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Record W1583025658

Clicks vs. Bricks: Toward a Model of Internet-Induced Channel Competition

2000· article· en· W1583025658 on OpenAlexaff
Paul Chwelos, Michael Brydon

Bibliographic record

VenueJournal of the Association for Information Systems · 2000
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicConsumer Market Behavior and Pricing
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsCompetition (biology)Competitor analysisIndustrial organizationChannel (broadcasting)BundleThe InternetBusinessQuality (philosophy)Product (mathematics)Production (economics)Space (punctuation)Service (business)Focus (optics)MicroeconomicsDatabase transactionMarketingComputer scienceEconomicsTelecommunicationsMathematicsDatabase
DOInot available

Abstract

fetched live from OpenAlex

The overall objective of this program of research is to develop a model of Internet-induced channel competition. In this paper, we focus on the ways in which retail channel technology—specifically, the online vs. bricks and mortar stores—affects the feasible trade-offs that firms can make between price and desirable attributes of their product/service bundles. This paper treats products as a bundle of the physical good and the fulfillment or transaction technology, and proposes a model of competition in the price-attribute space to illustrate the tradeoffs for consumers and producers. This model is grounded in demand, production, and hedonic theory, and relates the attributes (or “quality”) of products to their observed prices. Our objectives in future research are to refine the analytical model and to find evidence that (1) the functional forms assumed in the model are consistent with the price/attribute trade-offs observed in practice and (2) the observed competitive responses of firms dominated by online competitors are consistent with those prescribed by our model.

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)0.001
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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.483
Threshold uncertainty score0.262

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 communication0.0000.002
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 head0.028
GPT teacher head0.233
Teacher spread0.205 · 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 designSimulation or modeling
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

Citations2
Published2000
Admission routes1
Has abstractyes

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