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Record W2062665199 · doi:10.1509/jmr.10.0256

Wal-Mart's Impact on Supplier Profits

2011· article· en· W2062665199 on OpenAlexaff
Qingyi Huang, Vincent R. Nijs, Karsten T. Hansen, Eric T. Anderson

Bibliographic record

VenueJournal of Marketing Research · 2011
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicConsumer Market Behavior and Pricing
Canadian institutionsKellogg's (Canada)
Fundersnot available
KeywordsBusinessProfit (economics)Market powerIndustrial organizationVariety (cybernetics)Carry (investment)MarketingSupplier relationship managementCommerceEconomicsMicroeconomicsSupply chainSupply chain managementFinanceMonopoly

Abstract

fetched live from OpenAlex

Previous academic research on the expansion of dominant retailers such as Wal-Mart has examined implications for incumbent retailers, consumers, and the local community. Little is known, however, about Wal-Mart's influence on suppliers' performance. Manufacturers suggest that Wal-Mart uses its power to squeeze their profits. In this article, the authors study the validity of this claim. They investigate the underlying mechanisms that may cause changes in manufacturer profits following Wal-Mart market entry. The data contain information on supplier interactions with retail stores, including Wal-Mart, for a period of five years. They find that postentry supplier profits increased by 18% on average, whereas profits derived from incumbent retailers decreased only marginally. Their results show that wholesale prices are not the main driver of postentry supplier profit changes; market expansion is. They observe a significant increase in shipments to 50% of markets studied. Furthermore, their analyses demonstrate that supplier shipment and profit increases are highest for markets in which incumbents offer a wide variety of products and carry items that Wal-Mart does not sell.

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)0.023
metaresearch head score (Gemma)0.003
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.185
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0230.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.117
GPT teacher head0.359
Teacher spread0.242 · 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

Citations65
Published2011
Admission routes1
Has abstractyes

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