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Record W3033194040 · doi:10.1111/itor.12835

Multichannel retailing and price competition

2020· article· en· W3033194040 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueInternational Transactions in Operational Research · 2020
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicConsumer Market Behavior and Pricing
Canadian institutionsAthabasca UniversityOntario Tech University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsBusinessProfitability indexProfit (economics)DilemmaCompetition (biology)Online and offlineIndustrial organizationPosition (finance)Context (archaeology)MicroeconomicsProduct (mathematics)First-mover advantageMarketingCommerceEconomicsComputer scienceFinance

Abstract

fetched live from OpenAlex

Abstract We investigate the profitability of multichannel retailing for competing offline retailers. Each firm can sell a product both offline and online in a position of a first mover or follower in the online market. We find that, depending on the online market size and price competition levels across channels and retailers, the adoption of multichannel retailing may or may not enhance an offline retailer's profits in the first‐mover position. If one retailer profitably expands online, the second can also improve its profit by introducing another online channel to the detriment of the pioneer. However, when offline retailers are given the possibility of selecting an equilibrium channel mix, multichannel retailing could be adopted strategically by the two retailers to maintain their market shares, resulting in a prisoner's dilemma situation. In such a context, it drives down retail prices, increases sales, and reduces the profits of the two competing retailers.

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.723
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.118
GPT teacher head0.359
Teacher spread0.241 · 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