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Record W4319788609 · doi:10.1111/1475-679x.12472

Assessing the Social Impact of Corporations: Evidence from Management Control Interventions in the Supply Chain to Increase Worker Wages

2023· article· en· W4319788609 on OpenAlexaff
Gregory Distelhorst, Jee‐Eun Shin

Bibliographic record

VenueJournal of Accounting Research · 2023
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicGlobal trade, sustainability, and social impact
Canadian institutionsBaycrest HospitalUniversity of Toronto
Fundersnot available
KeywordsOvertimeMultinational corporationWageLabour economicsBusinessSupply chainControl (management)Psychological interventionHourly wageEconomicsFactory (object-oriented programming)MarketingFinance

Abstract

fetched live from OpenAlex

ABSTRACT This study examines an initiative by a large multinational garment retailer (H&M Group) to increase wages at its supplier factories by intervening in their wage‐related management practices. Difference‐in‐differences estimates based on eight years of data from over 1,800 factories show that the interventions were associated with an average real wage increase of approximately 5% by the third year of implementation. Our estimates suggest that the intervention‐associated wage increase was many times greater than if the retailer's cost for the program was instead paid directly to affected workers. We find that the wage effects were driven by factories with relatively poorer supplier ratings and do not find significantly different wage effects depending on the presence of trade unions. We also examine several nonwage outcomes such as factory orders, supplier price competitiveness, overtime pay, and total employment to probe the mechanisms underlying the wage increases. These findings offer new evidence on corporate social impact in global supply chains.

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)0.017
metaresearch head score (Gemma)0.005
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.051
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0170.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
Science and technology studies0.0010.000
Scholarly communication0.0020.002
Open science0.0010.000
Research integrity0.0000.001
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 head0.150
GPT teacher head0.468
Teacher spread0.318 · 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

Citations12
Published2023
Admission routes1
Has abstractyes

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