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Record W1959212851 · doi:10.1108/jkm-02-2015-0058

Living Lab as knowledge system: an actual approach for managing urban service projects?

2015· article· en· W1959212851 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Knowledge Management · 2015
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicInnovative Approaches in Technology and Social Development
Canadian institutionsSociety for Arts and TechnologyUniversité de SherbrookeUniversité du Québec à Montréal
Fundersnot available
KeywordsKnowledge managementGeneral partnershipContext (archaeology)NormativeService (business)Body of knowledgeSociologyComputer scienceBusinessPolitical scienceMarketing

Abstract

fetched live from OpenAlex

Purpose – This paper aims to explore Living Labs (LL) as knowledge systems for urban service projects. This empirical study aims to identify and characterize knowledge in LL dedicated to urban service projects. It also aims to understand how through knowledge path, LL redefine the management of projects. First, the praxeologic and academic context underlining the main challenges associated to urban service projects is presented. It mainly concerns the growth of the cities (Haouès-Jouve, 2013), the problematic of social acceptability (Savard, 2013) as well as the normative approaches to manage projects (Kerzner, 2010). Second, a literature review on co-innovation and Livings Labs is presented. (Chesbrough, 2004; Gaglio, 2011). This paper also presents the concept of knowledge applied in an LL system (Sanders and Stappers, 2008). Here, knowledge refers to dynamic knowledge, as suggested by Argyris (1995). Design/methodology/approach – In the third part, the goals of this study as well as the abductive and “partnership” qualitative methodology that was used are explained (Fontan and René, 2014). The constitutive and the operational definitions on knowledge that have been mobilized are detailed (Piaget, 1974; Gadille, 2012). A special focus is made, here, on distributed knowledge (Nowotny et al. , 2002; Trepos, 1996), on “users” as “experts of uses” (Chen et al. , 2010). Then, the sample and the four cases of LL that were explored are described. Findings – Finally, the findings are presented. This paper exposed how knowledge lying in the loops of the LL system was characterized and how knowledge is mobilized in an LL. This paper also draws a theoretical model of project management referring to knowledge, LL and co-innovation approach. Research limitations/implications – To conclude, several implications in project management research and urban studies are presented. Practical implications – Several implications concern the current practices of project management. Due to some new societal challenges, it is considered that a new professional posture is required. Social implications – Several implications concern citizens as users and stakeholders of urban projects. Originality/value – The originality of the study lies in its content and its format. A specific participative approach was used to explore LL. This paper investigated knowledge in LL, which are new entities dedicated to very actual projects, where users are co-managers.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.930
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.059
GPT teacher head0.279
Teacher spread0.220 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it