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Record W2166443045 · doi:10.1016/j.jom.2006.05.008

Sources and consequences of bargaining power in supply chains

2006· article· en· W2166443045 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.

Bibliographic record

VenueJournal of Operations Management · 2006
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicQuality and Supply Management
Canadian institutionsTellabs (Canada)
Fundersnot available
KeywordsBargaining powerInterdependenceSupply chainIndustrial organizationBusinessPower (physics)Control (management)Task (project management)Resource dependence theoryResource (disambiguation)MicroeconomicsSupply chain managementAction (physics)EconomicsOperations managementMarketingManagementComputer scienceSociology

Abstract

fetched live from OpenAlex

Abstract Research suggests that collaborative supply chain management (SCM) helps chain members create “a rising tide that lifts all boats.” Yet resource dependence theory suggests that when tides rise, some boats are lifted more than others; members who furnish important resources or resources where control is concentrated have bargaining power. Drawing on Thompson [Thompson, J.D., 1967. Organizations in Action. McGraw‐Hill, New York], we argue that strong firms’ bargaining power use is tempered by the type of coordination different types of task interdependencies demand. We also investigate how both strong and weak members benefit from SCM. Whereas strong members reap most of the direct benefits, weak members can often gain by building switching costs with strong members, leveraging SCM outside the focal chain, and increasing survival chances.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.859
Threshold uncertainty score0.410

Codex and Gemma teacher scores by category

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

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 head0.015
GPT teacher head0.236
Teacher spread0.222 · 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