Reducing uncertainty in supplier selection decisions: Antecedents and outcomes of procedural rationality
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.
Bibliographic record
Abstract
Abstract Supplier selection decisions are characterized by a high degree of uncertainty. We draw upon the behavioral operations management and decision‐making literatures to examine factors that lead to the adoption of procedural rationality as a decision strategy. In addition, we emphasize the effect of procedural rationality on decision‐makers’ perceived uncertainty and subsequent supplier decision performance. Our structural equation model with cross‐country survey data from 461 respondents in the United States and China reveals that (i) organizational, situational, and personal antecedents significantly influence the use of procedural rationality, (ii) procedural rationality is effective in reducing uncertainty in supplier selection decisions, and (iii) the reduction in decision uncertainty improves supplier decision performance. We also emphasize contextual idiosyncrasies between China and the United States.
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 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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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