The Relative Effects of Relationship Quality and Exchange Satisfaction on Customer Loyalty
Bibliographic record
Abstract
This paper addresses two key questions on how supplier firms can better manage industrial buyers to create higher loyalty. The first involves whether to focus on relationship quality or exchange satisfaction. This dual route model towards enhancing loyalty in essence is concerned with comparing the relative strengths of the effect from relationship quality to loyalty and from exchange satisfaction to loyalty. The second point of interest pertains to whether the effects from relationship quality and exchange satisfaction to loyalty are moderated by environmental conditions such as switching barriers and viable alternatives. Using data on business customers' ratings of a major information technology provider, we find that the effect of exchange satisfaction on loyalty is significantly greater than the effect of relationship quality on loyalty. We also find that the impact of exchange satisfaction on loyalty is less sensitive and more stable across different levels of switching barriers and viable alternatives. Conversely, the effect of relationship quality on loyalty is more pronounced to such moderating variables in that the effect of relationship quality on loyalty was greater when switching barriers were low and many viable alternatives existed. Implications for marketing theory and practice 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 | 0.021 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.011 | 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".