Customer relationship management and brand image: Empirical evidence from marine export company in Indonesia
Bibliographic record
Abstract
This research aimed to analyze the direct and indirect influence of customer relationship management and brand image on customer loyalty in the marine export department of DSV Transport Indonesia through customer satisfaction. Customer Relationship Management in goods delivery was one of the essential variables to improve company service to satisfy its customers and impact their loyalty. Research with a quantitative approach uses the Path Analysis statistical tool. This research used quantitative methods with a sample of 199 companies. The key findings of this research stated that customer relationship management has a negative and insignificant effect on the satisfaction and loyalty of marine export customers of DSV Transport Indonesia. Thus, the changes occurring in the application of Customer Relationship Management in marine exports would not affect the satisfaction and loyalty of marine export customers of DSV Transport Indonesia. Based on the results of this research, it was stated that customer satisfaction was indirectly able to function as a mediator or mediate the indirect influence of Customer Relationship Management and brand image on the customer loyalty to marine exports of DSV Transport Indonesia.
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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 | 0.003 |
| 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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".