Understanding trust development in negotiations: An interdependent approach
Bibliographic record
Abstract
Summary What affects the way that trust develops in negotiations? In two studies, we used an actor–partner interdependence model to investigate how both negotiators' trust propensity prior to the negotiation and two types of behavior during the negotiation affect negotiators' trust development. Study 1 demonstrated that both focal negotiators' (actors') and their counterparts' (partners') trust propensity were positively associated with negotiators' trust development. Study 2 showed that actors' and partners' trust propensity had an indirect effect on trust development via both actors' and partners' negotiation behaviors. Negotiators' trust propensity positively affected their use of Q&A (questions and answers about interests) and negatively affected their use of S&O (substantiation about positions and single‐issue offers). Actors and partners' negotiation behaviors in turn affected their own and their partners' trust development. Our studies propose and test a model to understand how negotiators' trust propensity and negotiation behaviors affect the development of trust in negotiation. Copyright © 2016 John Wiley & Sons, Ltd.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.010 | 0.038 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.007 |
| Scholarly communication | 0.007 | 0.013 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".