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
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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
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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!
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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
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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
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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
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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.
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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
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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
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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;
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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?
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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
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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, …
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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
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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

18. Project CloudFriends (home network diagnostics app)
SotA-research: habits Co-creation session
& practices network with experts & Lead
problems users Test user Post-usage
co-creation session validation
Phase 1 Phase 2 Phase 3
1st iteration
CloudFriends-app
2nd iteration
CloudFriends-app
Initial concept
CloudFriends-app

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

20. [E]: Dimitri.Schuurman@UGent.be
[W]:
www.mict.be
www.ibbt.be
www.leylab.be
www.mediatuin.be

21. Framework for customer characteristics
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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
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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
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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
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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
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