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Competition Between Local and Electronic Markets: How the Benefit of Buying Online Depends on Where You Live

2008· article· en· 559 citations· W3124922652 on OpenAlex· 10.1287/mnsc.1080.0932

Why is this work in the frame?

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

Canadian affiliationAn author listed a Canadian institution. This is the only route the usual frame has.
Canadian funderA Canadian agency funded it. The work may carry no Canadian affiliation at all.

Full frame distilled prediction

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.

Candidate categories
none
Consensus categories
none
Domain
Candidate signal: noneConsensus signal: none
Study design
Candidate signal: ObservationalConsensus signal: Observational
Genre
Candidate signal: EmpiricalConsensus signal: Empirical
Teacher disagreement score
0.431
Threshold uncertainty score
0.470
Validation status
machine_predicted_unvalidated · codex-gemma-dda1882f352a

Codex and Gemma teacher scores by category

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

Machine scores (provisional)

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

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.

Opus teacher head0.020
GPT teacher head0.226
Teacher spread
0.206 · how far apart the two teachers sit on this one work
Validation status
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Abstract

Our paper shows that the parameters in existing theoretical models of channel substitution such as offline transportation cost, online disutility cost, and the prices of online and offline retailers interact to determine consumer choice of channels. In this way, our results provide empirical support for many such models. In particular, we empirically examine the trade-off between the benefits of buying online and the benefits of buying in a local retail store. How does a consumer's physical location shape the relative benefits of buying from the online world? We explore this problem using data from Amazon.com on the top-selling books for 1,497 unique locations in the United States for 10 months ending in January 2006. We show that when a store opens locally, people substitute away from online purchasing, even controlling for product-specific preferences by location. These estimates are economically large, suggesting that the disutility costs of purchasing online are substantial and that offline transportation costs matter. We also show that offline entry decreases consumers' sensitivity to online price discounts. However, we find no consistent evidence that the breadth of the product line at a local retail store affects purchases.

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.

The record

Venue
Management Science
Topic
Consumer Market Behavior and Pricing
Field
Business, Management and Accounting
Canadian institutions
University of Toronto
Funders
Social Sciences and Humanities Research Council of CanadaNational Science Foundation
Keywords
PurchasingCompetition (biology)BusinessProduct (mathematics)Search costOnline and offlineAdvertisingMarketingMicroeconomicsOnline searchEconomicsComputer science
Has abstract in OpenAlex
yes