Getting to Know You: Trust Formation in New Interfirm Relationships and the Consequences for Investments in Management Control and the Collaboration
Bibliographic record
Abstract
Abstract Trust is often posited to substitute for management control in interfirm transactions. However, this raises questions of how trust arises in new relationships, and whether trust that is not based on prior experience transacting together is sufficient to persuade managers to forgo investments in management controls. We use an experiment to test whether two features of the early stage of an interfirm relationship influence a buyer's initial trust in a supplier and have consequences for subsequent investments in management controls and in the collaboration. These two features are the autonomy of the buyer's manager to choose a supplier (i.e., delegation of decision‐making authority) and the supplier's willingness to share information with the buyer. We find that the buyer manager's initial trust in the supplier is associated positively with both the autonomy to choose the supplier and the supplier's willingness to share information. Information content and supplier characteristics are held constant, so these results are novel and distinct from prior studies of the antecedents of trust. We find that higher initial trust is associated with reduced expenditures for management controls and increased investments in the collaboration. Thus, we conclude that delegation of decision‐making authority and supplier information‐sharing behavior in the early stages of a relationship influence the formation of initial trust, which has real consequences for investments in management control and in the collaboration.
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How this classification was reachedexpand
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 | 0.012 | 0.002 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".