Examining the Effects of Cause-Proximity and Gender on Consumers’ Response to Cause-Related Marketing: Evidence from Malaysia
Bibliographic record
Abstract
Over the last decade, cause-related marketing (CRM) has become a popular marketing strategy for companies. Academic research suggests outcomes of CRM campaigns are generally positive for companies as well as for causes. For companies, CRM has been noted to increase sales and enhance companies’ image. As for causes, they received greater funding and publicity. Cause-proximity which is one of the important elements of CRM’s structure has been suggested to significantly influence consumers’ response towards CRM. However, the impacts of cause-proximity on consumers’ response are inconsistent. In this light, this paper investigates (1) the effect of cause-proximity on consumers’ response to CRM (2) the moderating role of gender on the relationship between cause-proximity and consumers’ response to CRM. The results indicate that the effect of cause-proximity is insignificant while gender does influence consumers’ response to CRM. Based on these results, implications for CRM campaign managers and research limitations are highlighted.
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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 | 0.005 | 0.015 |
| 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".