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Record W2063421176 · doi:10.1108/08876040310467907

How intangibility affects perceived risk: the moderating role of knowledge and involvement

2003· article· en· W2063421176 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 Services Marketing · 2003
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicConsumer Behavior in Brand Consumption and Identification
Canadian institutionsUniversité du Québec à MontréalConcordia UniversityRoyal Bank of Canada
Fundersnot available
KeywordsConstruct (python library)Risk perceptionDimension (graph theory)GeneralityVariance (accounting)MarketingStructural equation modelingBusinessPsychologyProduct (mathematics)Test (biology)Services marketingService (business)PerceptionAccounting

Abstract

fetched live from OpenAlex

The marketing literature suggests that product intangibility is positively associated with perceived risk and the intangibility construct encompasses three dimensions: physical intangibility, mental intangibility, and generality. The purpose of this research is to test which dimension of the intangibility construct is the most correlated with perceived risk. A survey was conducted and structural equation modeling analyses were used to test the proposed model. Results show that the mental dimension of intangibility accounts for more variance in the perceived risk construct than the other two dimensions, even when knowledge and involvement are included as moderators. Hence, the challenge for marketers might not be so much to reduce risk by physically tangibilizing goods and services, as has been advised for the past two decades, as rather to mentally tangibilize their offerings.

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)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.171
Threshold uncertainty score0.344

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
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 integrity0.0000.000
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 head0.013
GPT teacher head0.226
Teacher spread0.213 · 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