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Record W2012451956 · doi:10.1016/j.jom.2010.07.001

The boundary spanning capabilities of purchasing agents in buyer–supplier trust development

2010· article· en· W2012451956 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 · 2010
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicCustomer Service Quality and Loyalty
Canadian institutionsTellabs (Canada)
Fundersnot available
KeywordsPurchasingBusinessBoundary spanningAutomotive industryMarketingSupplier relationship managementIndustrial organizationBoundary (topology)Affect (linguistics)Supply chainPurchasing processFunction (biology)Supply chain managementKnowledge managementComputer science

Abstract

fetched live from OpenAlex

Abstract This study examines how individual purchasing agents function as boundary spanners with suppliers to influence trust development in themselves and the buying firms that employ them. Building upon boundary theory and supply chain cooperation research, we identify three boundary spanning capabilities of purchasing agents and empirically test how these capabilities shape buyer–supplier trust development. Using two samples of data collected from suppliers in the automotive industry and food industry, we found that a purchasing agent's effectiveness in strategic communication with suppliers affects a supplier's trust in the buying firm, while an agent's professional knowledge and ability to reach compromises with suppliers affect a supplier's trust in the purchasing agent representing the firm. Trust in the purchasing agent in turn affects trust in the buying firm. Theoretical and managerial implications are discussed.

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)0.002
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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.753
Threshold uncertainty score0.433

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.026
GPT teacher head0.273
Teacher spread0.247 · 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