Effects of Supplier Customer Orientation on Buyer Loyalty: A Contingent Process Model Based on Self-Determination Theory
Bibliographic record
Abstract
Prior supplier-buyer relationship research has identified supplier customer orientation as a driver of buyer loyalty. In this research, we address how and when this effect occurs. Based on self-determination theory, we identify three buyer psychological states—buyer autonomy, buyer competence, and buyer relatedness—that mediate the impact of supplier customer orientation on buyer loyalty. Drawing from prior supplier-buyer relationship scholarship, we identify three contingencies—buyer asset specificity, buyer environmental uncertainty, and buyer reciprocal interdependence—that, respectively, moderate the mediating effects of the three buyer psychological states. Results from a survey of 171 supplier-buyer matched dyads show that the three buyer psychological states are positive mediators of the impact of supplier customer orientation on buyer loyalty. Results also show that while the positive mediating effects of buyer autonomy and buyer competence are respectively strengthened by buyer asset specificity and buyer environmental uncertainty, the positive mediating effect of buyer relatedness is weakened by buyer reciprocal interdependence. Theoretical and practical implications are discussed.
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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 | 0.004 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.010 | 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".