Understanding underdog brand positioning effects among emerging market consumers: a moderated mediation approach
Bibliographic record
Abstract
Purpose This study aims to explore the underdog brand biography dimensions that emerging-country consumers identify with (Study 1) and attempts to uncover the effects of these dimensions on brand affinity and purchase intention moderated by self-identity and brand trust (Study 2). Design/methodology/approach Study 1, using data from 359 young Indians, reveals three underlying dimensions integral to underdog brand biography in emerging markets. Study 2 uses an experimental setup with a single-factorial design among 332 young Mexican consumers to investigate the direct effects of three identified underdog brand biography dimensions on purchase intention, mediated by brand affinity and moderated by consumer self-identity and brand trust. Findings Study 1 reveals three dimensions underlying underdog brand biographies: unfavorable circumstances, striving in adversities and passion, and persistent will to succeed. Study 2 reveals that consumers with higher self-identity demonstrate greater purchase intentions for an underdog brand than a top dog one. Practical implications The results indicate that marketers can successfully use underdog narratives to influence consumer decision-making, thereby increasing brand affinity and purchase intention. Originality/value This study delineates the link between different dimensions of underdog brand biographies with brand affinity and purchase intention in emerging countries and builds on the understanding of the moderating role played by self-identity and brand trust.
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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 | 0.007 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.011 | 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".