The impact of negotiators’ motivation on the use of decision support tools in preparation for negotiations
Why this work is in the frame
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Bibliographic record
Abstract
Abstract Thorough preparation for a negotiation is considered critical for the achievement of successful relational and substantive results. Careful specification of preferences and determining the negotiation offer scoring systems is one of the most important preparation activities. To facilitate this process, preference elicitation aids have been designed and implemented in decision and negotiation support systems (NSSs). This paper shows that negotiators’ motivation affects the use of simple elicitation aid and elicited preferences. We identify three types of motivations: epistemic, social, identity, and assign the factors that describe them. Then, using the dataset from electronic negotiation experiments, we apply logistic regression to identify those motivations that allow distinguishing negotiators who make errors in the determination of the scoring systems from those who do not make them. The key result allows us to identify relational‐ and learning‐oriented goals of the identity motivation as having a significant and direct impact on the negotiators’ classification. Accommodating and competing approaches of social motivation impact agents' accuracy with the differences observed for gender. Surprisingly, epistemic motivation represented by rationality and experientiality factors does not affect users’ accuracy in the prenegotiation phase. The results obtained can be used to design decision support tools adjusted to the motivational profiles of the NSS users.
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it