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Record W2036090765 · doi:10.2202/1546-5616.1065

Investigating the Relationship Between Advertising and Pricing in a Channel with Private Label Offering: A Theoretic Model

2008· article· en· W2036090765 on OpenAlexaff
Salma Karray, Guiomar Martín‐Herrán

Bibliographic record

VenueReview of Marketing Science · 2008
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicConsumer Market Behavior and Pricing
Canadian institutionsOntario Tech University
Fundersnot available
KeywordsPrivate labelAdvertisingCompetition (biology)National brandBusinessMarketingEconomics

Abstract

fetched live from OpenAlex

We study the relationship between pricing and advertising decisions in a distribution channel where national brands are competing with a private label. We solve a three-stage game-theoretic model where the national brands compete on advertising and prices, and the retailer is investing in umbrella advertising for the store and is selling a private label. The obtained equilibrium strategies highlight the importance of determining the complementary or competitive roles of advertising to better understand the relationship between advertising and prices, and to better adjust strategies to varying competition levels in the marketplace. In particular, we find that advertising that expands the national brands' sales gives pricing power to manufacturers. However, persuasive advertising can create different effects on prices depending on the strength of the advertising effect and on the price competition level between the national and the store brands. For highly competitive advertising effects, the retailer should charge lower prices for the private label when it carries highly advertised national brands, increase the national brand's price that is being advertised and decrease the price of the competing national brand. The retailer's advertising leads to higher prices for the national and private labels. We consider several extensions of the base model (retail competition, asymmetric manufacturers and dynamic effects of advertising) and show that our results still hold in such settings. Marketing implications and comparative statistics are also 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 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)0.009
metaresearch head score (Gemma)0.006
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 score0.034
Threshold uncertainty score0.766

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0090.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0010.001
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 head0.056
GPT teacher head0.277
Teacher spread0.221 · 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

Citations25
Published2008
Admission routes1
Has abstractyes

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