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Record W2592927888 · doi:10.1002/mar.21000

Online Display Advertising: The Influence of Web Site Type on Advertising Effectiveness

2017· article· en· W2592927888 on OpenAlexaff
Sumitra Auschaitrakul, Ashesh Mukherjee

Bibliographic record

VenuePsychology and Marketing · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicDigital Marketing and Social Media
Canadian institutionsMcGill University
Fundersnot available
KeywordsOnline advertisingAdvertisingDisplay advertisingContextual advertisingWeb siteSearch advertisingPsychologyThe InternetAdvertising researchFeelingWorld Wide WebFluencyAntecedent (behavioral psychology)Computer scienceSocial psychologyBusiness

Abstract

fetched live from OpenAlex

ABSTRACT This research shows that online display advertising is more effective in terms of attitudes toward the ad and brand when it appears on commercial Web sites such as Walmart or Amazon, compared to social Web sites such as LinkedIn or Facebook. Consistent with a fit‐fluency mechanism, this effect of Web site type on advertising effectiveness was found to be driven by higher feelings of processing fluency on commercial compared to social Web sites. Further consistent with a fit‐fluency framework, online display advertising was found to be more effective on brand compared to personal pages of social Web sites. These results contribute to the literature on Internet advertising by identifying Web site type as a new antecedent and fit‐fluency as a new mechanism underlying the effectiveness of online display advertising.

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)0.004
metaresearch head score (Gemma)0.010
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.335
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.010
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
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 head0.017
GPT teacher head0.359
Teacher spread0.342 · 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 teacher head, not a consensus.

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

Citations29
Published2017
Admission routes1
Has abstractyes

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