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Record W1553495193 · doi:10.1108/17506121211216905

Brand network maps

2012· article· en· W1553495193 on OpenAlexaff
Sarena Saunders, Michel Rod

Bibliographic record

VenueInternational Journal of Pharmaceutical and Healthcare Marketing · 2012
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicConsumer Behavior in Brand Consumption and Identification
Canadian institutionsCarleton University
Fundersnot available
KeywordsBrand managementBrand equityGuildMarketingOriginalityStakeholderConsistency (knowledge bases)Brand relationshipBusinessComputer sciencePsychologyPublic relationsCreativitySocial psychology

Abstract

fetched live from OpenAlex

Purpose This paper aims to augment traditional investigations of consumer‐brand relationships and suggest alternative ways to consider these interactions. Specifically, the paper employs consumer associative networks for the purpose of uncovering how various stakeholders perceive the Pharmacy Guild of New Zealand brand subsequent to the implementation of a programme designed to enhance consistency of its brand. Design/methodology/approach The paper utilises semi‐structured interviews in a focus group setting to solicit attitudes, opinions and general feedback regarding a new service concept called the Supporting Independent Living (SIL) Program, recently developed by the Pharmacy Guild of New Zealand (PGNZ). Results are interpreted utilising community branding and network approaches, such as associative network theory. Findings The importance of utilising an associative network approach in investigating brand‐customer relationships is supported. This helps to identify the relationships between firms and their brands and the impact that this has on the brand development of existing, or newly‐created services. Originality/value The managerial implications include the suggestion of using a stakeholder approach once the SIL concept is fully operational; particularly focusing on how the brand association information is flowing back to the PGNZ parent brand and how various stakeholders (based on their salience) perceive their relationship with the brand.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.519
Threshold uncertainty score0.449

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.059
GPT teacher head0.352
Teacher spread0.293 · 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 teacher head, 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

Citations12
Published2012
Admission routes1
Has abstractyes

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Same venueInternational Journal of Pharmaceutical and Healthcare MarketingSame topicConsumer Behavior in Brand Consumption and IdentificationFrench-language works237,207