Influences of Product Involvement and Symbolic Consumption Cues in Advertisements on Consumer Attitudes
Bibliographic record
Abstract
Symbolic consumption has become pervasive in daily life; advertisements focusing on brand awareness and celebrity endorsements involve strong product symbols and serve as a persuasive advertising tool. This study employed a 2 × 2 between-subject experimental design to investigate the influence of two independent variables, namely the level of consumer product involvement (high and low levels of involvement) and types of symbolic cues (brand and celebrity symbols), on consumer attitudes toward advertisements (Aad) and brands (Ab). Four notable findings were revealed: (1) the level of participant product involvement affected their fondness for Aad and Ab; (2) symbolic cues affected participant Aad and Ab; (3) participants with a high level of product involvement exhibited more positive Aad; and (4) participants with low product involvement demonstrated more positive Ab. In the contemporary advertising market, how enterprises can enable a product to convey a certain symbolic meaning has become particularly critical, and enterprises should not ignore the influences that symbolic consumption may have on consumers. These study results serve as a reference for enterprises and advising agents for devising future product advertising strategies.
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 | 0.002 | 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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".