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Record W4205456360 · doi:10.1080/0267257x.2021.1966076

Is brand differentiation necessary for success? The role of purchase goal and confidence in the brand’s position

2022· article· en· W4205456360 on OpenAlexaff
Anne-Maree O’Rourke, François A. Carrillat, Paul Z. Wang

Bibliographic record

VenueJournal of Marketing Management · 2022
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicConsumer Behavior in Brand Consumption and Identification
Canadian institutionsHEC Montréal
Fundersnot available
KeywordsBusinessMarketingAdvertisingPosition (finance)Brand managementBrand equityBrand awarenessBrand extension

Abstract

fetched live from OpenAlex

There are few attempts at empirically validating the effectiveness of brand differentiation, leading to a long-lived debate regarding whether it is a necessary condition for brand success. Drawing from metacognition and decision process theory, the current research suggests that the relationship between perceived differentiation and purchase is stronger when there is a weaker match between the brand’s perceived position and consumers’ purchase goal (i.e. between what the brand stands for and what consumers are seeking). In addition to the condition of purchase goal, consumers’ confidence in their judgement of the brand’s position acts as an additional contingency factor in the relationship between differentiation and purchase. The hypotheses were supported by two studies across common consumer purchase goals: ‘value for money’ and ‘top of the range’ and two product categories, with different adult samples (n1 = 291 and n2 = 283 for the respective studies). Implications for brand communication strategy are discussed.

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 imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.022
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.020

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.022
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.002
Scholarly communication0.0020.002
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.000

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.

Opus teacher head0.013
GPT teacher head0.241
Teacher spread0.228 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations10
Published2022
Admission routes1
Has abstractyes

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