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Record W2295140105 · doi:10.1109/hicss.2016.205

Enablers and Mechanisms of Value Cocreation in Knowledge-Intensive Business Service Engagements: A Research Synthesis

2016· article· en· W2295140105 on OpenAlexaff
Lysanne Lessard, Chidinma Priscilla Okakwu

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicService and Product Innovation
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsOutsourcingKnowledge managementContext (archaeology)BusinessService (business)Empirical researchValue (mathematics)Component (thermodynamics)Key (lock)Service providerKnowledge baseEmpirical evidenceProcess managementComputer scienceMarketingWorld Wide Web

Abstract

fetched live from OpenAlex

Knowledge-intensive business services (KIBS) such as management consulting, research and development, and IT outsourcing, have become a key component of most industrialized economies. As such, there has been a growing number of empirical studies investigating the way in which KIBS providers, clients, and partners collaboratively create value. These studies provide an important opportunity to improve our understanding of how value cocreation unfolds in the specific context of KIBS engagements. However, their results remain dispersed across the literature and can be difficult to compare. We present an integrated framework of value cocreation enablers and mechanisms developed through a research synthesis integrating the empirical results of 24 articles on this topic. The framework can serve as a basis to guide the design of KIBS engagements. The method of research synthesis is also shown to be a promising means of strengthening the collective knowledge base on service systems.

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.

How this classification was reachedexpand

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.280
Threshold uncertainty score0.492

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
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 head0.075
GPT teacher head0.302
Teacher spread0.227 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations5
Published2016
Admission routes1
Has abstractyes

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