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Record W1483196185 · doi:10.1300/j046v19n03_03

The Online Shopping Profile in the Cross-National Context

2007· article· en· W1483196185 on OpenAlexaboutno aff
Brian F. Blake, Colin M. Valdiserri, Kimberly A. Neuendorf, Jillian N. Valdiserri

Bibliographic record

VenueJournal of International Consumer Marketing · 2007
Typearticle
Languageen
FieldDecision Sciences
TopicTechnology Adoption and User Behaviour
Canadian institutionsnot available
Fundersnot available
KeywordsNoveltyFacet (psychology)Context (archaeology)Domain (mathematical analysis)Sample (material)MarketingPsychologyDomain specificityBusinessAdvertisingSocial psychologyGeographyMathematicsCognition

Abstract

fetched live from OpenAlex

Abstract A study of online shopping in five nations (Austria, Canada, Iran, Taiwan, and the USA) demonstrates the utility of the 7-facet “online shopping profile” (OSP), beyond the unidimensional indices widely employed in investigations of the adoption/use of online shopping. Further, the roles of domain-specific innovativeness and of two dimensions of perceived newness of the innovation (novelty and recency of introduction) are examined. Findings indicate that domain-specific innovativeness is a highly effective predictor of many facets of OSP in each nation's sample, but call into question whether domain-specific innovativeness represents innovativeness as traditionally defined. Implications for behavioral/marketing scientists and for practitioners are discussed.

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)0.034
metaresearch head score (Gemma)0.023
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesMetaresearch
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.087
Threshold uncertainty score0.994

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0340.023
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0020.000
Research integrity0.0000.001
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 head0.111
GPT teacher head0.445
Teacher spread0.334 · 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; both teacher heads agree on what is shown here.

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

Citations16
Published2007
Admission routes1
Has abstractyes

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