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Record W2562595859 · doi:10.1002/cjas.1426

Respect in Buyer/Seller Relationships

2016· article· en· W2562595859 on OpenAlexaffvenue
Maureen Bourassa, Peggy Cunningham, Laurence Ashworth, Jay M. Handelman

Bibliographic record

VenueCanadian Journal of Administrative Sciences / Revue Canadienne des Sciences de l Administration · 2016
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicJob Satisfaction and Organizational Behavior
Canadian institutionsQueen's UniversityDalhousie UniversityUniversity of Saskatchewan
Fundersnot available
KeywordsMeaning (existential)Thematic analysisWork (physics)MarketingCitizenshipPoint (geometry)Word of mouthPsychologyBusinessSocial psychologySociologyPublic relationsQualitative researchPolitical scienceSocial scienceEngineering

Abstract

fetched live from OpenAlex

Abstract We explore respect's meaning and impact as experienced by individuals in buyer/seller business‐to‐business relationships. Though respect has known drivers and important consequences, it is poorly defined and understood, especially in business literature. We reviewed literature from various fields, including education, aging, and social work, and conducted in‐depth interviews with 24 North American professionals. Through thematic analysis of transcripts, we found respect is about valuing relationship partners. It results not only in commitment and positive word‐of‐mouth (as expected), but also positive emotions and citizenship behaviours. We develop a synthesized and expanded model of the determinants and outcomes of respect and point to future research. Our findings suggest managers should consider how to build respect in buyer/seller relationships to improve long‐term outcomes. Copyright © 2016 ASAC. Published by John Wiley & Sons, Ltd.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.014
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.023

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.014
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0040.004
Scholarly communication0.0050.003
Open science0.0000.005
Research integrity0.0010.002
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 head0.125
GPT teacher head0.308
Teacher spread0.183 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations13
Published2016
Admission routes2
Has abstractyes

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Same venueCanadian Journal of Administrative Sciences / Revue Canadienne des Sciences de l AdministrationSame topicJob Satisfaction and Organizational BehaviorFrench-language works237,207