MétaCan
Menu
Back to cohort
Record W2122401796 · doi:10.1509/jmkr.39.1.47.18930

The Influence and Value of Analogical Thinking during New Product Ideation

2002· article· en· W2122401796 on OpenAlexaff
Darren W. Dahl, Page Moreau

Bibliographic record

VenueJournal of Marketing Research · 2002
Typearticle
Languageen
FieldEngineering
TopicDesign Education and Practice
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsOriginalityAnalogyNew product developmentIdeationContext (archaeology)Product (mathematics)Value (mathematics)Empirical researchPsychologyCognitionProcess (computing)Cognitive psychologyComputer scienceCreativityMarketingSocial psychologyBusinessEpistemologyCognitive scienceMathematics

Abstract

fetched live from OpenAlex

Although both the academic and the trade literature have widely acknowledged the need to foster the development of more-innovative products, little empirical research has examined the cognitive processes underlying the creation of these novel product concepts. In this research, three empirical studies examine how analogical thinking influences the idea-generation stage of the new product development process. The first study uses the verbal protocols of real-world industrial designers to trace the role of analogy in the context of a new product development task, and the second and third studies use an experimental approach to assess the effectiveness of different ideation strategies and conditions. Findings from these studies indicate that the originality of the resulting product design is influenced by the extent of analogical transfer, the type of analogies used, and the presence of external primes. In addition, these studies reveal a positive relationship between the originality of the product concept and consumers' willingness to pay for it, an important measure in the concept-testing phase of product development.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.010
metaresearch head score (Gemma)0.135
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.010
Threshold uncertainty score0.055

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0100.135
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.003
Scholarly communication0.0030.003
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.000

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 head0.050
GPT teacher head0.338
Teacher spread0.287 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations619
Published2002
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Marketing ResearchSame topicDesign Education and PracticeFrench-language works237,207