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Record W3088125567 · doi:10.1515/roms-2019-0075

Persuasive Advertising in a Vertically Differentiated Competitive Marketplace

2020· article· en· W3088125567 on OpenAlexaff
Yuanfang Lin, Chakravarthi Narasimhan

Bibliographic record

VenueReview of Marketing Science · 2020
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicConsumer Market Behavior and Pricing
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsAdvertisingQuality (philosophy)Product (mathematics)BusinessCompetition (biology)Affect (linguistics)MarketingPerceptionInformative advertisingWillingness to payReservationNative advertisingEconomicsMicroeconomicsOnline advertisingPsychologyComputer science

Abstract

fetched live from OpenAlex

Abstract Despite the widely acknowledged existence in practice, the theoretical literature on persuasive advertising is generally vague about exactly how such advertising could affect consumer preferences, except for the general assumption that persuasive advertising affects consumer willingness to pay or simply “shifts demand.” This paper proposes a theoretical framework for characterizing different ways that persuasive advertising may affect consumer utility in a vertically differentiated marketplace. Firstly, persuasive advertising could simply raise consumers’ reservation price for the product category. Secondly, persuasive advertising could enhance consumers’ perception about the product quality offered by the advertising firm. Thirdly, persuasive advertising could increase consumers’ willingness to pay for quality increment. Preliminary evidences from lab studies are presented to support the existences of the proposed effects. Using a game-theoretic approach, we study two firms’ decision in the adoption of persuasive advertising of a particular effect and the associated price competition. Findings from the theoretical model analyses indicate that factors influencing a firm’s decision in persuasive advertising include consumer heterogeneity, degree of product differentiation, the effectiveness and the cost of such advertising. In a vertically differentiated competitive marketplace, persuasive adverting is a more desirable strategic tool for firms of higher-quality products to further establish a competitive advantage.

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)0.005
metaresearch head score (Gemma)0.009
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.299
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.017
GPT teacher head0.258
Teacher spread0.240 · 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.

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

Citations4
Published2020
Admission routes1
Has abstractyes

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