Revising the Effects of Online Advertising Attributes on Consumer Processing and Response
Bibliographic record
Abstract
With advances in technology, the internet has allowed advertisers to design advertisements with unique features that can help capture consumers’ visual attention and enhance their psychological states such as attitudes and emotions. Yet, web advertising features and attributes can significantly contribute to online consumer behaviors. This paper strives to provide guidelines for researchers and advertisers as to what outlines the effects of online advertising design on consumers’ processing and multiple outcomes. The findings indicated that exposure to a well-designed online advertisement can influence several cognitive and emotional responses, such as attention to the ad, motivations to process the ad, depth of processing, pleasure, arousal, and online purchase intention. According to the present review, consumer involvement is regarded as an important moderator in the relationships between web advertising content as well as design and several responses, including consumers’ intention to search and process information. The article concludes by identifying several areas of opportunities for advancing our understanding of web advertising effects. Marketers and advertisers will find the current work useful, as it can be used to maximize the effectiveness of web 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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
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 teacher head, 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".