Reexamining and extending the dual mediation hypothesis in an on‐line advertising context
Bibliographic record
Abstract
Abstract The relationship between attitude toward the advertisement (Aad) and intentions to buy (Ib) is a controversial one. The present research examines the potential for a direct relationship between Aad and Ib within an on‐line advertising context, substituting Asite (attitude toward the Web site) for Aad. The article replicates previous findings with respect to the four competing Aad models they tested. The article then predicts and finds a significant Asite → Ib path based on an opportunity and motivation perspective. In terms of opportunity, Web sites contain nonproduct information that is independent of traditional measures of brand attitude (Ab), such as security, ease of use, transactional capabilities, which are likely to affect Ib. Further, on‐line consumers are motivated to process this information when they visit a Web site because they cannot directly examine the products they are considering. Evidence for the opportunity and motivation perspective is provided by the decomposition of Asite into its claim and non‐claim components and assessment of the Asite → Ib path across levels of motivation to process. Implications for on‐line advertisers are discussed. © 2005 Wiley Periodicals, Inc.
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.007 | 0.033 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.003 | 0.005 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.018 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".