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MASTERING
TRANSFORMATION
NO
MYSTIC
SELF-
CONTAINED
SELF-
DRIVEN
JANUARY
1st
MEDIATED
ALGORITHMIC
MODERATED
USER
BEHAVIOR
USER
CONTENT
DYNAMIC
DESIGN
DYNAMIC
CONTENT
PERSUASIVE
DESIGN
TRIANGLE
CURVE
METRIC
CIRCLES
ARCHITECTURE
SOCIUM
MODERATION
ETHICS
CT
COMPETITION
SL
LEARNING
SC
COMPARISON
CR
COOPERATION
NI
NORMATIVE
SF
FACILITATION
RE
RECOGNITION
INVOLVEMENT
ENGAGEMENT
PARTICIPATION
POSITIVENEGATIVE
INTENDED
UNINTENDED
MAJOR MINOR
HIGH
LOW
BACKFIRING
TARGET
SURPRISE
DARK GREY
INVISIBLE
VISIBLE
DARK
1
2 3
4
5
6
7
8
TRANSFORMING
CHANGE CARE SOCIOTECH DESIGN
INTELLIGENCE
CLASSIFY UNDERSTAND ANALYTICS
DATA
READ FEEL SENSORS
120
2014
€ 30 000 000
FROM/VON
2010 —
TO/BIS
2014
Highlights
Radwege-Bauprojekte
Wichtige Radprojekte, in den Jahren 2010 bis 2014
umgesetzt: 1: Ottakringer Straße, 2: Ring-Rund-Radweg,
3: Radwege rund um den Hauptbahnhof, 4: Landstraßer
Gürtel, 5: Zentrum Meidling, 6: Kagraner Platz,
7: fahrradfreundliche Hasnerstraße
Generelle Radverkehrsplanung
und Studien
Auswahl aus Konzepten und Studien: Radlangstrecken und
Lückenschlüsse, befahrbare Haltestellenkaps für RadfahrerInnen,
Piktogramme und Pfeile zur Erhöhung der Verkehrssicherheit,
Radfahren gegen die Einbahn
1
2
4
5
6
3
7
Radfahren
gegen
die Einbahn
+16%
StVO-Novelle umgesetzt
Fahrradstraße: 1.650 m
Benutzungspflicht bei Radwegen aufgehoben: 1.970 m
Begegnungszonen: 1.200 m
Detailplanung
Mehr als 600 Einzelmaßnahmen für den (fließenden und ruhenden)
Radverkehr pro Jahr, unter breiter interdisziplinärer Beteiligung
am Planungs- und Umsetzungsprozess: Dienststellen, Bezirke,
Wirtschaftskammer, Polizei etc. (bis zu 30 Beteiligte)
Radfahrnetz
Citybike-Stationen
+96 km
2010
Budget für die
Radinfrastruktur
Millionen
Euro
(6 Mio. p.a.)
30
79
2010
Winterdienst
266 km prioritär geräumte Radwege
Errichtete Radabstellplätze
2010
+9.588
27.329 Stück
2014
36.917 Stück
2014
1.270 km
1.174 km
Radinfrastruktur 2010–2014
Tempo-30-Zonen in Wien
Befahrbare
Haltestellenkaps für
RadfahrerInnen
Radlangstrecken
Piktogramme
und Pfeile
zur Erhöhung der
Verkehrs-
sicherheit
Radfahren
gegen
die Einbahn
Modal Split Radverkehr
Anteil des Radverkehrs an den zurückgelegten
Wegen der Wienerinnen und Wienern
2010: 1.472 km
2014: 1.657 km
4,6%
7,1%
2010
2014
EINBAHN
ausgen.
2010
208.790 m
ausgen.
242.420 m
EINBAHN
2014
Impressum: Magistrat der Stadt Wien, Rathaus, A-1082 Wien, www.verkehr.wien.at
https://scottbreslin.org/2016/08/transformation-vs-change/
DIET 1
DIET 2
DIET 3
175 lbs
190 lbs
180 lbs
200 lbs
185 lbs
???
0.99365 = 0.03
1.01365 = 37.78
INTELLIGENT
INSTINCTIVE
2 1
SOURCE: ONLINE
https://www.engageandprosper.com/approaches/the-carrothttps://www.engageandprosper.com/approaches/the-stick
TODAY
ONLY
%
TRANSACTION TRANSITION TRANSFORMATION
DOT DURATION DIRECTION
1 PERIOD ENDLESS
TRANSACTION TRANSITION TRANSFORMATION
DOT DURATION DIRECTION
1 PERIOD ENDLESS
2
1
PERSUASION
?
SOURCE: ONLINE
SOCIAL
INFLUENCE
2019
Empowering Sustainable Change: Emergence of
Transforming Wellbeing Theory
Agnis Stibe1
, Kathrin Röderer2
, Michaela Reisinger2
, and Tobias Nyström3
1
ESLSCA Business School Paris, France
agnis@transforms.me
2
Austrian Institute of Technology, Austria
{kathrin.roederer, michaela.reisinger}@ait.ac.at
3
Uppsala University, Sweden
tobias.nystrom@im.uu.se
Abstract. Majority of global problems and business challenges are byproducts
1SOURCE: ONLINE
2
INSTINCTIVE
1
SOURCE: ONLINE
FRAGILE
CAREFUL
TV
IMAGE
1
TRIANGLE
1
INSTINCTIVE
1
SOURCE: ONLINE
INTELLIGENT
2
SOURCE: ONLINE
INTELLIGENT
?
ATTITUDE
BEHAVIOR
ENVIRONMENT
-
+
+
2
TRIANGLE
CURVE
1
2
INTELLIGENT
INSTINCTIVE
? ?
SOURCE: ONLINE
SOURCE: ONLINE
https://www.piaggiofastforward.com/gitaSOURCE: ONLINE
SOURCE: MIT
SOURCE: MIT
SOURCE: ONLINE
SOURCE: ONLINE
SOURCE: MIT
SOURCE: ONLINE
SOURCE: MIT
PEOPLE METRIC
BEHAVIOR TODAY
TRANSFORMATION FUTURE
3
TRIANGLE
CURVE
METRIC
1
2 3
http://inspiration.goreapparel.com/cycling-to-work/
https://echristensen42.com/2016/10/07/creating-your-own-pathways-through-the-cloud/usesidewalks/
10 0001
SELF-
CONTAINED
SELF-
DRIVEN
JANUARY
1st
SELF-
DRIVEN
SELF-
CONTAINED
JANUARY
1st
4
SOURCE: ONLINE
SELF-
CONTAINED
SELF-
DRIVEN
JANUARY
1st
TRIANGLE
CURVE
METRIC
CIRCLES
1
2 3
4
WELLBEING IN MY CITY
I SEE HOW MY CITY DEVELOPS IN LINE WITH NOVEL
TECHNOLOGIES AND INNOVATIONS. I WILL HAVE A HEALTHY
LIFE HERE. COMMUNITIES HAVE STRONG COLLABORATIVE
SPIRIT TOWARDS WELLBEING. I WILL BE ABLE TO FULFIL
MYSELF. I WOULD SPEND MORE TIME OUTSIDE OF MY HOME
TO INTERACT WITH OTHERS. WE WILL HAVE NICELY
DESIGNED PUBLIC SPACES FOR THE RESIDENTS OF ALL AGES.
TRANSFORMING
CHANGE CARE SOCIOTECH DESIGN
INTELLIGENCE
CLASSIFY UNDERSTAND AI / BIG DATA
DATA
READ FEEL SENSORS 5
SELF-
CONTAINED
SELF-
DRIVEN
JANUARY
1st
TRANSFORMING
CHANGE CARE SOCIOTECH DESIGN
INTELLIGENCE
CLASSIFY UNDERSTAND AI / BIG DATA
DATA
READ FEEL SENSORS
TRANSFORMING
CHANGE CARE SOCIOTECH DESIGN
SMART
CLASSIFY UNDERSTAND AI / BIG DATA
SENSING
READ FEEL SENSORS
TRIANGLE
CURVE
METRIC
CIRCLES
ARCHITECTURE
1
2 3
4
5
Persuasive Cities for Sustainable Wellbeing:
Quantified Communities
Agnis Stibe(&)
and Kent Larson
MIT Media Lab, Cambridge, USA
{agnis,kll}@mit.edu
Abstract. Can you imagine a city that feels, understands, and cares about your
wellbeing? Future cities will reshape human behavior in countless ways. New
strategies and models are required for future urban spaces to properly respond to2016
https://vimeo.com/287397858SOURCE: ONLINE
https://techcrunch.com/2016/07/22/bad-ux-kills/
http://www.thisiscolossal.com/2014/10/lets-bike-it-bamboo-car-skeletons/
SOURCE: ONLINE
SOURCE: ONLINE
1000
640
790
430
820
SOURCE: MIT
CT
COMPETITION
SL
LEARNING
SC
COMPARISON
CR
COOPERATION
NI
NORMATIVE
SF
FACILITATION
RE
RECOGNITION
SOCIAL INFLUENCE
Downward Upward
Injunctive Descriptive
Goal Gain
Goal Together
Participants Onlookers
INVOLVEMENT PARTICIPATION ENGAGEMENT
Towards a Framework for Socially Influencing Systems:
Meta-analysis of Four PLS-SEM Based Studies
Agnis Stibe( )
MIT Media Lab, Cambridge, MA, USA
agnis@mit.edu
Abstract. People continuously experience various types of engagement through
social media, mobile interaction, location-based applications, and other tech-
nologically advanced environments. Often, integral parts of such socio- 2015
SELF-
CONTAINED
SELF-
DRIVEN
JANUARY
1st
TRANSFORMING
CHANGE CARE SOCIOTECH DESIGN
SMART
CLASSIFY UNDERSTAND AI / BIG DATA
SENSING
READ FEEL SENSORS
TRIANGLE
CURVE
METRIC
CIRCLES
ARCHITECTURE
SOCIUM
CT
COMPETITION
SL
LEARNING
SC
COMPARISON
CR
COOPERATION
NI
NORMATIVE
SF
FACILITATION
RE
RECOGNITION
INVOLVEMENT
ENGAGEMENT
PARTICIPATION
1
2 3
4
5
6
SOURCE: ONLINE
0
1
2
3
4
5
6
7
8
Sunny Andrew Gerbert Leen Isabel Rosa Ingrid Anita Albert George Gina Rita
Nov-13 Nov-14 Nov-20 Nov-27 Nov-28 Dec-01 Dec-05
0%
20%
40%
60%
80%
100%
120%
Nov-13 Nov-14 Nov-20 Nov-27 Nov-28 Dec-01 Dec-05
MOTIVATED
COLLEAGUES HESITANT
DEMOTIVATED
0
1
2
3
4
5
6
7
8
Sunny Andrew Gerbert Leen Isabel Rosa Ingrid Anita Albert George Gina Rita
Nov-13 Nov-14 Nov-20 Nov-27 Nov-28 Dec-01 Dec-05
Advancing Typology of Computer-Supported Influence:
Moderation Effects in Socially Influencing Systems
Agnis Stibe( )
MIT Media Lab, Cambridge, MA, USA
agnis@mit.edu
Abstract. Persuasive technologies are commonly engineered to change beha-
vior and attitudes of users through persuasion and social influence without us-
ing coercion and deception. While earlier research has been extensively focused 2015
SELF-
CONTAINED
SELF-
DRIVEN
JANUARY
1st
TRANSFORMING
CHANGE CARE SOCIOTECH DESIGN
SMART
CLASSIFY UNDERSTAND AI / BIG DATA
SENSING
READ FEEL SENSORS
MEDIATED
ALGORITHMIC
MODERATED
USER
BEHAVIOR
USER
CONTENT
DYNAMIC
DESIGN
DYNAMIC
CONTENT
PERSUASIVE
DESIGN
TRIANGLE
CURVE
METRIC
CIRCLES
ARCHITECTURE
SOCIUM
MODERATION
CT
COMPETITION
SL
LEARNING
SC
COMPARISON
CR
COOPERATION
NI
NORMATIVE
SF
FACILITATION
RE
RECOGNITION
INVOLVEMENT
ENGAGEMENT
PARTICIPATION
1
2 3
4
5
6
7
SOURCE: ONLINE
POSITIVENEGATIVE
INTENDED
UNINTENDED
MAJOR MINOR
HIGH
LOW
BACKFIRING
TARGET
SURPRISE
DARK GREY
INVISIBLE
VISIBLE
DARK
8
Persuasive Backfiring: When Behavior Change
Interventions Trigger Unintended
Negative Outcomes
Agnis Stibe1(&)
and Brian Cugelman2,3
1
MIT Media Lab, Cambridge, MA, USA
agnis@mit.edu
2
Statistical Cybermetrics Research Group,
University of Wolverhampton, Wolverhampton, UK
brian@alterspark.com
3
AlterSpark, Toronto, ON, Canada
2016
SELF-
CONTAINED
SELF-
DRIVEN
JANUARY
1st
TRANSFORMING
CHANGE CARE SOCIOTECH DESIGN
SMART
CLASSIFY UNDERSTAND AI / BIG DATA
SENSING
READ FEEL SENSORS
MEDIATED
ALGORITHMIC
MODERATED
USER
BEHAVIOR
USER
CONTENT
DYNAMIC
DESIGN
DYNAMIC
CONTENT
PERSUASIVE
DESIGN
TRIANGLE
CURVE
METRIC
CIRCLES
ARCHITECTURE
SOCIUM
MODERATION
ETHICS
CT
COMPETITION
SL
LEARNING
SC
COMPARISON
CR
COOPERATION
NI
NORMATIVE
SF
FACILITATION
RE
RECOGNITION
INVOLVEMENT
ENGAGEMENT
PARTICIPATION
POSITIVENEGATIVE
INTENDED
UNINTENDED
MAJOR MINOR
HIGH
LOW
BACKFIRING
TARGET
SURPRISE
DARK GREY
INVISIBLE
VISIBLE
DARK
1
2 3
4
5
6
7
8
SOURCE: HIGI
0
0,5
1
1,5
2
2,5
TOTAL WEIGHT
+20%
+32%
Transforming Cities and Communities for Sustainable Wellbeing

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