Marketing Ethics and Relationship Marketing - An Empirical Study that Measure the Effect of Ethics Practices Application on Maintaining Relationships with Customers
Bibliographic record
Abstract
<p>The purpose of this study is to measure the effect of ethics embedded practices on maintaining long-term relationships with customers. Based on an extensive literature review, four elements of marketing ethics, namely, honesty, autonomy, privacy and transparency were identified and examined by utilizing a sample of 360 participants. Adopting a quantitative approach, the study conducted on telecommunication sector subscribers revealed that the elements of marketing ethics affected an organization’s ability of maintaining long-term relationships with customers and had a strong influence on feedback, transparency and privacy. The results also showed the crucial role of generating feedback from customers for creating and maintaining long-term relationships. The results will enable marketers to not only analyze the importance of adopting ethical practices in their strategies but also the relative relevance of these practices as perceived by customers.</p>
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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 | 0.215 | 0.477 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.003 |
| 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; both teacher heads agree on what is shown here.
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".