Transactions vs. Relationships: What Should the Company Emphasize?
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
The relevance of transactional and relational marketing variables in relational exchanges is now well established in the marketing literature. However, the knowledge about their relative effectiveness and their optimal mix over time remains very sparse. An analytical model is proposed to help determine optimal decision rules for transactional and relational marketing efforts. Some of the main results are as follows: (a) If the seller benefits from the interaction between the transactional marketing effort and buyer’s commitment, then the seller’s optimal decision rules change over time and depend on the level of the partners’commitment. (b) Otherwise, the seller’s optimal decision rules for the two types of marketing are constant over time. (c) The seller should allocate more resources to relational marketing at the beginning of a relational exchange and, later on, should allocate more resources to transactional marketing.
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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 | 0.007 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.005 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it