The Power of Customer Relationship Management: A New Marketing Trend for Hospitality in Globalization Context (Case study of Hanoi Old Quarter)
Bibliographic record
Abstract
Customer Relationship Management is known as an effective method which helps administrations solve many problems customers may have. Customer Relationship Management is a global way for businesses to set up, maintain, and extend their customer network. Nowadays, every business which wants to survive and develop needs to improve its customer relationship management department. Researchers have shown that in every decision-making process the most important factors concerning customers are the following: price, promotions, processing speed and response time, and these are among the key factors which are going to be covered in this article. In the hospitality sector, especially for hotel business in the old city center of Hanoi, 90% of visitors are foreigners and mainly through online (OTA) sources. About the booking process for foreign visitors when traveling to Hanoi was presented in the study of Dr. Nguyen Van Ha “The power of online marketing for hospitality in Vietnam in globalization context” showed that before booking a room, they were able to find out the hotel by reading reviews of customers who had experienced the hotel through the channels such as tripadvisor, booking.com .... The Old Quarter hotel is primarily concerned with customer reviews, customer service aimed at keeping customers happy and satisfy about the hotel. And these good reviews are the most effective way to help hotels boost sales, boost hotel branding, and promote the image of the hotel. This research has a scope of surveys which were done in Hanoi, Vietnam. Nevertheless, it serves as the grounds for all travel agencies and hotels doing business in Hanoi to re-examine their online marketing activities and consider the findings of this paper as reference for further research.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.003 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".