MétaCan
Menu
Back to cohort

Seeing Is Believing (Too Much): The Influence of Product Form on Perceptions of Functional Performance

2011· article· en· W1871955902 on OpenAlexaff
JoAndrea Hoegg, Joseph W. Alba

Bibliographic record

VenueJournal of Product Innovation Management · 2011
Typearticle
Languageen
FieldPsychology
TopicColor perception and design
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsFeature (linguistics)Product (mathematics)PerceptionFunction (biology)Process (computing)New product developmentComputer scienceMarketingCognitive psychologyPsychologyBusinessMathematicsLinguistics

Abstract

fetched live from OpenAlex

The present research investigates the manner in which product form communicates functional performance, and examines how the form of a product can alter judgments about feature function. In a series of experiments, product form is pitted against objective information about feature function to understand how conflicting visual and verbal cues are reconciled. The findings indicate that when a product's form suggests a particular level of functional performance, consumers naturally incorporate that information into judgments of feature performance, even when presented with conflicting feature information from an objective source. The role of consumer attention in the process is also explored. The results suggest that product developers may be able to improve perceived performance by focusing design efforts and marketing communications on specific features that visually communicate functionality.

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)0.003
metaresearch head score (Gemma)0.033
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.033
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0010.001
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 head0.072
GPT teacher head0.306
Teacher spread0.235 · 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

Citations131
Published2011
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Product Innovation ManagementSame topicColor perception and designFrench-language works237,207