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Record W2266333131

Different Levels of Trust in Global Business Negotiation

2015· article· en· W2266333131 on OpenAlexaboutno aff
Mie-Jung Kim, Liyuan Wang, Moon-Suh Park

Bibliographic record

Venue통상정보연구 · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicConflict Management and Negotiation
Canadian institutionsnot available
Fundersnot available
KeywordsNegotiationIdentification (biology)Process (computing)Public relationsBusinessKnowledge managementPolitical scienceComputer scienceLaw
DOInot available

Abstract

fetched live from OpenAlex

This study examines the close relationship between trust and global business negotiations. Kristen Blankley(2010) pointed out three level of trust impacting each negotiation stage: calculus-, knowledge-, identification-based trust. In this regard, the present study examines the relationship between each level of trust and the process of business negotiations by focusing on Canadians and Koreans who had business negotiation experience with Chinese counterparts. For Canadian respondents, calculus-based trust and identification-based trust didnt have significant effects on the negotiation atmosphere, whereas they did for Korean respondents. For Canadian respondents, knowledge-based trust had the greatest effect on each step of the business negotiation process.

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)0.000
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.260
Threshold uncertainty score0.356

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.078
GPT teacher head0.333
Teacher spread0.255 · 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.

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

Citations1
Published2015
Admission routes1
Has abstractyes

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