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Record W2063265149 · doi:10.1002/dir.20040

Predicting intentions to return to the Web site: Extending the dual mediation hypothesis

2005· article· en· W2063265149 on OpenAlexaff
Eric J. Karson, Robert J. Fisher

Bibliographic record

VenueJournal of Interactive Marketing · 2005
Typearticle
Languageen
FieldSocial Sciences
TopicDigital Marketing and Social Media
Canadian institutionsWestern University
Fundersnot available
KeywordsWeb siteMediationContext (archaeology)Perspective (graphical)World Wide WebDual (grammatical number)Transactional leadershipPath analysis (statistics)Computer scienceAdvertisingPath (computing)Test (biology)The InternetPsychologyBusinessSocial psychologySociologyGeographyArtificial intelligenceArt

Abstract

fetched live from OpenAlex

MacKenzie, Lutz, and Belch (1986) test four advertising attitude models and find that the Dual Mediation Hypothesis is the best. This research proposes an extended model within an online context, using intentions to return (I r ) to a Web site versus purchase intentions, with a direct path between attitudes toward the Web site (A site ) and I r . This path is hypothesized as Web sites contain informative or entertaining content that attracts subsequent visits, and I r depends on other non-brand-related factors such as security, ease of use, transactional capabilities, etc. Data from visitors to three actual Web sites––digital cameras, watches, and a charity––demonstrate significant relationships between A site and I r . In support of this perspective, when A site was decomposed into its claim and non-claim components, the non-claim component had a significant effect on I r for all three sites. Implications for online researchers and advertisers 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 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)0.009
metaresearch head score (Gemma)0.039
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 score0.009
Threshold uncertainty score0.048

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0090.039
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0030.001
Science and technology studies0.0010.002
Scholarly communication0.0030.004
Open science0.0020.004
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0090.001

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 head0.020
GPT teacher head0.305
Teacher spread0.285 · 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

Citations70
Published2005
Admission routes1
Has abstractyes

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