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Record W2049221718 · doi:10.1108/sbm-08-2011-0069

Mind, body, or spirit? An exploration of customer motivations to purchase university licensed merchandise

2014· article· en· W2049221718 on OpenAlexaboutno aff
Joan M. Phillips, Robert I. Roundtree, Kim Dae-Hyun

Bibliographic record

VenueSport Business and Management An International Journal · 2014
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicCustomer Service Quality and Loyalty
Canadian institutionsnot available
Fundersnot available
KeywordsReputationMarketingOriginalityBusinessQuality (philosophy)Value (mathematics)AdvertisingQualitative researchSociologyComputer science

Abstract

fetched live from OpenAlex

Purpose – The purpose of this paper is to explore the relationship between consumers’ purchase motivations to show support for university programs and the influence of merchandise quality cues on their purchase decision, and examine how one's affiliation with a university (official or non-official) moderates this relationship. Design/methodology/approach – This research utilized a mail survey of university bookstore customers from the USA and Canada. The university, located in the USA, has an international reputation for its academic programs, its athletic teams, and its religious affiliation. Findings – Our findings demonstrate the significance of athletic programs over academic programs and religious values in motivating purchases of licensed university merchandise. Research limitations/implications – These findings have significant implications for several stakeholders in the business of retailing licensed merchandise. In particular, university licensors and their bookstore retailers may consider managing their inventory of licensed products to reflect the greater relative importance athletic teams have in the purchase decision process. Originality/value – This paper adds to our understanding of customer motivations to purchase university licensed merchandise, and the conditions when merchandise quality is a key decision driver.

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)0.001
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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.645
Threshold uncertainty score0.623

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.005
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 head0.045
GPT teacher head0.282
Teacher spread0.238 · 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 designTheoretical or conceptual
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

Citations7
Published2014
Admission routes1
Has abstractyes

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