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Record W1528374983 · doi:10.1002/mar.20720

Bundle Building in the Arts: An Experimental Investigation

2014· article· en· W1528374983 on OpenAlexaff
Jessica Darveau, Alain d’Astous

Bibliographic record

VenuePsychology and Marketing · 2014
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicConsumer Behavior in Brand Consumption and Identification
Canadian institutionsHEC Montréal
Fundersnot available
KeywordsBundleComplementarity (molecular biology)Subtractive colorPerceptionThe artsPsychologyMarketingSelection (genetic algorithm)BusinessComputer scienceArtificial intelligenceArtVisual arts

Abstract

fetched live from OpenAlex

ABSTRACT Within the arts and culture sector, bundling is a commonly used strategy that consists in marketing a combination of products in a single package. Drawing from current examples in the arts and culture industry, the study presented in this article examines how different bundling strategies affect consumer decisions and perceptions. An experiment was conducted among a sample of 200 adult consumers where the complementarity of bundle items (complementary vs. noncomplementary) and mode of selection of bundle items (additive vs. subtractive) were jointly manipulated by means of a self‐administered questionnaire. Consistent with previous research, the results showed that consumers who construct an arts and culture bundle in a subtractive fashion end up with a greater number of items and a more expensive bundle. However, the impact of mode of selection on the bundle's perceived value was shown to depend on the complementarity of the items. These findings suggest that the recommendation of avoiding bundling noncomplementary products usually put forward in the bundling literature must be evaluated through a consideration of the type of strategy that is used to build the bundle.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.465
Threshold uncertainty score0.242

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 communication0.0000.000
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 head0.043
GPT teacher head0.318
Teacher spread0.275 · 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

Citations7
Published2014
Admission routes1
Has abstractyes

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