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Record W1993830319 · doi:10.1016/j.ausmj.2011.10.009

Making a Face: Graphical Illustrations of Managerial Stances toward Customer Creativity

2011· article· en· W1993830319 on OpenAlexaff
Pierre Berthon, Leyland Pitt, Ian P. McCarthy, Kirk Plangger

Bibliographic record

VenueAustralasian Marketing Journal (AMJ) · 2011
Typearticle
Languageen
FieldEngineering
TopicDesign Education and Practice
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsMarketingCreativityBusinessFace (sociological concept)Value (mathematics)RevenueTypologyBusiness modelAction (physics)Intellectual propertyComputer scienceSociologyPsychology

Abstract

fetched live from OpenAlex

Creative consumers – consumers who adapt, modify or transform a proprietary offering – represent an intriguing paradox for business. On the one hand they can be a black hole for future revenue, with breach of copyright and intellectual property, while on the other hand they represent a gold mine of ideas and business opportunities. This problem is central to business – business needs to both create and capture value; the problem is that creative consumers demand a shift in the mindsets and business models of how firms both create and capture value. We develop a typology of firms’ stances to creative consumers based upon their attitude and action towards customer innovation. We then consider the implications of the stances model for corporate strategy, and examine a three-step approach to dealing with creative consumers, namely, awareness, analysis and response.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.653
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.066
GPT teacher head0.303
Teacher spread0.237 · 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.

Study designObservational
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

Citations3
Published2011
Admission routes1
Has abstractyes

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