The Influence of Psychological Distance and Personal Relationship of Channel Members on Conflict, Satisfaction and Performance
Bibliographic record
Abstract
This study aims to find out the influence of psychological distance and personal relationship of channel members on conflict, satisfaction and performance. And we also study the connection between psychological distance and personal relationship and the influence of personal relationship on organizational trust. Besides, we discuss the substitution effect of personal relationship to organizational relationship, in the specific business environment of China, especially in the cooperation between small distributors and large suppliers. The trust on the salesmen of suppliers from the dealers may have more influence on their decision and behaviors than the trust on the supply organization. So the influence of organizational trust may not be very significant in our study. Our data are from 200 gas stations of Sinopec. And we design panel data regressions of several dimensions for every research variable, to study it objectively and comprehensively. Based on the results of regressions, this study try to explain the effect of psychological distance and personal relationship on the factors of channel, and put forward some advice to company operation. The conclusion of our study may be different from many traditional theories, because we find that the organizational trust doesn’t affect conflict, satisfaction and performance significantly.
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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 | 0.001 | 0.009 |
| 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 | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".