yea s old)
3. Old adul s (o e 60 yea s old)
Wo k a el imes a e ela i ely s able ac oss age g oups wi h no signi ican di e ence.
Indi iduals om all age g oups usually d i e o wo k- ela ed ips.
Middle-aged adul s ha e he longes shopping ips, bu wi h high a iabili y.
Ca is he p edominan mode o shopping and leisu e ips conduc ed by middle-aged adul s.
Olde adul s end o spend mo e ime on leisu e ips, bu no signi ican ly.
Bo h young and old adul s walk mo e han middle-aged adul s when a elling o leisu e.
81
8. ÎLE-DE-FRANCE
8.1. Gene al cha ac e is ics o Île-de-F ance and LL loca ion
Île-de-F ance egion consis s o 8 dis ic s (dépa emen s) and has o e 1,200 municipali ies. (10). Wi h
mo e han 12,4 million inhabi an s in 2022, i is he mos populous egion and he mos densely
popula ed in F ance. Île-de-F ance has a highly de eloped public anspo ne wo k consis ing o 16
me o lines, egional ain lines, am lines and bus lines.
The Île-de-F ance Li ing Lab is cen ed a ound he T12 Exp ess amway co ido , which links se e al
municipali ies in he Essonne egion. This amway, which will be inaugu a ed in 2023, se es a ound
280,000 inhabi an s. The anspo ne wo k in he Li ing Lab a ea al eady includes imp o ed cycling
in as uc u e linking he am line o he su ounding neighbou hoods and egional ains.
Figu e 73 shows he map o Île-de-F ance and he loca ion o he Essonne egion.
Figu e 73: Loca ion o he Essonne dis ic (o ange line) (Sou ce: OSM (2024))
82
8.2. Desc ip i e s a is ical analysis
Fo he desc ip i e s a is ical analysis o he Île-de-F ance egion and he Essonne egion, he da ase
“Enquê e Globale T anspo (EGT) 2020” (11) was used. A lis o socioeconomic a iables, bo h o
households and indi iduals, was selec ed and p esen ed in Tables Table 71 and Table 72 espec i ely.
The sample used o his pa o he analysis is he o al esiden popula ion wi hin he a ea (Île-de-
F ance o Essonne), wi h no il e ing o speci ic ip pu poses. Fu he mo e, he sample o su ey
esponden s who did no p o ide a alid esponse o one o mo e o he selec ed ques ions was excluded
om he sample.
Table 71: Socioeconomic cha ac e is ics o households (Île-de-F ance & Essonne) – Sou ce: EGT 2020
Socioeconomic Cha ac e is ics o Households
Île
-
de
-
F ance
LL Loca ion (
Essonne
)
n
%
n
%
Household size
1 Pe son 1779 37.3 161 32.0
2 Pe sons
1512
31.7
168
33.4
3 Pe sons
602
12.6
75
14.9
4+ Pe sons 873 18.3 99 19.7
Economic si ua ion
Less han 800
€
87
2.2
8
1.9
F om 800 o 1200
€
200
5.0
15
3.5
F om 1200 o 1600
€
324
8.1
32
7.5
F om 1600 o 2000
€
389
9.8
53
12.5
F om 2000 o 2400
€
411
10.3
44
10.4
F om 2400 o 3000
€
491
12.3
55
12.9
F om 3000 o 3500
€
398
10.0
50
11.8
F om 3500 o 4500
€
582
14.6
74
17.4
F om 4500 o 5500
€
414
10.4
37
8.7
5500€ and mo e 683 17.2 57 13.4
Ca owne ship
0
839
19.4
30
6.4
1
2292
53.0
253
54.1
2 1033 23.9 165 35.3
3
140
3.2
18
3.8
4+
20
0.5
2
0.4
Table 72: Socioeconomic cha ac e is ics o indi iduals (Île-de-F ance & Essonne) – Sou ce: EGT 2020
Socioeconomic Cha ac e is ics o Indi iduals
Île
-
de
-
F ance
LL Loca ion (
Essonne
)
n
%
n
%
Gende
Male
4993
47.7
554
48.2
Female
5477
52.3
596
51.8
Age Ca ego y (y.o.)
6 – 14 1972 18.8 203 17.7
15
–
19
615
5.9
81
7.0
20
–
24
359
3.4
40
3.5
25 – 34 1061 10.1 112 9.7
35
–
44
1462
14.0
142
12.3
45
–
54
1608
15.4
181
15.7
55 – 64 1381 13.2 157 13.7
65+
2012
19.2
234
20.3
Occupa ion
S uden
2064
22.1
225
22.3
Employed 4433 47.4 463 45.9
Pensione
2181
23.3
251
24.9
O he
673
7.2
70
6.9
Ca d i ing
license
Yes
6397
79.8
156
17.7
No
1617
20.2
724
82.3
The desc ip i e s a is ical analysis p o ides a comp ehensi e insigh in o he demog aphic
cha ac e is ics o he inhabi an s o Île-de-F ance and Essonne. Fi s ly, he sample o women is sligh ly
la ge han ha o men. In addi ion, child en and olde adul s a e mo e s ongly ep esen ed in he
sample. Rega ding he ype o employmen , he majo i y o he sample is employed. In addi ion, mos o
83
he people in Île-de-F ance ha e a d i ing licence, in con as o he people in Essonne, whe e only
17.7% o he inhabi an s ha e a d i ing licence.
8.3. Modal spli
As illus a ed in Figu e 74, and analysis o he modal spli by ip pu pose o he Île-de-F ance egion
e eals ha o commu e s, d i ing is he p edominan mode o anspo a ion, ollowed by public
anspo and walking. Wi h espec o educa ional- ela ed ips, walking eme ges as he p edominan
mode o anspo a ion, ollowed by public anspo . In he case o shopping ips, walking is he mos
p e alen mode, hough ca use and public anspo a ion also eme ge as popula modes. Wi h ega d
o leisu e ips, walking eme ges as he p edominan mode. The analysis indica es a p e e ence among
Île-de-F ance esiden s o walking and public anspo a ion when ul illing daily needs. Fu he mo e,
bicycle usage is no as p e alen in Île-de-F ance.
Figu e 74: Modal spli by ip pu pose - Île-de-F ance
The esul s o he modal spli analysis in he Essonne depa men , as p esen ed in Figu e 75, indica e a
clea p e e ence o d i ing and public anspo o wo k- ela ed ips. A no able inc ease in he
u ilisa ion o ca s o daily commu es is obse ed, accompanied by a decline in walking. A simila end
is obse ed in he con ex o shopping, wi h an inc ease in ca use o his pu pose. Leisu e ips a e
p edominan ly unde aken on oo , and by ca , which mi o s he modal spli obse ed in Île-de-F ance.
Addi ionally, an inc ease in public anspo a ion usage and ca usage (as passenge ) is obse ed o
educa ional ips. I is also no ed ha bicycle usage emains low. The modal spli esul s in Essonne
depa men indica e a s ong eliance on mo o ized anspo , con as ing wi h he esul s o Île-de-
F ance modal spli .
84
Figu e 75: Modal spli by ip pu pose - Essonne
8.4. T ip Cha ac e is ics - Île-de-F ance
8.4.1. Wo k ips
The a e age du a ion o a wo k ip in Île-de-F ance is app oxima ely 34 minu es, wi h an a e age
dis ance o 9 kilome es. Acco ding o Table 74, nea ly 85% o wo k ips in he egion a e comple ed
wi hin 15 minu es. D i ing is he mos p e alen mode o commu ing, wi h an a e age du a ion o 32
minu es. Howe e , only 30.8% o hese ips las up o 15 minu es. Public anspo is also a popula
mode o commu ing, especially o longe ips, wi h he a e age du a ion o a commu e unde aken by
public anspo being 55 minu es, while co e ing almos 14 kilome es. This may be a ibu ed o he
ac ha a signi ican p opo ion o Île-de-F ance esiden s eside in a eas dis an om he Pa is egion,
necessi a ing longe commu es. Finally, walking ips a e he sho es bo h in du a ion and dis ance.
Despi e he high deg ee o p oximi y o wo k- ela ed acili ies indica ed by he esul s, esiden s o he
Île-de-F ance egion ne e heless emain highly dependen on mo o ised anspo o hei daily
commu es.
(a) Du a ion by mode o anspo
(b) Dis ance by mode o anspo
Figu e 76: Densi y plo o wo k ip du a ion (a) and dis ance (b) by anspo mode – Île-de-F ance
85
Table 73: Wo k ip s a is ics by anspo mode – Île-de-F ance
T anspo Modes Sample (n) Du a ion (min) Dis ance (km)
Mean Median SD Mean Median SD
All Modes 4141 34.19 30.0 28.30 8.99 5.0 13.06
Pedes ians 1008 10.06 7.5 11.40 0.57 0.4 0.69
Bicycle 145 25.83 20.0 23.79 4.61 2.8 5.91
Ca (as D i e ) 1477 31.69 30.0 22.48 10.76 7.3 10.61
Ca (as Passenge ) 67 19.42 15.0 16.36 5.63 2.7 7.38
Public T anspo 1444 55.10 50.0 27.47 13.66 9.4 17.05
(a) Du a ion ac oss all modes (b) Du a ion by mode o anspo
(c) Dis ance ac oss all modes (d) Dis ance by mode o anspo
Figu e 77: Cumula i e dis ibu ion unc ion (CDF) o wo k ip du a ion (a, b) and dis ance (c, d)– Île-de-F ance
Table 74: Pe cen age o wo k ips conduc ed o di e en ime s amps – Île-de-F ance
T anspo Modes Sha e o ips wi h a du a ion less han (min)
10 15 20 30
All Modes 26.8% 36.2% 43.5% 58.5%
Pedes ians 24.8% 43.4% 60.0% 80.0%
Bicycle 26.8% 36.2% 43.5% 58.5%
Ca (as D i e ) 18.5% 30.8% 41.2% 63.8%
Ca (as Passenge )
43.3%
59.7%
77.6%
85.1%
Public T anspo 0.5% 3.5% 7.5% 22.4%
86
8.4.2. Educa ional ips
T ips o educa ional ins i u ions in Île-de-F ance egion las on a e age 20 minu es, while co e ing
almos 3 kilome es. The esul s p esen ed in Table 76 indica e a high deg ee o p oximi y o educa ional
ins i u ions, since almos 90% o he educa ional ips epo ed a e comple ed wi hin 15 minu es. The
dominan mode in his ip pu pose ca ego y is walking, ollowed by public anspo and ca (as
passenge ). Walking ips a e he sho es in bo h du a ion and dis ance, and 72% o hem las up o 15
minu es. In con as , public anspo ips a e he longes , wi h an a e age du a ion o 43 minu es and
an a e age dis ance o almos 8 kilome es. The p edominance o sho ips in he Île-de-F ance egion
is indica i e o a high deg ee o dependency on mo o ised anspo . This phenomenon may be
a ibu ed o he ac ha a signi ican p opo ion o uni e si y s uden s who do no eside in close
p oximi y o Pa is, whe e he majo i y o uni e si ies a e loca ed, a e compelled o unde ake longe
jou neys.
(a) Du a ion by mode o anspo (b) Dis ance by mode o anspo
Figu e 78: Densi y plo o educa ional ip du a ion (a) and dis ance (b) by anspo mode – Île-de-F ance
Table 75: Educa ional ip s a is ics by anspo mode – Île-de-F ance
T anspo Modes Sample (n) Du a ion (min) Dis ance (km)
Mean Median SD Mean Median SD
All Modes
2267
19.65
10.0
20.47
2.95
0.8
5.62
Pedes ians 1234 10.02 10.0 6.35 0.60 0.4 0.61
Bicycle
43
19.95
10.0
25.93
3.28
1.5
5.15
Ca (as D i e ) 28 29.50 25.0 13.01 10.30 8.0 8.33
Ca (as Passenge )
351
12.44
10.0
9.70
2.37
1.0
3.44
Public T anspo 611 42.77 35.0 24.69 7.68 4.4 8.28
87
(a) Du a ion ac oss all modes (b) Du a ion by mode o anspo
(c) Dis ance ac oss all modes
(d) Dis ance by mode o anspo
Figu e 79: Cumula i e dis ibu ion unc ion (CDF) o educa ional ip du a ion (a, b) and dis ance (c, d)– Île-de-F ance
Table 76: Pe cen age o educa ional ips conduc ed o di e en ime s amps – Île-de-F ance
T anspo Modes Sha e o ips wi h a du a ion less han (min)
10 15 20 30
All Modes 73.3% 89.7% 95.9% 99.4%
Pedes ians 51.2% 72.1% 81.4%
Bicycle
3.6%
7.1%
42.9%
67.9%
Ca (as D i e )
51.9%
64.7%
73.7%
83.3%
Ca (as Passenge ) 64.7% 77.5% 90.0% 95.4%
Public T anspo
3.6%
8.8%
20.5%
44.5%
8.4.3. Shopping ips
On a e age, shopping ips in Île-de-F ance egion las app oxima ely 16 minu es, wi h a dis ance
co e ed o 3 kilome es. The p edominan mode o anspo a ion is walking, ollowed by ca and public
anspo . On a e age, indi iduals in he Île-de-F ance egion walk o 10 minu es o access shopping
acili ies, wi h almos 90% o hese ips las ing up o 15 minu es. Ca jou neys, on he o he hand, a e
compa a i ely leng hy, al hough hey do co e g ea e dis ances. The high p opo ion o ips comple ed
wi hin 15 minu es unde sco es a high deg ee o p oximi y o shopping ameni ies in he Île-de-F ance
egion.
88
(a) Du a ion by mode o anspo (b) Dis ance by mode o anspo
Figu e 80: Densi y plo o shopping ip du a ion (a) and dis ance (b) by anspo mode – Île-de-F ance
Table 77: Shopping ip s a is ics by anspo mode – Île-de-F ance
T anspo Modes Sample (n)
Du a ion (min)
Dis ance (km)
Mean Median SD Mean Median SD
All Modes
4109
16.21
10.0
17.82
3.05
0.9
8.01
Pedes ians 1954 9.73 5.0 8.50 0.49 0.3 0.56
Bicycle
68
16.47
15.0
15.50
2.42
1.3
3.42
Ca (as D i e ) 1291 17.45 15.0 18.31 4.89 2.4 7.84
Ca (as Passenge )
295
16.57
15.0
13.09
4.23
2.5
6.40
Public T anspo 501 38.05 30.0 26.13 7.68 4.1 16.86
(a) Du a ion ac oss all modes (b) Du a ion by mode o anspo
(c) Dis ance ac oss all modes (d) Dis ance by mode o anspo
Figu e 81: Cumula i e dis ibu ion unc ion (CDF) o shopping ip du a ion (a, b) and dis ance (c, d)– Île-de-F ance
89
Table 78: Pe cen age o shopping ips conduc ed o di e en ime s amps – Île-de-F ance
T anspo Modes Sha e o ips wi h a du a ion less han (min)
10 15 20 30
All Modes 54.4% 72.0% 79.9% 90.1%
Pedes ians 75.0% 89.4% 94.1% 98.1%
Bicycle 48.5% 67.6% 75.0% 92.6%
Ca (as D i e ) 45.0% 68.2% 78.5% 91.4%
Ca (as Passenge ) 41.7% 69.8% 83.1% 94.2%
Public T anspo 6.6% 15.6% 27.3% 52.9%
8.4.4. Leisu e ips
The a e age a el ime o esiden s o Île-de-F ance o each a leisu e acili y is 23 minu es, wi h a
dis ance o 4 kilome es being co e ed. Acco ding o Table 80, almos 60% o hese jou neys a e
comple ed wi hin 15 minu es. Walking is he mos used mode o leisu e ips, ollowed by ca (as
d i e ) and public anspo . On a e age, walking ips a e b ie in bo h dis ance and du a ion, wi h 75%
o hem las ing up o 15 minu es. The ca is also a popula anspo mode in his ip ca ego y o longe
dis ances. Bicycle ips a e cha ac e ised by hei ex ended du a ion, wi h an a e age du a ion o 34
minu es. The high s anda d de ia ion in he sample indica es ha he bicycle is used o bo h sho and
long leisu e ips by Île-de-F ance esiden s, wi h 75% o ips comple ed wi hin 15 minu es. Finally,
ips made by public anspo a e on a e age he longes (46 minu es) and co e longe dis ances han
hose made by o he a el modes. The e o e, a ela i ely limi ed p opo ion (10.3%) o hese ips las
up o 15 minu es.
(a) Du a ion by mode o anspo (b) Dis ance by mode o anspo
Figu e 82: Densi y plo o leisu e ip du a ion (a) and dis ance (b) by anspo mode – Île-de-F ance
Table 79: Leisu e ip s a is ics by anspo mode – Île-de-F ance
T anspo Modes Sample (n) Du a ion (min) Dis ance (km)
Mean
Median
SD
Mean
Median
SD
All Modes 5400 23.10 15.0 25.95 4.02 1.0 13.34
Pedes ians
2830
15.53
10.0
18.58
0.60
0.4
0.76
Bicycle 157 33.99 15.0 43.50 8.03 1.8 26.80
Ca (as D i e )
1086
24.98
15.0
26.71
7.80
3.3
15.97
Ca (as Passenge ) 533 21.91 15.0 23.18 6.39 2.7 13.46
Public T anspo
794
46.17
40.0
29.64
8.63
4.8
22.54
96
(a) Du a ion by mode o anspo
(b) Dis ance by mode o anspo
Figu e 90: Densi y plo o leisu e ip du a ion (a) and dis ance (b) by anspo mode – Essonne
Table 87: Leisu e ip s a is ics by anspo mode – Essonne
T anspo Modes Sample (n)
Du a ion (min)
Dis ance (km)
Mean Median SD Mean Median SD
All Modes 428 22.82 15.0 24.06 4.61 1.6 7.69
Pedes ians 174 18.12 15.0 14.33 0.54 0.3 0.77
Bicycle Insu icien sample size o analysis
Ca (as D i e ) 139 21.91 15.0 18.02 7.06 3.8 7.92
Ca (as Passenge ) 72 16.31 15.0 12.20 4.73 2.6 5.68
Public T anspo
32
62.13
60.0
32.29
14.84
16.0
9.69
(a) Du a ion ac oss all modes
(b)
Du a ion by mode o anspo
(c) Dis ance ac oss all modes
(d) Dis ance by mode o anspo
Figu e 91: Cumula i e dis ibu ion unc ion (CDF) o leisu e ip du a ion (a, b) and dis ance (c, d)– Essonne
97
Table 88: Pe cen age o leisu e ips conduc ed o di e en ime s amps – Essonne
T anspo Modes Sha e o ips wi h a du a ion less han (min)
10
15
20
30
All Modes 39.3% 58.2% 69.4% 82.2%
Pedes ians 46.0% 64.4% 70.7% 86.8%
Bicycle Insu icien sample size o analysis
Ca (as D i e ) 34.5% 56.8% 71.9% 84.2%
Ca (as Passenge ) 48.6% 65.3% 87.5% 94.4%
Public T anspo 6.3%
6.3%
6.3%
18.8%
8.6. T a el beha iou ac oss di e en socioeconomic g oups
The p esen sec ion o he analysis is conce ned wi h an examina ion o modal spli and ip
cha ac e is ics o di e en socioeconomic g oups in Île-de-F ance. The main indings o he analysis a e
p esen ed he e, bu he de ailed esul s o he analysis can be ound in Appendix E and G.
8.6.1. Gende
Males a el signi ican ly longe han women, o wo k and leisu e ip pu poses.
Females end o walk mo e o en o shopping ips han males, who a e mo e likely o use hei
ca s o his pu pose.
Walking is he p edominan mode o anspo a ion o educa ional excu sions, i espec i e o
gende .
Females u ilize public anspo o commu es han males, who gene ally p e e p i a e
anspo a ion.
8.6.2. Income
The da ase ca ego izes he economic si ua ion o households in Île-de-F ance based on he mon hly ne
income class o he household. Fo he pu pose o he analysis, we ha e been me ged he i s six g oups
(less han 800€ – up o 3000€) in o a single ca ego y called low income, and he las i e g oups (mo e
han 3000€ - mo e han 5500€) in o a single ca ego y called high income. This ca ego isa ion is based
on he na ional s a is ics ha s a e ha o he yea o 2021 he a e age ne mon hly income in Île-de-
F ance was app oxima ely 3,128€ (h ps://www.s a is a.com/s a is ics/1440766/a e age-ne -
mon hly-income-in- ance-by-gende -and-by- egion/).
Wo k and educa ion ips ha e no signi ican a ia ion bo h in du a ion and dis ance ac oss
income g oups.
Shopping ips a e signi ican ly longe in e ms o dis ance o he low-income g oup.
The ip du a ion o leisu e ips is signi ican ly longe o indi iduals om he low-income
g oup.
8.6.3. Age
In o de o analyse a el beha iou ac oss age in Île-de-F ance, he sample has been di ided in o ou
g oups. The g oups a e he ollowing:
1. Child en/S uden s (up o 18 yea s old)
2. Young adul s (19 o 39 yea s old)
3. Middle-aged adul s (40 o 59 yea s old)
4. Old adul s (o e 60 yea s old)
Wo k a el dis ance di e s signi ican ly ac oss age g oups, bu du a ion does no .
Educa ion ips show he la ges a ia ion, wi h young adul s a eling signi ican ly a he and
longe .
Shopping and leisu e ips inc ease sligh ly wi h age bu emain ela i ely sho .
98
Olde adul s ake he longes leisu e ips, while younge adul s ha e he longes educa ion ips.
Ca usage inc eases wi h age, especially o shopping and leisu e ips.
Public anspo is he p edominan mode o wo k and educa ion ips o young adul s.
Middle-aged and olde adul s ely mo e on ca s o non-wo k ips.
99
9. MUNICH
9.1. Gene al cha ac e is ics o Munich and LL loca ion
The capi al o he sou he n Ge man s a e o Ba a ia is he ci y Munich, which has a popula ion o 1,48
million inhabi an s and is he hi d la ges ci y in Ge many. Munich's public anspo ne wo k consis s
o subu ban ailways, eigh me o lines, am lines, bus lines and an ex ensi e cycling in as uc u e.
Fu he mo e, he ci y o e s a ple ho a o ac i e and sha ed mobili y op ions.
The Munich Li ing Lab cons i u es he wo municipali ies o Ge e s ied and Wol a shausen, which a e
loca ed in he sou he n pa o Munich. Ge e s ied has an app oxima e popula ion o 25,705, while
Wol a shausen has a o al popula ion o 19,115 inhabi an s. Bo h municipali ies a e walkable and
cyclable, and hey a e connec ed wi h he ci y o Munich ia subu ban ailways and buses.
Figu e 92 shows he map o Munich and he loca ion o he Munich Li ing Lab ( ed pins).
Figu e 92: Loca ion o he Munich Li ing Labs ( ed pins) (Sou ce: OSM (2024))
100
9.2. Desc ip i e s a is ical analysis
Fo he desc ip i e s a is ical analysis o he Munich egion and he Munich Li ing Lab egion, he
da ase “Mobili ä in Deu schland (MiD) 2017” (12) was used. A lis o socioeconomic a iables, bo h o
households and indi iduals, was selec ed and p esen ed in Tables Table 89 and Table 90 espec i ely.
I is impo an o acknowledge he limi a ions imposed by he ela i ely modes sample size o ips
made by esiden s o he o Ge e s ied and Wol a shausen municipali ies. This limi s he scope and
gene alisabili y o he esul s o he analysis. In o de o add ess hese limi a ions, a comp ehensi e
analysis o all he dense owns a S-Bahn e mini is conduc ed, since all hese owns sha e common
socio-economic and a el cha ac e is ics.
The sample used o his pa o he analysis is he o al esiden popula ion wi hin he a ea (Munich o
Munich LL), wi h no il e ing o speci ic ip pu poses. Fu he mo e, he sample o su ey esponden s
who did no p o ide a alid esponse o one o mo e o he selec ed ques ions was excluded om he
sample
Table 89: Socioeconomic cha ac e is ics o households (Munich & Dense Towns a S-Bahn Te mini) – Sou ce: MiD 2017
Socioeconomic Cha ac e is ics o Households
Munich
LL Loca ion (Dense Towns a S
-
Bahn Te .)
n
%
n
%
Household size
1 Pe son
2582
31.4
101
17.2
2 Pe sons 3547 43.2 262 44.6
3
Pe sons
1051
12.8
88
15
4+ Pe sons
1038
12.6
137
23.3
Economic si ua ion
Ve y poo 220 2.7 21 3.6
Poo
497
6
35
6
A e age
3255
39.6
225
38.3
Good 2970 36.1 239 40.6
Ve y good
1276
15.5
68
11.6
Ca owne ship
0
2013
24.5
24
4.1
1 4598 56 293 49.8
2+
1607
19.6
271
46.1
Table 90: Socioeconomic cha ac e is ics o indi iduals (Munich & Dense Towns a S-Bahn Te mini) – Sou ce: MiD 2017
Socioeconomic Cha ac e is ics o Indi iduals
Munich
LL Loca ion (Dense Towns a
S
-
Bahn Te .)
n
%
n
%
Gende
Male 7755 49.1 666 49.2
Female
8026
50.9
687
50.8
Age Ca ego y (y.o.)
0
-
17
2088
13.2
223
16.5
18 - 29 1777 11.3 153 11.4
30
-
39
2352
14.9
123
9.1
40
-
49
2152
13.6
194
14.4
50
-
59
2419
15.3
236
17.5
60
-
69
2040
12.9
221
16.4
70
-
79
2140
13.6
155
11.5
80+
804
5.1
43
3.2
Occupa ion
S uden
2203
14
261
19.3
Employed
7865
49.9
630
46.7
Pensione
3974
25.2
327
24.2
O he
1735
11
132
9.8
Ca d i ing license
Yes
10831
91.7
886
94.2
No
982
8.3
55
5.8
Ca a ailabili y
Always
8672
74.9
792
85.7
Occasionally
1701
14.7
81
8.8
Ne e
1210
10.4
51
5.5
Bicycle a ailabili y
Yes
12865
81.6
1125
83.2
No
2897
18.4
227
16.8
101
The desc ip i e s a is ical analysis p o ides a comp ehensi e o e iew o he demog aphic p o iles o
esiden s in Munich and he Munich Li ing Lab egion. Wi h espec o gende , he popula ion in he
sample is almos equally dis ibu ed. Howe e , a ma ked dispa i y eme ges wi h espec o ehicle
owne ship, wi h he Munich Li ing Lab egion exhibi ing a signi ican ly highe a e compa ed o he
Munich sample. While he majo i y o households in Munich LL possess a leas one ca , in Munich, he
p opo ion o households wi hou ca s is highe . Wi h espec o occupa ion, bo h samples a e
p edominan ly comp ised o employed indi iduals and pensione s. Wi h espec o income, he majo i y
o households in bo h egions epo an a e age o good economic si ua ion.
9.3. Modal spli
Figu e 93 shows he modal spli by ip pu pose o he ci y o Munich. Fo wo king commu es, public
anspo is he mos p e e ed mode o Munich esiden s, ollowed by d i ing and cycling. Fo
educa ional ips, public anspo is once again he mos p e alen mode o anspo , hough he sha e
o cycling and walking ips is also high. In con as , shopping ips a e p edominan ly unde aken on
oo , while ca usage emains no ably high. Wi h espec o leisu e ips, he e walking eme ges as he
p edominan mode wi h 43%, ollowed by public anspo and ca usage. The modal spli in Munich
demons a es a clea p e e ence o public anspo o wo k and educa ional pu poses, and o
walking o shopping and leisu e pu poses. Ne e heless, ca usage and bicycle usage pe sis as
p e alen modes o wo k- ela ed and shopping- ela ed ips.
Figu e 93: Modal spli by ip pu pose – Munich
The esul s o he modal spli analysis in he Munich Li ing Lab a ea, as p esen ed in Figu e 94, indica e
a clea p e e ence o d i ing o wo k- ela ed ips. In compa ison wi h he esul s o he wide Munich
a ea, whe e public anspo is he p edominan mode o anspo , he e is a ma ked inc ease in ca
usage o daily commu es, accompanied by a decline in cycling and public anspo usage. A simila
end is obse ed in he con ex o shopping, wi h an inc ease in ca use o his pu pose. Fu he mo e,
i is obse ed ha leisu e ips a e p edominan ly unde aken by ca o on oo . The modal spli esul s
in Munich Li ing Lab a ea indica e a eliance on mo o ized anspo , pa icula ly o wo k and shopping
ips, con as ing wi h he esul s o he modal spli in Munich.
102
Figu e 94: Modal spli by ip pu pose – Dense Towns a S-Bahn Te mini
9.4. T ip Cha ac e is ics – Munich
9.4.1. Wo k ips
The mean a el ime o commu e s in Munich is 32 minu es, wi h a dis ance o 12 kilome es being
co e ed. Acco ding o Table 92, 26% o he commu es in Munich a e comple ed wi hin 15 minu es. The
mos common modes o anspo a ion o commu ing a e public anspo , p i a e ehicle and bicycle.
The mean du a ion o public anspo commu es is 42 minu es, while he mean dis ance a elled is
14.5 kilome es. In con as , commu es by ca a e compa a i ely b ie , ye co e ex ended dis ances.
Bicycle commu es, on a e age, las app oxima ely 23 minu es, and 44% o hese a e comple ed wi hin
15 minu es. The analysis indica es ha indi iduals in Munich alloca e a subs an ial po ion o hei daily
ime o commu ing and hey a e dependen on mo o ized anspo and he public anspo a ion
sys em.
(a) Du a ion by mode o anspo (b) Dis ance by mode o anspo
Figu e 95: Densi y plo o wo k ip du a ion (a) and dis ance (b) by anspo mode – Munich
103
Table 91: Wo k ip s a is ics by anspo mode – Munich
T anspo Modes Sample (n) Du a ion (min) Dis ance (km)
Mean Median SD Mean Median SD
All Modes 6773 31.90 30.00 26.91 12.06 7.20 28.93
Pedes ians 521 16.89 10.00 18.02 1.50 0.98 2.35
Bicycle 1459 22.73 20.00 14.32 5.10 3.92 4.11
Ca (as D i e ) 2166 29.28 25.00 22.88 15.98 9.50 28.56
Ca (as Passenge ) 140 38.34 20.00 50.36 20.17 5.87 50.26
Public T anspo 2487 42.34 35.00 31.19 14.49 9.00 36.64
(a) Du a ion ac oss all modes (b) Du a ion by mode o anspo
(c) Dis ance ac oss all modes (d) Dis ance by mode o anspo
Figu e 96: Cumula i e dis ibu ion unc ion (CDF) o wo k ip du a ion (a, b) and dis ance (c, d)– Munich
Table 92: Pe cen age o wo k ips conduc ed o di e en ime s amps – Munich
T anspo Modes Sha e o ips wi h a du a ion less han (min)
10 15 20 30
All Modes 13.7% 26.2% 37.4% 63.7%
Pedes ians 54.5% 70.4% 78.1% 89.4%
Bicycle 22.5% 44.1% 58.5% 82.8%
Ca (as D i e ) 11.2% 26.9% 41.8% 72.1%
Ca (as Passenge )
18.6%
35.7%
50.7%
65.0%
Public T anspo 2.1% 5.3% 11.9% 39.8%
9.4.2. Educa ional ips
T ips o educa ional ins i u ions in Munich las on a e age 23.5 minu es, while co e ing almos 6
kilome es. Acco ding o Table 94, almos 55% o educa ional ips in Munich a e comple ed wi hin 15
minu es. The p edominan mode o anspo a ion in his ca ego y is public anspo , ollowed by
bicycle and walking. Educa ional ips unde aken by public anspo ha e an a e age du a ion o 37
minu es (see Table 93: Educa ional ip s a is ics by anspo mode – Munich), while co e ing 9
kilome es. Bicycle and walking ips a e also popula , al hough he co e much sho e dis ances.
Walking eme ges as one o he p e alen modes, accoun ing o 82.5% o all educa ion- ela ed ips
comple ed wi hin he s ipula ed ime ame. The esul s indica e a high deg ee o p oximi y o
educa ional ins i u ions in Munich.
104
(a) Du a ion by mode o anspo (b) Dis ance by mode o anspo
Figu e 97: Densi y plo o educa ional ip du a ion (a) and dis ance (b) by anspo mode – Munich
Table 93: Educa ional ip s a is ics by anspo mode – Munich
T anspo Modes Sample (n)
Du a ion (min)
Dis ance (km)
Mean Median SD Mean Median SD
All Modes
2298
23.50
15.00
23.98
5.93
2.35
20.58
Pedes ians 543 14.10 10.00 15.80 0.88 0.64 0.95
Bicycle
612
16.04
15.00
10.41
2.51
1.96
2.29
Ca (as D i e ) 86 44.52 25.00 69.60 34.08 8.71 81.42
Ca (as Passenge )
308
16.79
14.50
21.12
6.25
2.43
28.23
Public T anspo 749 36.77 30.00 20.20 9.03 6.30 9.32
(a) Du a ion ac oss all modes (b) Du a ion by mode o anspo
(c) Dis ance ac oss all modes (d) Dis ance by mode o anspo
Figu e 98: Cumula i e dis ibu ion unc ion (CDF) o educa ional ip du a ion (a, b) and dis ance (c, d)– Munich
105
Table 94: Pe cen age o educa ional ips conduc ed o di e en ime s amps – Munich
T anspo Modes Sha e o ips wi h a du a ion less han (min)
10 15 20 30
All Modes 33.4% 54.2% 63.7% 79.5%
Pedes ians 58.7% 82.5% 89.7% 96.5%
Bicycle 41.7% 71.2% 83.2% 94.0%
Ca (as D i e ) 11.6% 39.5% 48.8% 69.8%
Ca (as Passenge ) 48.7% 75.0% 83.1% 92.5%
Public T anspo 4.5% 12.8% 22.7% 51.0%
9.4.3. Shopping ips
The mean du a ion o shopping ips in Munich is 17 minu es, wi h a o al dis ance co e ed o almos 4
kilome es. The p edominan mode o anspo a ion is walking, ollowed by ca and cycling.
Fu he mo e, almos 72% o shopping ips in Munich a e comple ed wi hin 15 minu es. Walking and
cycling ips a e b ie , bo h in dis ance and du a ion, while app oxima ely 80% o hem las up o 15
minu es. Ca ips (as d i e ) end o co e longe dis ances, al hough hey a e b ie in du a ion. Finally,
shopping ips unde aken by public anspo co e simila dis ances o hose made by ca , ye hey a e
cha ac e ised by a longe du a ion. The indings o his s udy demons a e ha indi iduals in Munich
p edominan ly u ilise sus ainable anspo modes o shopping ips; howe e , hey a e s ill dependen
on mo o ised anspo when hey wish o co e longe dis ances.
(a) Du a ion by mode o anspo (b) Dis ance by mode o anspo
Figu e 99: Densi y plo o shopping ip du a ion (a) and dis ance (b) by anspo mode – Munich
Table 95: Shopping ip s a is ics by anspo mode – Munich
T anspo Modes Sample (n) Du a ion (min) Dis ance (km)
Mean
Median
SD
Mean
Median
SD
All Modes 8888 17.12 10.00 20.65 3.69 1.47 12.76
Pedes ians
3126
14.28
10.00
19.36
0.80
0.49
1.22
Bicycle 1752 13.34 10.00 15.28 2.08 1.27 2.83
Ca (as D i e )
2264
17.22
10.00
21.17
6.44
2.95
21.18
Ca (as Passenge ) 662 20.25 15.00 21.04 7.59 3.80 12.93
Public T anspo 1084 29.25 25.00 25.20 6.49 4.50 14.78
112
(a) Du a ion ac oss all modes (b) Du a ion by mode o anspo
(c) Dis ance ac oss all modes (d) Dis ance by mode o anspo
Figu e 108: Cumula i e dis ibu ion unc ion (CDF) o shopping ip du a ion (a, b) and dis ance (c, d)– Dense Towns a S-Bahn
Te mini
Table 104: Pe cen age o shopping ips conduc ed o di e en ime s amps – Dense Towns a S-Bahn Te mini
T anspo Modes Sha e o ips wi h a du a ion less han (min)
10 15 20 30
All Modes 62.3% 77.3% 83.9% 90.7%
Pedes ians
50.9%
68.3%
79.8%
91.3%
Bicycle
66.2%
85.9%
92.9%
93.7%
Ca (as D i e ) 66.1% 79.2% 84.3% 91.4%
Ca (as Passenge )
60.2%
75.3%
83.9%
91.4%
Public T anspo Insu icien sample size o analysis
9.5.4. Leisu e ips
The esiden s o Munich's LL loca ion ypically a el an a e age o 31.5 minu es o leisu e pu poses.
Acco ding o Table 104, almos 55% o hese leisu e ips a e comple ed wi hin 15 minu es. The
p edominan mode o anspo a ion is he au omobile, ollowed by walking. The du a ion o ca
jou neys is on a e age 30 minu es, wi h almos 57% o hese las ing up o 15 minu es. In con as ,
walking ips a e cha ac e ised by hei du a ion, albei co e ing sho e dis ances, wi h almos 49% o
hem las ing up o 15 minu es. This igu e, howe e , may no necessa ily signi y a lack o p oximi y o
leisu e acili ies, bu a he , i could be indica i e o a dis inc p e e ence among Munich's LL o walking
as a leisu e ac i i y in i sel .
113
(a) Du a ion by mode o anspo (b) Dis ance by mode o anspo
Figu e 109: Densi y plo o leisu e ip du a ion (a) and dis ance (b) by anspo mode – Dense Towns a S-Bahn Te mi
Table 105: Leisu e ip s a is ics by anspo mode – Dense Towns a S-Bahn Te mini
T anspo Modes Sample (n)
Du a ion (min)
Dis ance (km)
Mean Median SD Mean Median SD
All Modes
1384
31.43
15.00
39.77
14.90
3.46
42.96
Pedes ians 367 34.93 20.00 37.09 2.08 1.19 2.37
Bicycle
209
26.27
10.00
36.80
4.62
1.96
9.91
Ca (as D i e ) 438 29.18 15.00 40.88 24.45 7.60 63.96
Ca (as Passenge )
272
22.92
15.00
30.73
17.00
5.70
33.98
Public T anspo 98 63.02 45.00 54.37 36.26 27.90 51.91
(a) Du a ion ac oss all modes (b) Du a ion by mode o anspo
(c) Dis ance ac oss all modes (d) Dis ance by mode o anspo
Figu e 110: Cumula i e dis ibu ion unc ion (CDF) o leisu e ip du a ion (a, b) and dis ance (c, d)– Dense Towns a S-Bahn
Te mini
114
Table 106: Pe cen age o leisu e ips conduc ed o di e en ime s amps – Dense Towns a S-Bahn Te mini
T anspo Modes Sha e o ips wi h a du a ion less han (min)
10
15
20
30
All Modes 36.9% 55.2% 63.0% 73.4%
Pedes ians
36.2
%
48.8
%
54.8
%
66.8
%
Bicycle 51.7% 66.9% 74.2% 82.3%
Ca (as D i e )
33.1
%
56.4
%
68.0
%
76.9
%
Ca (as Passenge ) 43.0% 69.1% 75.4% 84.9%
Public T anspo 8.2% 10.2% 13.3% 31.6%
9.6. T a el beha iou ac oss di e en socioeconomic g oups
The p esen sec ion o he analysis is conce ned wi h an examina ion o modal spli and ip
cha ac e is ics o di e en socioeconomic g oups in Munich. The main indings o he analysis a e
p esen ed he e, bu he de ailed esul s o he analysis can be ound in Appendix F and G.
9.6.1. Gende
Wo k ips a e signi ican ly longe o males han o emales, howe e , o o he ip pu poses
no signi ican di e ences ha e been ound.
In e ms o ip du a ion, he e a e no s a is ically signi ican di e ences in ip du a ions
be ween gende s o any ip pu pose.
Males end o d i e ca s mo e o en, especially o wo k and shopping ips.
Females ely mo e on public anspo and walking o hei shopping and leisu e ips.
Bicycle usage is ai ly balances be ween gende s, bu sligh ly highe o males in educa ion ips.
9.6.2. Income
The da ase ca ego izes he economic si ua ion o households as e y poo , poo , a e age, good, and
e y good. Fo he pu pose o he analysis, we ha e been me ged he i s wo ca ego ies ( e y poo and
poo ) in o a single ca ego y called low income, and he las wo ca ego ies (good and e y good) in o a
single ca ego y called high income.
Low-income indi iduals spend mo e ime on educa ion and shopping ips, while high-income
indi iduals co e longe dis ances o wo k and leisu e.
Wo k ips a e longe in dis ance o high-income indi iduals; howe e , ip du a ion does no
di e signi ican ly.
Bike usage is highe among high-income indi iduals, especially o wo k and educa ion ips.
High-income indi iduals use ca s mo e o hei shopping and wo k ips.
Low-income indi iduals ely hea ily on public anspo o all ip pu poses.
People wi h highe incomes a e mo e likely o walk o educa ional ins i u ions.
9.6.3. Age
In o de o analyse a el beha iou ac oss age in Munich, he sample has been di ided in o ou g oups.
The g oups a e he ollowing:
1. Child en/S uden s (up o 17 yea s old)
2. Young adul s (18 o 39 yea s old)
3. Middle-aged adul s (40 o 59 yea s old)
4. Old adul s (o e 60 yea s old)
T ip du a ion shows signi ican a ia ions ac oss age g oups o educa ion, shopping and leisu e
ips.
T ip dis ance shows signi ican di e ences o educa ion and leisu e ips, bu no signi ican
di e ences o shopping and wo k ips.
Middle-aged adul s and old adul s use ca s mo e o hei wo k and shopping ips.
115
Child en and young adul s ely mo e on public anspo a ion o hei educa ion ips.
The age g oup wi h he highes sha e o walking ips o shopping acili ies is he one o young
adul s.
Bike usage is highe among child en/s uden s and middle-aged adul s.
116
10. COMPARISON
This chap e unde akes a compa a i e analysis o he a el beha iou exhibi ed by he inhabi an s o
he ci ies and Li ing Labs unde e iew.
10.1. Ci y le el
Figu e 111 p esen s he Cumula i e Dis ibu ion Func ions (CDF) o he ci y le el, ca ego ized
acco ding o ip pu pose, and Tables 107 o 110 p esen he pe cen age o wo k, educa ional, shopping,
and leisu e ips conduc ed o di e en ime s amps.
(a)
Wo k ips
(b)
Educa ional ips
(c) Shopping ips (d) Leisu e ips
Figu e 111: Cumula i e dis ibu ion unc ion (CDF) o ip du a ion pe ip pu pose– Ci y le el
Figu e 112: Pe cen age o ips comple ed wi hin 15 minu es by ip pu pose - Ci y le el
117
Wo k ips
The esul s o he s udy demons a e a di e gence in he alignmen o wo k ips wi h he 15-Minu e
Ci y (15mC) concep . The ci y o U ech exhibi s he s onges alignmen wi h his concep , wi h 40.5%
o wo k- ela ed ips las ing less han 15 minu es and 75.8% aking less han 30 minu es. This sugges s
ha he u ban design o U ech is mo e compac , acili a ing e icien access o wo kplaces. B ussels is
a close second wi h 35.9% o ips being comple ed wi hin 15 minu es, hough a g ea e p opo ion o
hese ips a e comple ed wi hin he 30-minu e ime ange. Île-de-F ance, in spi e o i s s a us as a as
me opoli an zone, demons a es ha 36.2% o jou neys a e execu ed wi hin a ime span o 15 minu es,
whils a no able p opo ion o 58.5% alls wi hin a 30-minu e ime ame. Munich and Vienna
demons a e mode a e alignmen wi h he concep , wi h app oxima ely 26-27% o ips alling unde
15 minu es, and subs an ial p opo ions ex ending beyond 30 minu es (63.7% and 65.3%, espec i ely).
Budapes , wi h i s 17.4% o sho -du a ion ips (unde 15 minu es) and 49.6% o ips unde 30
minu es, appea s o be he u hes om ully emb acing he 15mC concep . O e all, U ech s ands ou
as he closes ma ch, while Budapes shows he leas alignmen . In ega d o he modal spli , indi iduals
in Vienna, B ussels and Munich demons a e a g ea e eliance on public anspo and ca s o hei
commu es, in compa ison o indi iduals in U ech , Budapes , and he Île-de-F ance egion, whe e he e
is a p e e ence o mo o ized anspo .
Table 107: Pe cen age o wo k ips conduc ed o di e en ime s amps – Ci y le el
Ci y Sha e o wo k ips wi h a du a ion less han (min)
10 15 20 30
Vienna 14.3% 26.9% 38.6% 65.3%
U ech 23.3% 40.5% 52.2% 75.8%
B ussels 23.5% 35.9% 49.5% 68.5%
Budapes 10.5% 17.4% 27.8% 49.6%
Île-de-F ance 26.8% 36.2% 43.5% 58.5%
Munich 13.7% 26.2% 37.4% 63.7%
Educa ional ips
A compa ison o hese ci ies in ela ion o he 15-Minu e Ci y concep e eals Île-de-F ance o be he
mos accomplished egion in his ega d, wi h a no ewo hy 89.7% o ips aking unde 15 minu es and
almos all (99.4%) aking unde 30 minu es. This inding sugges s he p esence o a well-dis ibu ed
educa ional in as uc u e in he whole egion. U ech also e eals no able pe o mance, wi h 57.5% o
ips comple ed wi hin 15 minu es and 80.8% wi hin 30 minu es. Munich and B ussels demons a e
mode a e alignmen , wi h app oxima ely 50% o educa ional ips comple ed wi hin 15 minu es and
a ound 70-80% wi hin 30 minu es. Vienna also displays a compa able endency, wi h 40.5% o ips
las ing less han 15 minu es and 74% las ing less han 30 minu es. On he o he hand, Budapes exhibi s
he leas deg ee o alignmen wi h only 21.6% o educa ional ips alling wi hin he unde 15 minu es
b acke and jus 56.8% wi hin he unde 30 minu es b acke . O e all, Île-de-F ance and U ech appea
closes o he ideal o 15-minu e ci y cen es (15mC), whe e he majo i y o s uden s can access
educa ional acili ies e icien ly, whe eas Budapes alls behind. Howe e , he absence o s uden s unde
he age o 18 in he Budapes da ase p ecludes he possibili y o de i ing any meaning ul insigh s
ega ding he deg ee o p oximi y o p ima y and seconda y educa ional ins i u ions in Budapes . Wi h
espec o he modal spli , s uden s in Vienna, B ussels, Budapes and Munich demons a e a g ea e
p opensi y o u ilising public anspo a ion o access educa ional ins i u ions, in con as o hei
coun e pa s in U ech and he Île-de-F ance egion, whe e cycling and walking a e p e e ed modes
o anspo a ion, espec i ely.
118
Table 108: Pe cen age o educa ional ips conduc ed o di e en ime s amps – Ci y le el
Ci y Sha e o educa ional ips wi h a du a ion less han (min)
10
15
20
30
Vienna 24.6% 40.5% 53.0% 74.0%
U ech
44.3%
57.5%
67.1%
80.8%
B ussels 33.1% 48.7% 56.9% 71.7%
Budapes
8.1%
21.6%
35.1%
56.8%
Île-de-F ance 73.3% 89.7% 95.9% 99.4%
Munich 33.4% 54.2% 63.7% 79.5%
Shopping ips
In e ms o shopping ips, U ech once again exhibi s a high deg ee o alignmen wi h he 15mC
concep , wi h 84.1% o ips being comple ed wi hin 15 minu es and 96.1% o ips aking no mo e han
30 minu es. This inding sugges s a high le el o p oximi y o shopping acili ies in U ech . Vienna,
Munich, he Île-de-F ance egion and B ussels ollow closely behind, wi h app oxima ely 70% o
shopping ips comple ed wi hin 15 minu es and a ound 90% wi hin 30 minu es. This inding indica es
ha hese ci ies also exhibi a high deg ee o comme cial p oximi y. Budapes , while main aining a
majo i y o ips wi hin 30 minu es (87.4%), exhibi s de iciencies in sho e ip du a ions, wi h only
55% unde 15 minu es and 37.7% unde 10 minu es. Consequen ly, i is e iden ha U ech exhibi s
op imal p oximi y o shopping, whils Budapes emains he leas aligned, al hough all ci ies
demons a e ela i ely sa is ac o y access o shopping oppo uni ies. Fu he mo e, wi h espec o
modal spli , indi iduals in all ci ies excep U ech demons a e a p e e ence o walking when accessing
shopping acili ies. In U ech , howe e , he p e e ed op ions a e cycling, d i ing o walking.
Table 109: Pe cen age o shopping ips conduc ed o di e en ime s amps – Ci y le el
Ci y Sha e o shopping ips wi h a du a ion less han (min)
10
15
20
30
Vienna 52.1% 69.9% 79.5% 90.1%
U ech 67.8% 84.1% 90.0% 96.1%
B ussels 55.0% 69.3% 78.3% 90.0%
Budapes 37.7% 55.0% 72.6% 87.4%
Île-de-F ance 54.4% 72.0% 79.9% 90.1%
Munich 52.05 71.3% 79.4% 90.6%
Leisu e ips
In e ms o leisu e ips, he Île-de-F ance egion aligns mos closely wi h he 15-Minu e Ci y (15mC)
concep , wi h 59.2% o ips comple ed wi hin 15 minu es and 80.8% wi hin 30 minu es. This sugges s
a high deg ee o p oximi y o ec ea ional spaces. Budapes also pe o ms sa is ac o ily, whe e 47% o
leisu e ips a e comple ed wi hin 15 minu es and 75% wi hin 30 minu es. B ussels and U ech exhibi
analogous ends, wi h app oxima ely 42-43% o ips alling wi hin he 15-minu e ma k and a ound
wo- hi ds o all ips aking up o 30 minu es. Con e sely, Vienna and Munich exhibi he lowes
p opo ions o sho leisu e ips, wi h app oxima ely 36-40% o ips alling unde 15 minu es and
a ound 67% wi hin 30 minu es. In conclusion, Île-de-F ance demons a es he highes deg ee o
p oximi y o ec ea ional acili ies among he o he ci ies. Wi h espec o he modal spli , he
p edominan mode o anspo a ion o leisu e a el in all ci ies is walking.
Table 110: Pe cen age o leisu e ips conduc ed o di e en ime s amps – Ci y le el
Ci y Sha e o leisu e ips wi h a du a ion less han (min)
10
15
20
30
Vienna 20.1% 36.0% 46.6% 67.0%
U ech
27.1%
43.0%
50.1%
66.6%
B ussels 27.9% 42.5% 52.4% 70.3%
Budapes
35.1%
47.0%
57.7%
75.0%
Île-de-F ance 42.1% 59.2% 66.4% 80.8%
Munich
24.3%
39.7%
48.9%
67.8%
119
10.2. Ou ski s (Li ing Lab) le el
Figu e 113 p esen s he Cumula i e Dis ibu ion Func ions (CDF) o he ou ski s (Li ing Lab) le el,
ca ego ized acco ding o ip pu pose, and Tables 111 o 114 p esen he pe cen age o wo k,
educa ional, shopping, and leisu e ips conduc ed o di e en ime s amps.
(a) Wo k ips (b) Educa ional ips
(c) Shopping ips (d) Leisu e ips
Figu e 113: Cumula i e dis ibu ion unc ion (CDF) o ip du a ion pe ip pu pose– Ou ski s (Li ing Lab) le el
Figu e 114: Pe cen age o ips comple ed wi hin 15 minu es by ip pu pose – Ou ski s (Li ing Lab) le el
120
Wo k ips
An analysis o wo k ip du a ions in he Li ing Labs (LL) e eals ha Munich LL exhibi s he closes
alignmen wi h he 15mC concep , wi h 37.7% o ips las ing less han 15 minu es and 62.7% occu ing
wi hin 30 minu es, sugges ing enhanced local job accessibili y. A simila pe o mance is obse ed in
B ussels LL, wi h 29.7% o wo k ips alling unde he 15-minu e h eshold and 74.3% wi hin he 30-
minu e ange. The U ech LL exhibi s mode a e alignmen , wi h 26.7% o wo k ips alling unde 15
minu es and a subs an ial 76.7% wi hin 30 minu es. In con as , he Île-de-F ance LL and Vienna LL
exhibi compa a i ely lowe pe cen ages o sho -du a ion commu es, wi h app oxima ely 19-28%
alling unde he 15-minu e ca ego y and a ound 50% wi hin a 30-minu e adius. This indica es a mo e
dispe sed dis ibu ion o employmen cen e s in hese egions. The Budapes LL exhibi s he mos
lacking pe o mance, wi h only 4.9% o ips occu ing unde 15 minu es and a me e 37.2% unde 30
minu es, unde sco ing subs an ial challenges in local job accessibili y. In conclusion, he Munich LL
demons a es he s onges alignmen wi h he 15mC ision, while he Budapes LL exhibi s he leas
alignmen .
Table 111: Pe cen age o wo k ips conduc ed o di e en ime s amps – Ou ski s (Li ing Lab) le el
Li ing Lab Sha e o wo k ips wi h a du a ion less han (min)
10
15
20
30
Vienna
11.8%
19.1%
30.9%
50.0%
U ech 13.3% 26.7% 40.0% 76.7%
B ussels 18.9% 29.7% 54.1% 74.3%
Budapes 1.7% 4.9% 10.1% 37.2%
Île-de-F ance 18.1% 28.1% 36.7% 51.8%
Munich 26.3% 37.7% 46.0% 62.7%
Educa ional ips
In he Li ing Labs, Île-de-F ance and Munich exhibi he mos obus alignmen wi h he 15mC concep
o educa ional excu sions. Île-de-F ance dis inguishes i sel wi h 52.5% o ips comple ed wi hin 15
minu es and 74% wi hin 30 minu es, e lec ing a well-dis ibu ed ne wo k o schools and uni e si ies.
Munich exhibi s a simila pe o mance, wi h 51.4% o ips comple ed in unde 15 minu es and 80.5%
wi hin 30 minu es, sugges ing a compa able le el o accessibili y. B ussels also demons a es a posi i e
pe o mance wi h 48.6% o ips comple ed wi hin 15 minu es and 80% wi hin 30 minu es. Con e sely,
Vienna exhibi s a compa a i ely lowe le el o accessibili y, wi h only 31.8% o educa ional ips alling
wi hin 15 minu es and 56.8% wi hin 30 minu es, sugges ing a less e enly dis ibu ed educa ional
in as uc u e. No ably, da a conce ning U ech and Budapes is una ailable due o insu icien sample
size, impeding comp ehensi e compa a i e analyses. O e all, he Île-de-F ance LL and Munich LL
appea o bes suppo he 15mC ision o educa ion.
Table 112: Pe cen age o educa ional ips conduc ed o di e en ime s amps – Ou ski s (Li ing Lab) le el
Li ing Lab Sha e o educa ional ips wi h a du a ion less han (min)
10
15
20
30
Vienna 20.5% 31.8% 40.9% 56.8%
U ech - - - -
B ussels
34.3%
48.6%
54.3%
80.0%
Budapes
-
-
-
-
Île-de-F ance 43.6% 52.5% 67.2% 74.0%
Munich 31.9% 51.4% 65.6% 80.5%
121
Shopping ips
Among he Li ing Labs, U ech and Munich demons a e op imal accessibili y o shopping ips in
acco dance wi h he 15mC concep . U ech demons a es a no ewo hy dis inc ion wi h 81.9% o ips
comple ed wi hin 15 minu es and an imp essi e 97.9% wi hin 30 minu es, unde sco ing i s obus e ail
accessibili y. Munich exhibi s a compa able pe o mance, wi h 77.3% o ips comple ed in unde 15
minu es and 90.7% wi hin 30 minu es, sugges ing a well-dis ibu ed comme cial ne wo k. Vienna and
Île-de-F ance also demons a e commendable pe o mance, wi h app oxima ely 70% o ips occu ing
wi hin 15 minu es and o e 90% wi hin 30 minu es, indica ing con enien access o shopping
des ina ions. Con e sely, B ussels exhibi s a sligh ly lowe pe o mance, wi h only 60.3% o ips alling
unde 15 minu es and 86.8% wi hin 30 minu es. Budapes exhibi s he leas e icien pe o mance, wi h
only 44.8% o shopping ips unde 15 minu es and 81% wi hin 30 minu es, indica ing a less compac
e ail in as uc u e. In conclusion, i is e iden ha he U ech LL and he Munich LL mos closely align
wi h he 15mC p inciples o shopping accessibili y.
Table 113: Pe cen age o shopping ips conduc ed o di e en ime s amps – Ou ski s (Li ing Lab) le el
Li ing Lab Sha e o shopping ips wi h a du a ion less han (min)
10
15
20
30
Vienna 52.1% 71.9% 79.2% 93.8%
U ech 62.8% 81.9% 89.4% 97.9%
B ussels 48.8% 60.3% 71.1% 86.8%
Budapes
17.2%
44.8%
58.6%
81.0%
Île-de-F ance
49.5%
69.3%
80.2%
93.9%
Munich 62.3% 77.3% 83.9% 90.7%
Leisu e ips
Fo leisu e ips in he Li ing Labs, Île-de-F ance and Munich show he s onges alignmen wi h he
15mC concep . Île-de-F ance leads wi h 58.2% o ips wi hin 15 minu es and 82.2% wi hin 30 minu es,
indica ing widesp ead access o ec ea ional oppo uni ies. Munich ollows closely, wi h 55.2% o ips
less han 15 minu es and 73.4% wi hin 30 minu es, sugges ing a well-dis ibu ed ne wo k o leisu e
des ina ions. B ussels and Budapes show mode a e accessibili y, wi h abou 42% and 37.5% o ips
unde 15 minu es, espec i ely, and nea ly 70% wi hin 30 minu es. U ech LL and Vienna LL ank
lowes , wi h only abou a hi d o leisu e ips wi hin 15 minu es and jus o e hal wi hin 30 minu es,
sugges ing a mo e limi ed p oximi y o leisu e des ina ions. O e all, he Île-de-F ance LL and he Munich
LL bes suppo he 15mC ision o leisu e accessibili y.
Table 114: Pe cen age o leisu e ips conduc ed o di e en ime s amps – Ou ski s (Li ing Lab) le el
Li ing Lab
Sha e o
leisu e
ips wi h a du a ion less han (min)
10
15
20
30
Vienna
10.6%
35.1%
42.6%
58.5%
U ech 17.5% 32.5% 40.0% 55.0%
B ussels 29.9% 42.1% 54.2% 73.8%
Budapes 25.0% 37.5% 48.9% 69.3%
Île-de-F ance 39.3% 58.2% 69.4% 82.2%
Munich 36.9% 55.2% 63.0% 73.4%
128
Age
A9: Modal spli ac oss age g oups - Vienna
A10: T ip du a ion densi y ac oss age g oups and ip pu poses - Vienna
129
A11: T ip du a ion s a is ics ac oss age g oups – Vienna
T ip
Pu pose Age G oup N Mean
(min) SD P (>F)
Wo k
1
25
38.4
17.5
0.009**
2 679 30.8 22.2
3
1026
28.4
18.1
4 93 29.0 18.6
Educa ion
1
411
21.1
15.3
<0.001***
2 219 30.5 18.1
3 37 33.5 18.6
4 Insu icien sample size o analysis
Shopping
1 65 16.2 13.5
0.056
2 388 14.4 13.4
3 579 16.4 18.0
4 711 17.7 23.0
Leisu e
1 220 27.5 29.1
<0.001***
2
516
28.6
23.9
3 577 35.4 41.5
4
588
17.7
23.0
Signi icance le el (
p
-
alue): *
≤0.05, **≤0.01, ***≤0.001
A12: T ip dis ance s a is ics ac oss age g oups – Vienna
T ip
Pu pose Age G oup N Mean
(km) SD P (>F)
Wo k
1 25 9.1 6.6
0.476
2
679
10.1
15.0
3 1026 9.2 10.3
4 93 9.9 19.8
Educa ion
1 411 5.1 9.7
0.003**
2 219 7.4 7.7
3 37 10.9 9.9
4 Insu icien sample size o analysis
Shopping
1
65
3.6
3.6
0.044*
2 388 3.3 6.6
3
579
4.6
10.8
4
711
3.4
7.6
Leisu e
1
220
7.3
14.1
0.013*
2 516 7.5 12.3
3
577
12.6
39.3
4 588 3.4 7.6
Signi icance le el (
p
-
alue): *
≤0.05, **≤0.01, ***≤0.001
130
APPENDIX B
U ech
Gende
B1: Modal spli ac oss gende s – U ech
B2: T ip du a ion densi y ac oss gende s and ip pu poses - U ech
131
B3: T ip du a ion s a is ics ac oss gende s – U ech
T ip
Pu pose Gende N Mean
(min) SD -sco e p- alue
Wo k Male 1336 26.52 21.20 1.183 0.237
Female 1243 25.46 23.86
Educa ion Male 564 20.55 24.56 -1.443 0.149
Female 644 22.48 21.57
Shopping Male 2478 11.87 11.82 -1.184 0.236
Female
2951
12.33
16.74
Leisu e
Male
4082
37.61
48.67
-0.179 0.857
Female
4288
37.80
47.29
Signi icance le el (
p
-
alue): *
≤0.05
B4: T ip dis ance s a is ics ac oss gende s – U ech
T ip
Pu pose Gende N Mean
(km) SD -sco e p- alue
Wo k
Male
1336
16.92
20.19
4.669 <0.05*
Female
1243
13.54
16.47
Educa ion Male 564 6.66 13.06 -0.848 0.397
Female 644 7.28 12.06
Shopping Male 2478 3.50 6.74 1.109 0.268
Female 2951 3.29 7.52
Leisu e Male 4082 8.98 17.17 1.099 0.272
Female 4288 8.56 17.68
Signi icance le el (
p
-
alue): *
≤0.05
Income
B5: Modal spli ac oss income g oups - U ech
132
B6: T ip du a ion densi y ac oss income g oups and ip pu poses - U ech
B7: T ip du a ion s a is ics ac oss income g oups – U ech
T ip
Pu pose
Income
G oup N Mean
(min) SD -sco e p- alue
Wo k
Low
543
26.32
26.51
0.375 0.708
High 2013 25.86 21.29
Educa ion Low 342 23.07 23.03 1.459 0.145
High 841 20.91 23.12
Shopping Low 1516 12.57 12.23 1.512 0.131
High 3831 11.96 15.67
Leisu e
Low
1850
40.27
56.97
2.455 0.014*
High
6411
36.74
44.86
Signi icance le el (
p
-
alue): *
≤0.05 (5%)
B8: T ip dis ance s a is ics ac oss income g oups – U ech
T ip
Pu pose
Income
G oup N Mean
(km) SD -sco e p- alue
Wo k Low 543 11.68 14.71 -6.042 <0.05*
High 2013 16.30 19.39
Educa ion Low 342 6.79 11.56 -0.369 0.712
High
841
7.08
12.95
Shopping Low 1516 3.02 5.89 -2.809 <0.05*
High 3831 3.57 7.68
Leisu e Low 1850 8.57 17.16 -0.565 0.572
High 6411 8.83 17.54
Signi icance le el (
p
-
alue): *
≤0.05 (5%)
133
Age
B9: Modal spli ac oss age g oups - U ech
B10: T ip du a ion densi y ac oss age g oups and ip pu poses – U ech
134
B11: T ip du a ion s a is ics ac oss age g oups – U ech
T ip
Pu pose
Age
G oup N Mean
(min) SD P (>F)
Wo k
1 132 16.89 14.34
<0.001***
2 1020 27.80 21.59
3 999 26.13 24.98
4 380 23.61 19.97
Educa ion
1 963 18.03 20.39
<0.001***
2
181
38.19
26.59
3
43
30.19
31.45
4
21
23.57
16.52
Shopping
1 345 13.93 14.18
0.018*
2 1503 12.05 20.39
3 1747 11.45 11.30
4 1762 12.49 11.69
Leisu e
1 1512 30.13 42.99
<0.001***
2
1020
27.80
21.59
3
181
38.19
26.59
4 1503 12.05 20.39
Signi icance le el (
p
-
alue): *
≤0.05, **≤0.01, ***≤0.001
B12: T ip dis ance s a is ics ac oss age g oups – U ech
T ip
Pu pose
Age
G oup N Mean
(km) SD P (>F)
Wo k
1 132 4.94 6.65
<0.001***
2 1020 16.66 19.61
3 999 16.09 18.44
4 380 12.44 16.57
Educa ion
1 963 4.47 7.57
<0.001***
2
181
19.14
22.09
3
43
11.23
16.40
4 21 8.97 9.22
Shopping
1 345 4.54 10.11
0.006**
2 1503 3.09 6.78
3 1747 3.53 6.94
4 1762 3.28 7.04
Leisu e
1 1512 6.08 12.99
<0.001***
2 1020 9.10 18.26
3 181 9.53 19.25
4 1503 9.39 16.67
Signi icance le el (
p
-
alue): **
≤0.01, ***≤0.001
135
APPENDIX C
BRUSSELS
Gende
C1: Modal spli ac oss gende s – B ussels
C2: T ip du a ion densi y ac oss gende s and ip pu poses - B ussels
136
C3: T ip du a ion s a is ics ac oss gende s – B ussels
T ip
Pu pose Gende N Mean
(min) SD -sco e p- alue
Wo k Male 265 24.25 21.46 -0.107 0.915
Female 339 27.49 20.30
Educa ion Male 146 24.34 22.67 -0.947 0.349
Female 206 24.10 22.35
Shopping Male 501 14.33 15.79 0.144 0.886
Female 685 16.09 17.37
Leisu e Male 531 33.21 42.79 2.724 0.007*
Female
560
28.07
27.24
Signi icance le el (
p
-
alue): *
≤0.05 (5%)
C4: T ip dis ance s a is ics ac oss income gende s – B ussels
T ip
Pu pose Gende N Mean
(km) SD -sco e p- alue
Wo k Male 265 16.15 34.86 0.402 0.688
Female 339 14.29 20.18
Educa ion Male 146 4.91 7.22 -0.419 0.677
Female 206 5.97 11.24
Shopping Male 501 7.64 26.55 0.578 0.564
Female 685 6.08 14.14
Leisu e Male 531 15.65 30.00 2.319 0.021*
Female 560 9.45 20.89
Signi icance le el (
p
-
alue): *
≤0.05 (5%)
Age
C5: Modal spli ac oss age g oups - B ussels
137
C6: T ip du a ion densi y ac oss age g oups and ip pu poses - B ussels
C7: T ip du a ion s a is ics ac oss age g oups – B ussels
T ip
Pu pose Age G oup N
Mean
(min) SD P (>F)
Wo k
1 Insu icien sample size o analysis
0.518
2 197 27.95 16.24
3 302 25.00 15.48
4 Insu icien sample size o analysis
Educa ion
1 246 19.91 2.50
<0.001***
2 70 36.46 9.64
3
28
22.57
10.29
4 Insu icien sample size o analysis
Shopping
1
116
16.29
10.04
0.156
2 262 14.45 8.27
3
397
14.75
6.61
4 251 17.20 3.78
Leisu e
1
193
28.63
12.70
0.02*
2 285 28.78 19.86
3
325
29.33
9.81
4 149 39.21 12.18
Signi icance le el (
p
-
alue): *
≤0.05, **≤0.01, ***≤0.001
144
E6: T ip du a ion densi y ac oss income g oups and ip pu poses - Île-de-F ance
E7: T ip du a ion s a is ics ac oss income g oups – Île-de-F ance
T ip
Pu pose
Income
G oup N
Mean
(min) SD -sco e p- alue
Wo k Low 1048 34.2 31.1 0.200 0.841
High 2480 34.0 27.3
Educa ion Low 620 19.1 21.0 -0.332 0.740
High
1288
19.4
19.8
Shopping
Low
1446
16.4
18.5
0.459 0.647
High 2013 16.1 18.1
Leisu e
Low
1686
25.5
29.5
4.726 <0.05*
High 2915 21.5 23.7
Signi icance le el (
p
-
alue): *
≤0.05 (5%)
E8: T ip dis ance s a is ics ac oss income g oups – Île-de-F ance
T ip
Pu pose
Income
G oup N
Mean
(km) SD -sco e p- alue
Wo k Low 1048 34.2 31.1 -1.552 0.121
High 2480 34.0 27.3
Educa ion Low 620 19.1 21.0 -1.355 0.176
High 1288 19.4 19.8
Shopping Low 1446 16.4 18.5 -3.979 <0.05*
High 2013 16.1 18.1
Leisu e Low 1686 25.5 29.5 1.306 0.192
High 2915 21.5 23.7
Signi icance le el (
p
-
alue): *
≤0.05 (5%)
145
Age
E9: Modal spli ac oss age g oups - Île-de-F ance
E10: T ip du a ion densi y ac oss age g oups and ip pu poses - Île-de-F ance
146
E11: T ip du a ion s a is ics ac oss age g oups – Île-de-F ance
T ip
Pu pose Age G oup N Mean
(min) SD P (>F)
Wo k
1 Insu icien sample size o analysis
0.267
2
1387
34.8
29.4
3 2286 34.3 28.0
4
318
31.4
26.7
Educa ion
1 2021 16.2 15.4
<0.001***
2
236
48.5
32.0
3 Insu icien sample size o analysis
4 Insu icien sample size o analysis
Shopping
1 191 12.5 15.8
<0.001***
2 659 17.0 17.4
3 1334 17.7 20.7
4 1874 15.3 15.8
Leisu e
1
792
17.5
18.2
<0.001***
2 1175 24.5 29.0
3
1462
21.6
27.5
4 1903 25.7 25.2
Signi icance le el (
p
-
alue): *
≤0.05, **≤0.01, ***≤0.001
E12: T ip dis ance s a is ics ac oss age g oups – Île-de-F ance
T ip
Pu pose Age G oup N Mean
(km) SD P (>F)
Wo k
1 Insu icien sample size o analysis
0.007**
2
1387
9.0
11.7
3 2286 9.4 14.4
4 318 6.8 8.8
Educa ion
1 2021 2.0 3.5
<0.001***
2 236 11.2 10.9
3 Insu icien sample size o analysis
4 Insu icien sample size o analysis
Shopping
1
191
2.6
15.1
<0.001***
2 659 3.3 5.8
3
1334
3.7
7.7
4
1874
2.5
7.9
Leisu e
1
792
2.4
8.2
0.004**
2 1175 4.5 16.3
3
1462
4.2
15.9
4 1903 4.2 10.6
Signi icance le el (
p
-
alue): *
≤0.05, **≤0.01, ***≤0.001
147
APPENDIX F
MUNICH
Gende
F1: Modal spli ac oss gende s - Munich
F2: T ip du a ion densi y ac oss gende s and ip pu poses - Munich
148
F3: T ip du a ion s a is ics ac oss gende s – Munich
T ip
Pu pose Gende N Mean
(min) SD -sco e p- alue
Wo k Male 3595 32.4 27.5 1.740 0.082
Female 3178 31.3 26.2
Educa ion Male 1172 23.2 26.2 -0.692 0.489
Female 1124 23.9 21.5
Shopping Male 4134 16.8 21.6 -1.294 0.196
Female 4752 17.4 19.7
Leisu e Male 7432 37.3 47.4 -0.955 0.340
Female
8120
38.0
49.6
Signi icance le el (
p
-
alue): *
≤0.05 (5%)
F4: T ip dis ance s a is ics ac oss gende s – Munich
T ip
Pu pose Gende N Mean
(km) SD -sco e p- alue
Wo k Male 3595 13.4 31.9 4.108 <0.05*
Female 3178 10.6 25.1
Educa ion Male 1172 6.3 24.7 0.881 0.379
Female
1124
5.6
15.1
Shopping Male 4134 4.0 17.4 1.927 0.054
Female 4752 3.4 6.4
Leisu e Male 7432 15.3 47.9 -1.213 0.225
Female 8120 16.4 56.4
Signi icance le el (
p
-
alue): *
≤0.05 (5%)
Income
F5: Modal spli ac oss income g oups - Munich
149
F6: T ip du a ion densi y ac oss income g oups and ip pu poses - Munich
F7: T ip du a ion s a is ics ac oss age g oups – Munich
T ip
Pu pose
Income
G oup N
Mean
(min) SD -sco e p- alue
Wo k Low 301 30.1 18.9 -1.100 0.272
High 4751 31.4 25.9
Educa ion Low 236 29.6 30.4 3.577 <0.05*
High 1686 22.2 23.1
Shopping Low 669 19.0 27.9 2.886 <0.05*
High 4733 15.8 18.8
Leisu e Low 1038 37.9 51.2 0.858 0.391
High
9316
36.5
47.8
Signi icance le el (
p
-
alue):
*
≤0.05 (5%)
F8: T ip dis ance s a is ics ac oss age g oups – Munich
T ip
Pu pose
Income
G oup N Mean
(km) SD -sco e p- alue
Wo k Low 301 9.2 13.0 -3.766 <0.05*
High 4751 12.5 31.7
Educa ion Low 236 8.0 13.4 2.587 <0.05*
High 1686 5.4 20.2
Shopping Low 669 3.3 6.6 -1.644 0.100
High
4733
3.8
15.9
Leisu e Low 1038 9.8 27.3 -6.829 <0.05*
High 9316 16.8 56.2
Signi icance le el (
p
-
alue): *
≤0.05 (5%)
150
Age
F9: Modal spli ac oss age g oups - Munich
F10: T ip du a ion densi y ac oss age g oups and ip pu poses – Munich
151
F10: T ip du a ion s a is ics ac oss age g oups – Munich
T ip
Pu pose Age G oup N Mean
(min) SD P (>F)
Wo k
1
Insu icien sample size o analysis
0.413
2 2666 32.5 28.1
3
3389
31.5
24.1
4 706 31.8 34.3
Educa ion
1
1714
19.1
16.2
<0.001***
2 527 35.6 31.1
3 42 45.0 74.0
4 Insu icien sample size o analysis
Shopping
1 272 17.7 18.8
<0.001***
2 1970 15.8 16.4
3 2869 15.7 21.3
4 3777 18.8 22.1
Leisu e
1 2401 29.5 40.5
<0.001***
2
4200
37.1
49.3
3 4224 38.2 50.7
4
4741
41.9
49.1
Signi icance le el (
p
-
alue): *
≤0.05, **≤0.01, ***≤0.001
F11: T ip dis ance s a is ics ac oss age g oups – Munich
T ip
Pu pose Age G oup N Mean
(km) SD P (>F)
Wo k
1 Insu icien sample size o analysis
0.731
2 2666 12.3 28.6
3 3389 12.0 29.0
4 706 11.5 30.0
Educa ion
1 1714 3.4 5.9
<0.001***
2 527 12.8 36.4
3
42
23.0
64.1
4
Insu icien sample size o analysis
Shopping
1 272 4.0 6.1
0.151
2
1970
3.6
8.1
3 2869 4.1 19.1
4
3777
3.4
8.3
Leisu e
1 2401 12.2 45.5
<0.001***
2
4200
17.5
55.5
3 4224 17.3 54.7
4
4741
15.0
50.9
Signi icance le el (
p
-
alue): *
≤0.05, **≤0.01, ***≤0.001
APPENDIX G
G1: Gende -Based Compa ison o T a el Time (min) a he Ci y Le el
Pedes ian
T ip Pu pose Vienna U ech B ussels Budapes Île-de-F ance Munich
Male Female Male Female Male Female Male Female Male Female Male Female
Wo k 12.37 11.44 12.8 9.4 10.2 11.8 11.4 12.2 10.1 10.0 16.1 17.8
Educa ion 11.07 10.28 8.8 9.1 12.1 10.6 - - 9.7 10.3 13.2 15.1
Shopping 13.21 12.75 10.1 10.2 9.7 11.4 12.0 11.7 9.5 9.9 13.8 14.7
Leisu e 34.06 35.32 41.3 42.1 32.9 27.1 12.5 13.0 15.8 15.3 35.1 35.2
Bicycle
Wo k 19.10 17.60 20.0 20.1 19.6 17.5 23.7 32.3 26.2 25.3 23.7 21.6
Educa ion - - 18.5 16.9 - - - - 19.8 - 15.9 16.2
Shopping
12.12
10.42
11.0
10.6
10.8
9.4
18.8
20.3
15.4
17.7
13.2
13.5
Leisu e 43.83 29.00 36.7 34.8 25.6 29.9 19.5 - 31.9 37.6 29.7 26.0
Ca (as D i e )
Wo k
26.45
23.22
27.5
27.0
28.3
26.8
36.1
35.0
33.1
30.0
29.7
28.6
Educa ion 23.15 - 35.0 28.4 - - - - - - 46.1 42.5
Shopping 17.12 14.77 12.8 13.1 18.1 15.6 20.6 31.4 18.0 16.8 18.2 16.0
Leisu e 31.09 25.57 31.3 26.3 35.0 24.1 32.4 32.4 26.8 23.0 39.0 36.7
Ca (as Passenge )
Wo k - 21.57 29.3 24.5 - - 40.0 - 20.3 18.4 38.7 38.1
Educa ion 17.60 12.41 17.1 18.3 21.3 15.5 - - 13.7 11.3 16.4 17.3
Shopping 19.61 16.59 16.2 16.9 - 15.1 - - 16.6 16.5 19.5 20.5
Leisu e 24.08 31.56 34.2 35.1 34.3 21.7 - 33.2 20.0 23.1 36.6 41.3
Public T anspo
Wo k 38.08 36.53 60.6 51.5 37.6 40.4 44.4 43.5 57.1 53.4 44.5 40.3
Educa ion 31.43 31.94 53.1 58.2 40.3 38.5 - 33.5 41.9 43.6 36.5 37.0
Shopping 26.17 25.39 - 49.4 27.0 32.0 27.4 28.2 41.0 36.4 29.0 29.5
Leisu e
34.42
34.49
69.9
73.9
37.5
37.5
32.7
39.3
48.8
44.1
45.9
49.6
153
G2: Gende -Based Compa ison o T a el Dis ance (km) a he Ci y Le el
Walk
T ip Pu pose Vienna U ech B ussels Budapes Île-de-F ance Munich
Male Female Male Female Male Female Male Female Male Female Male Female
Wo k
1.00
0.88
1.1
0.8
1.5
1.4
0.6
0.6
1.6
1.4
Educa ion
0.95
0.68
0.9
0.7
1.2
1.2
0.6
0.6
0.8
1.0
Shopping 0.88 0.78 0.7 0.7 1.5 1.6 0.5 0.5 0.8 0.8
Leisu e 2.31 2.19 3.0 2.9 3.5 2.5 0.6 0.6 2.1 2.0
Bicycle
Wo k 4.09 3.31 4.7 4.6 6.4 6.6
5.2 3.8 5.7 4.5
Educa ion - - 3.6 3.2 - - 3.2 - 2.6 2.5
Shopping 1.96 1.39 2.0 1.8 2.4 2.8 2.2 2.7 2.1 2.0
Leisu e 9.78 4.50 6.5 5.3 10.6 8.9 5.0 13.1 5.4 4.2
Ca (as D i e )
Wo k
13.07
9.98
23.5
20.5
22.0
22.1
11.9
9.4
16.7
14.9
Educa ion 9.51 - 26.7 18.2 - - - - 36.4 31.1
Shopping 7.87 5.80 6.0 5.7 13.0 7.4 5.2 4.6 7.4 5.3
Leisu e 22.28 16.28 18.4 16.1 29.0 15.0 8.8 6.7 29.4 24.2
Ca (as Passenge )
Wo k - 13.49 18.1 14.9 - -
5.4 5.9 16.6 22.9
Educa ion 6.62 3.94 7.7 8.3 5.1 2.1 2.7 2.1 7.1 5.2
Shopping 8.01 8.23 8.6 8.3 - 12.4 3.1 4.6 7.5 7.6
Leisu e 13.74 21.56 18.4 22.0 37.1 24.3 6.4 6.4 27.8 32.4
Public T anspo
Wo k
11.66
9.56
34.9
25.5
7.7
11.6
15.1
12.5
17.5
11.8
Educa ion 8.05 7.99 30.0 25.8 17.0 7.6 7.4 8.0 9.3 8.8
Shopping 6.15 5.94 - 15.9 2.7 4.7 9.0 7.0 7.4 5.9
Leisu e 12.06 11.28 38.2 37.3 14.1 2.3 10.9 6.8 19.5 26.1
