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Structuring User Involvement Dimitri Schuurman et al summer school research day
 

Structuring User Involvement Dimitri Schuurman et al summer school research day

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3rd ENoLL Living Lab Summer School

3rd ENoLL Living Lab Summer School

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    Structuring User Involvement Dimitri Schuurman et al summer school research day Structuring User Involvement Dimitri Schuurman et al summer school research day Presentation Transcript

    • Structuring User Involvement in ICT- Innovation: a Panel-based Living Lab-approach Dimitri Schuurman Bram Lievens Lieven De Marez Pieter Ballon20/08/2012 1
    • Overview & Methodology Literature research Analysis of 9 Living Lab-conceptualizations Construction of modified Living Lab definition Assess the implications of panel-based approach IllustrationInsight into the differences and similaritiesbetween conceptualization and actualpractice in Living Labs 20/08/2012 2
    • Evolution of Innovation ManagementOrtt & 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
    • Evolution of Living Labs Concepts/methods related to Living Labs Vision on innovation managementHouses of the Future, demohomes Technology or science pushEthnographic/observational methods Market or need pullAmerican Living Labs InteractionismEuropean Living Labs Open InnovationPanel based Living Lab-approach Contextual innovation  Variety of practices under LL-umbrella: need for clearer conceptualization 20/08/2012 4
    • 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
    • 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 undercontextualization 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 andconcretization 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 ofimplementation 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 offeedback 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
    • 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
    • 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
    • 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
    • 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 42 = 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 ausers; 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
    • 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
    • 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
    • iLab.o: IBBT’s Living Lab-divisionPanel Living Lab Prototyping & Simulate Your EuropeanManagement Methodology testing Business Network of Living LabsWe’ll find and We’ll show you how We’ll model a rough Draw, discuss andmotivate 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 theusers 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
    • The iLab.o Living Lab-approachBaseline Live-phase Added Valuemeasurement 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
    • 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
    • Illustration: LeYLab Living Lab Sept 2010 11 industrial partners IBBT-iLab.o as research partner Fibre internet connection 20/08/2012 16
    • 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
    • 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
    • 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
    • [E]: Dimitri.Schuurman@UGent.be [W]: www.mict.be www.ibbt.be www.leylab.be www.mediatuin.be
    • Framework for customer characteristics 20/08/2012 21
    • Results of codings (N= 64)Characteristics Mean % high % low1 = Research into the usage context 2,20 34,4% 65,6% 42 = Discover unexpected ICT-uses and new service opportunities 2,19 29,7% 70,3% 53 = Co-creation with the users 2,55 50% 50% 94 = Evaluation of new ICT-solutions by users 2,63 50% 50% 35 = Technical testing of the innovation in a realistic context 2,56 48,4% 51,6% 26 = Familiar usage context for the users 3,05 71,9% 28,1% 97 = Experience and experiment in a real-world context 2,44 54,1% 46,9% 98 = Medium- or long-term user studies 3,61 91,9% 8,1% 99 = Large scale user studies 2,36 50,8% 49,2% 4Sum /9  Co-creation with the users only in half of the sample 20/08/2012 22
    • Results of codings (N= 64)Characteristics Mean % high % low1 = Research into the usage context 2,20 34,4% 65,6% 42 = Discover unexpected ICT-uses and new service opportunities 2,19 29,7% 70,3% 53 = Co-creation with the users 2,55 50% 50% 94 = Evaluation of new ICT-solutions by users 2,63 50% 50% 35 = Technical testing of the innovation in a realistic context 2,56 48,4% 51,6% 26 = Familiar usage context for the users 3,05 71,9% 28,1% 97 = Experience and experiment in a real-world context 2,44 54,1% 46,9% 98 = Medium- or long-term user studies 3,61 91,9% 8,1% 99 = Large scale user studies 2,36 50,8% 49,2% 4Sum /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
    • Results of codings (N= 64)Characteristics Mean % high % low1 = Research into the usage context 2,20 34,4% 65,6% 42 = Discover unexpected ICT-uses and new service opportunities 2,19 29,7% 70,3% 53 = Co-creation with the users 2,55 50% 50% 94 = Evaluation of new ICT-solutions by users 2,63 50% 50% 35 = Technical testing of the innovation in a realistic context 2,56 48,4% 51,6% 26 = Familiar usage context for the users 3,05 71,9% 28,1% 97 = Experience and experiment in a real-world context 2,44 54,1% 46,9% 98 = Medium- or long-term user studies 3,61 91,9% 8,1% 99 = Large scale user studies 2,36 50,8% 49,2% 4Sum /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
    • Results of codings (N= 64)Characteristics Mean % high % low1 = Research into the usage context 2,20 34,4% 65,6% 42 = Discover unexpected ICT-uses and new service opportunities 2,19 29,7% 70,3% 53 = Co-creation with the users 2,55 50% 50% 94 = Evaluation of new ICT-solutions by users 2,63 50% 50% 35 = Technical testing of the innovation in a realistic context 2,56 48,4% 51,6% 26 = Familiar usage context for the users 3,05 71,9% 28,1% 97 = Experience and experiment in a real-world context 2,44 54,1% 46,9% 98 = Medium- or long-term user studies 3,61 91,9% 8,1% 99 = Large scale user studies 2,36 50,8% 49,2% 4Sum /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