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Record W2082431823 · doi:10.1108/09555340710830118

Placing Wroe Alderson's contributions to buyer behavior in historical perspective

2007· article· en· W2082431823 on OpenAlexaff
Robert D. Tamilia

Bibliographic record

VenueEuropean Business Review · 2007
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicConsumer Behavior in Brand Consumption and Identification
Canadian institutionsUniversité du Québec à Montréal
Fundersnot available
KeywordsConceptualizationPerspective (graphical)OriginalityPurchasingContext (archaeology)Consumer behaviourValue (mathematics)Consumer researchInterpretation (philosophy)MarketingEpistemologySociologyPsychologySocial scienceBusinessComputer scienceQualitative researchHistoryPhilosophy

Abstract

fetched live from OpenAlex

Purpose The purpose of this paper is to present the contributions of Wroe Alderson to the buyer behavior literature from an historical perspective. His views of the consumer in the 1950s revolutionized the way we now teach and do research in this domain of marketing. Design/methodology/approach This research relied heavily on Alderson's own published work and the work of others familiar with his work. The historical research tradition of document interpretation was employed and personal interviews were conducted. Findings The findings revealed that Alderson contributed much to buyer behavior thought than is generally believed. This eminent theorist – practitioner was ahead of his time in his conceptualization of the consumer/household purchasing agent as an information processor and a problem solver in the behavioral process of buying and consuming. Originality/value A detailed account of Alderson's contributions to the then emerging science of consumer behavior is unique especially in the context of thought contributions originating from other sciences.

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)0.007
metaresearch head score (Gemma)0.010
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.007
Threshold uncertainty score0.036

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.010
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.002
Science and technology studies0.0020.011
Scholarly communication0.0060.007
Open science0.0010.002
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0040.001

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.

Opus teacher head0.041
GPT teacher head0.306
Teacher spread0.265 · 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 designNot applicable
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
Published2007
Admission routes1
Has abstractyes

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