Consumer responses to strategic customer extensions
Bibliographic record
Abstract
Purpose This study aims to examine how brands attempt to extend their customer set not through the typical route of adding brands, but through the strategic extension or enlargement of their target customer set. Building on theories from both reference group perceptions and brand identification, this research explores the impact of strategic customer extensions on current target market consumers. Design/methodology/approach Two scenario-based experiments explore strategic customer extensions for a packaged goods brand and a well-known retail brand. The analysis involves both analysis of variance and SEM methods. Findings Current target market consumers’ evaluations of strategic customer extensions are informed by reference group perceptions relating to the proposed customer extension. When current target market consumers perceive strategic customer extensions as potentially attracting a dissociative reference group, consumers have weaker evaluations and brand identification measures and, subsequently, weaker future intentions towards the brand. Originality/value The brand identification literature is augmented by incorporating theories from the reference group literature to demonstrate how to reference group perceptions drive a current target market consumers’ evaluations of strategic customer extensions to affect the strength of the identification that current target market consumers have with a brand. Brand identification is also demonstrated as mediator customer evaluations and subsequent intentions towards the brand.
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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 | 0.002 | 0.008 |
| 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 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".