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Record W2152426234 · doi:10.1111/itor.12051

Pricing strategies with reference effects in competitive industries

2013· article· en· W2152426234 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueInternational Transactions in Operational Research · 2013
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicConsumer Market Behavior and Pricing
Canadian institutionsWestern University
Fundersnot available
KeywordsCompetitor analysisExternalityProfit (economics)MicroeconomicsEconomicsCompetition (biology)Industrial organizationReference priceBusiness

Abstract

fetched live from OpenAlex

Abstract This paper examines the effect of reference prices on companies operating within competitive industries. We confirm that even with competition, firms optimally price high in the short term to generate a high reference price and then decrease this price over time. Competitors' prices converge toward each other over time, emphasizing the short‐term nature of reference prices. We then show that pricing optimally to take advantage of reference prices generates a positive externality for other firms in an industry, such that competitors may generate higher profit. The longer the focus of a given firm, the more profit the firm generates, but less relative to its competitors. This arises because the externalities created through pricing high to increase reference prices outweigh the benefits of the higher reference prices themselves. If pricing managers are compensated relative to their competition, this suggests that short‐termism may be implicitly encouraged to the detriment of profit.

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.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.574
Threshold uncertainty score0.998

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 communication0.0010.002
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.070
GPT teacher head0.349
Teacher spread0.279 · 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