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Record W2913733706 · doi:10.2501/jar-2019-001

Dynamic Asymmetric Effects of Cross-Media Exposures over the Purchase Cycle

2019· article· en· W2913733706 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 Advertising Research · 2019
Typearticle
Languageen
FieldDecision Sciences
TopicInnovation Diffusion and Forecasting
Canadian institutionsMcGill University
Fundersnot available
KeywordsAdvertisingVariation (astronomy)BusinessTelevision advertisingConsumer demandEconomicsMarketingMicroeconomics

Abstract

fetched live from OpenAlex

<h3>ABSTRACT</h3> Cross-media advertising campaigns can grant marketers decisive advantages given the potential for synergy. Little is known, however, about the dynamics of cross-media effects due to the evolution of household demand over the purchase cycle as well as the potential for asymmetry in such effects due to sequential exposure. More remains to be learned about such effects in the emerging Chinese market, which may exhibit regional variation. The authors studied the dynamic effects of cross-media advertising on television and online over the household purchase cycle, examining single-source data on household-level cross-media exposures and purchases for a brand of a consumer packaged goods (CPG) in China. They found evidence for dynamic synergistic effects, which exhibited asymmetry in the direction of television advertising. They also found evidence for regional variation in cross-media response.

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)0.015
metaresearch head score (Gemma)0.034
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.665
Threshold uncertainty score0.974

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0150.034
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.004
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.073
GPT teacher head0.455
Teacher spread0.382 · 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