Buyers’ Perspective of Buyer-Supplier Relationship Development: Interaction of Key Variables
Bibliographic record
Abstract
In this paper, we propose and test a three-stage model. A relationship begins at the Pre-Deal Stage (t-1), where, Buyer and Supplier Power are likely to impact Input Commitment. The relationship moves on to the Deal Enactment Stage (t), where the Input Commitment is likely to foster Low Relational Embeddedness. This, in turn, develops Contractual Trust that leads to a business deal and Attitudinal Commitment. Depending on requirements and mutual satisfaction, the relationship may then move to the Continuation Stage (t+1), where the developed Attitudinal Commitment enhances High Relational Embeddedness. From this comes Competence-based Trust and Temporal Commitment. Temporal Commitment and High Relational Embeddedness is likely to further produce Goodwill Trust and improved Overall Performance. This research study extends existing literature by empirically testing a cohesive model, which explains the different, multidimensional roles relational constructs can play in a relationship, and how these relationships evolve over time.
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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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.018 | 0.001 |
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".