They’re Just Not That into You: How to Leverage Existing Consumer–Brand Relationships Through Social Psychological Distance
Bibliographic record
Abstract
While prevailing marketing practice is to encourage ever-stronger relationships between consumers and brands, such relationships are rare, and many consumers are relationship-averse or content with the status quo. The authors examine how marketers can more effectively manage existing brand relationships by focusing on the psychological distance between consumers and brands in order to match close (distant) brands with concrete (abstract) language in marketing communications. Through such matching, marketers can create a beneficial mindset-congruency effect leading to more favorable evaluations and behavior, even for brands that are relatively distant to consumers. Study 1 demonstrates the basic mindset-congruency effect, and Study 2 shows that it is capable of affecting donation behaviors. Study 3 documents two brand-level factors (search vs. experience goods, brand stereotypes) that moderate this effect in managerially relevant ways. Study 4 shows that activation of the mindset-congruency effect influences consumers to spend more and that these behaviors are moderated by consumer category involvement. The authors conclude with marketing and theoretical implications.
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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 | 0.004 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.005 |
| Scholarly communication | 0.004 | 0.009 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 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".