The document discusses structuring user involvement in ICT innovation through a panel-based living lab approach. It provides an overview of living lab conceptualizations and methodologies. A modified consensus definition is presented that describes living labs as medium- to long-term research that cocreates innovations with users in a familiar, real-world context while considering the surrounding ecosystem. The benefits of IBBT-iLab.o's panel-based approach are explained, including how it aids various phases of living lab research projects.
1. Structuring User
Involvement in ICT-
Innovation: a Panel-based
Living Lab-approach
Dimitri Schuurman
Bram Lievens
Lieven De Marez
Pieter Ballon
20/08/2012 1
2. Overview & Methodology
Literature research
Analysis of 9 Living Lab-conceptualizations
Construction of modified Living Lab definition
Assess the implications of panel-based approach
Illustration
Insight into the differences and similarities
between conceptualization and actual
practice in Living Labs
20/08/2012 2
3. Evolution of Innovation Management
Ortt & van der Duin (2008)
Technology push: +/-‘60s
Market pull: +/- ‘70s
No user needs vs. incremental flood
Interactionist approach: +/- ‘80s
Combining both, still in-house
Open innovation: +/- ‘90s- ‘00s
More open process
Cooperation & interaction
Contextual innovation: now
Approach depends on contextual factors
More cyclical & non-linear approach
‘Innofusion’ & ‘social learning’ usage!
3
4. Evolution of Living Labs
Concepts/methods related to Living
Labs Vision on innovation management
Houses of the Future, demohomes Technology or science push
Ethnographic/observational methods Market or need pull
American Living Labs Interactionism
European Living Labs Open Innovation
Panel based Living Lab-approach Contextual innovation
Variety of practices under LL-umbrella:
need for clearer conceptualization
20/08/2012 4
5. Conceptualizing from practice
Living Labs as Test and Experimentation Platform
Commercial maturity lower than in market & societal pilots
Focus less on technical testing than in field trials & testbeds
Living Labs as open innovation platforms
Ballon et al., 2007
20/08/2012 5
6. Conceptualizing from practice (2)
Pierson & Lievens (2005), re-used by Shamsi (2008)
Research phase Actions
an exploration of the technological and social implications of the technology or service under
contextualization
investigation; technological scan and state-of-the-art study
identifying potential users or user groups; this can be done on a socio-demographic level,
selection based on selective or criterion sampling, allowance for theoretical variation of previously defined
concepts
an initial measurement of the selected users on current characteristics, behavior and
concretization
perceptions regarding the research focus, in order to enable a post-measurement
the operationally running test phase of the Living Lab; research methods: direct analysis of
implementation usage by means of remote data collection techniques (e.g. logging), indirect analysis based on e.g.
focus groups, interviews, self-reporting techniques…
an ex-post-measurement of the users (same techniques of initial measurement) and a set of
feedback technological recommendations from the analysis of data gathered during the implementation-
phase, which makes it possible to assess the added-value
20/08/2012 6
7. Conceptualizing from practice (3)
9 general ICT Living Lab-characteristics by Følstad (2008) –
bottom-up approach analyzing 32 Living Labs-papers
1 = Research into the usage context;
2 = Discover unexpected ICT-uses and new service opportunities;
3 = Co-creation with the users;
4 = Evaluation of new ICT-solutions by users;
5 = Technical testing of the innovation in a realistic context;
6 = Familiar usage context for the users;
7 = Experience and experiment in a real-world context;
8 = Medium- or long-term user studies;
9 = Large scale user studies.
20/08/2012 7
8. Conceptualizing from practice (3)
9 general ICT Living Lab-characteristics by Følstad (2008) –
bottom-up approach analyzing 32 Living Labs-papers
1 = Research into the usage context;
2 = Discover unexpected ICT-uses and new service opportunities;
3 = Co-creation with the users;
4 = Evaluation of new ICT-solutions by users;
5 = Technical testing of the innovation in a realistic context;
6 = Familiar usage context for the users;
7 = Experience and experment in a real-world context;
8 = Medium- or long-term user studies;
9 = Large scale user studies.
Only 4 ‘shared’ characteristics!
Another indication of the conceptual ambiguity of the Living Lab-concept
20/08/2012 8
9. Analysis of LL-conceptualizations
ENoLL-related scholars 1 2 3 4 5 6 7 8 9
Frissen & van Lieshout, 2004 X X X X X
Pasman, Stappers et al., 2005 X X X X X X
Eriksson, Niitamo et al., 2006 X X X X X X X X
Ballon, Pierson et al., 2007 X X X X
Feurstein, Hesmer et al., 2008 X X X X
Ståhlbröst & Bergvall-Kåreborn, 2008 X X X X X X X X X
Almirall & Wareham, 2009 X X X X
Turkama, 2010 X X X X X X
Mahr & Schuurman, 2011 X X X X X X X X
Sum /9 4 5 9 3 2 9 9 9 4
20/08/2012 9
10. Analysis of LL-conceptualizations
ENoLL-related scholars 1 2 3 4 5 6 7 8 9
Frissen & van Lieshout, 2004 X X X X X
Pasman, Stappers et al., 2005 X X X X X X
Eriksson, Niitamo et al., 2006 X X X X X X X X
Ballon, Pierson et al., 2007 X X X X
Feurstein, Hesmer et al., 2008 X X X X
Ståhlbröst & Bergvall-Kåreborn, 2008 X X X X X X X X X
Almirall & Wareham, 2009 X X X X
Turkama, 2010 X X X X X X
Mahr & Schuurman, 2011 X X X X X X X X
Sum /9 4 5 9 3 2 9 9 9 4
2 = Discover unexpected ICT-uses and 3 = Co-creation with the users;
new service opportunities; 6 = Familiar usage context for the users;
4 = Evaluation of new ICT-solutions by 7 = Experience and experiment in a
users; real-world context;
6 = Familiar usage context for the users; 8 = Medium- or long-term user studies;
8 = Medium- or long-term user studies;
20/08/2012 10
11. Modified consensus definition
A Living Lab-approach consists of medium- or
long-term research co-creating innovations
with users in a familiar and real-world context,
taking into account the ecosystem surrounding
the innovation.
Missing aspect: where to get your users?
20/08/2012 11
12. IBBT-iLab.o’s panel-based approach
IBBT: Flemish (virtual) research institute, incubator and
innovation intermediary for ICT, funded by Flemish government
Mission: IBBT aims to add economic and social value through
excellent research and the creation of human capital in the
domain of ICT
12
13. iLab.o: IBBT’s Living Lab-division
Panel Living Lab Prototyping & Simulate Your European
Management Methodology testing Business Network of
Living Labs
We’ll find and We’ll show you how We’ll model a rough Draw, discuss and
motivate your test- to set up a living lab idea into a usable simulate your value
project app for daily life and chain and business iLab.o hosts the
users Brussels Office for
test it through model on the fly
ENoLL
A A toolbox for any project type: ICON, Living Lab, CIP, FP7, …
toolbox for any project type: ICON, Living Lab, CIP, FP7, …
13
14. The iLab.o Living Lab-approach
Baseline Live-phase Added Value
measurement assessment
•SotA Market: • Field Trials • Exit and
Environmental • User Research Debriefing
scan • Logging • Post-usage
•SotA User: • Intermediary co- Validation
Current habits & creation • Business Model
practices sessions Simulation
•Selection Test • Added Lab Tests
Users from (isolating
existing user Variables)
panels
•co-creation
sessions
15. Added value of panel based-approach
1) contextualization: through the longitudinal data the panel
generates, a permanent ‘contextualization’ is taking place for the
surveyed topics
2) selection: the identification test-users is only a matter of selecting
the right profiles out of the panel database. This avoids the time-
and budget consuming surveying and recruiting of relevant user
profiles.
3) concretization: a lot of data already present, so only a brief extra
intake survey is required
4) implementation: panel members have ‘opted in’, panel
management ensures practical organisation of research activities &
device handling, panel manager as SPOC
5) feedback: all data added with existing panel data to further add to
profile building
20/08/2012 PANEL WITH THEMATIC FOCUS! 15
16. Illustration: LeYLab Living Lab
Sept 2010
11 industrial partners
IBBT-iLab.o as
research partner
Fibre internet
connection
20/08/2012 16
17. LeYLab panel
115 fibre connections
32% course surfing
98 households 35% course SNS
43 tablets 58% course working with
computer/tablet
36 mini PC
>200 profiled panel
members
3% has already developed
innovative apps
10% has innovative ideas
regarding the Internet
20% is among the first to
test innovative apps
19. Conclusions
Living Labs as promising innovation methodology,
involving the end-user as key stakeholder through
co-creation
Still a large variety in definitions and concrete set-
ups of Living Labs
Added-value of a panel-based approach, in practice
especially for entrepeneurs & start-ups
19
22. Results of codings (N= 64)
Characteristics Mean % high % low
1 = Research into the usage context 2,20 34,4% 65,6% 4
2 = Discover unexpected ICT-uses and new service opportunities 2,19 29,7% 70,3% 5
3 = Co-creation with the users 2,55 50% 50% 9
4 = Evaluation of new ICT-solutions by users 2,63 50% 50% 3
5 = Technical testing of the innovation in a realistic context 2,56 48,4% 51,6% 2
6 = Familiar usage context for the users 3,05 71,9% 28,1% 9
7 = Experience and experiment in a real-world context 2,44 54,1% 46,9% 9
8 = Medium- or long-term user studies 3,61 91,9% 8,1% 9
9 = Large scale user studies 2,36 50,8% 49,2% 4
Sum /9
Co-creation with the users only in half of the sample
20/08/2012 22
23. Results of codings (N= 64)
Characteristics Mean % high % low
1 = Research into the usage context 2,20 34,4% 65,6% 4
2 = Discover unexpected ICT-uses and new service opportunities 2,19 29,7% 70,3% 5
3 = Co-creation with the users 2,55 50% 50% 9
4 = Evaluation of new ICT-solutions by users 2,63 50% 50% 3
5 = Technical testing of the innovation in a realistic context 2,56 48,4% 51,6% 2
6 = Familiar usage context for the users 3,05 71,9% 28,1% 9
7 = Experience and experiment in a real-world context 2,44 54,1% 46,9% 9
8 = Medium- or long-term user studies 3,61 91,9% 8,1% 9
9 = Large scale user studies 2,36 50,8% 49,2% 4
Sum /9
Co-creation with the users only in half of the sample
Familiar usage context more often than real-world context
20/08/2012 23
24. Results of codings (N= 64)
Characteristics Mean % high % low
1 = Research into the usage context 2,20 34,4% 65,6% 4
2 = Discover unexpected ICT-uses and new service opportunities 2,19 29,7% 70,3% 5
3 = Co-creation with the users 2,55 50% 50% 9
4 = Evaluation of new ICT-solutions by users 2,63 50% 50% 3
5 = Technical testing of the innovation in a realistic context 2,56 48,4% 51,6% 2
6 = Familiar usage context for the users 3,05 71,9% 28,1% 9
7 = Experience and experiment in a real-world context 2,44 54,1% 46,9% 9
8 = Medium- or long-term user studies 3,61 91,9% 8,1% 9
9 = Large scale user studies 2,36 50,8% 49,2% 4
Sum /9
Co-creation with the users only in half of the sample
Familiar usage context more often than real-world context
Lack of research into the actual usage context
Lack of discovery of unexpected usage or new
opportunities
20/08/2012 24
25. Results of codings (N= 64)
Characteristics Mean % high % low
1 = Research into the usage context 2,20 34,4% 65,6% 4
2 = Discover unexpected ICT-uses and new service opportunities 2,19 29,7% 70,3% 5
3 = Co-creation with the users 2,55 50% 50% 9
4 = Evaluation of new ICT-solutions by users 2,63 50% 50% 3
5 = Technical testing of the innovation in a realistic context 2,56 48,4% 51,6% 2
6 = Familiar usage context for the users 3,05 71,9% 28,1% 9
7 = Experience and experiment in a real-world context 2,44 54,1% 46,9% 9
8 = Medium- or long-term user studies 3,61 91,9% 8,1% 9
9 = Large scale user studies 2,36 50,8% 49,2% 4
Sum /9
Co-creation with the users only in half of the sample
Familiar usage context more often than real-world context
Lack of research into the actual usage context
Lack of discovery of unexpected usage or new
opportunities
Medium- or long term is a given, large scale is not
20/08/2012 25