The interaction of social CRM between CRM performance and marketing performance in hotels
Bibliographic record
Abstract
In recent times, there has been a significant decline in hotel occupancy rates, and this is primarily due to marketing performance. Hoteliers and the decision-makers are thus seeking new strategies to increase occupancy rates by enhancing marketing performance. The present work examined the relationship between customer relationship management performance and marketing performance by considering the moderating role of social customer relationship management on this relationship. In this work, both the “Resource-Based View Theory” and “Social Exchange Theory” were employed. Data from hotel managers in Jordan were collected, with 139 responses being collected and analyzed altogether. “Smart Partial Least Squares” were used for the analysis process, which showed that customer relationship management performance positively impacted marketing performance, and that Social customer relationship management also had a positive effect on marketing performance. Moreover, the relationship between customer relationship management performance and marketing performance is enhanced through social customer relationship management. These findings can be used by hoteliers to develop effective marketing strategies using new technology and communication tools.
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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 | 0.002 | 0.007 |
| 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 | 0.003 | 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".