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Article

The Quality of Hilton Hotel Services in the V4 Countries: The Impact of the Platform on Ratings and Customer Satisfaction

by
Stela Kolesárová
,
Anna Šenková
,
Erika Kormaníková
* and
Kristína Šambronská
Department of Tourism and Hotel Management, Faculty of Management and Business, University of Prešov, Konštantínova 16, 080 01 Prešov, Slovakia
*
Author to whom correspondence should be addressed.
Tour. Hosp. 2025, 6(4), 169; https://doi.org/10.3390/tourhosp6040169
Submission received: 27 June 2025 / Revised: 22 August 2025 / Accepted: 2 September 2025 / Published: 5 September 2025
(This article belongs to the Special Issue Customer Behavior in Tourism and Hospitality)
Versions Notes

Abstract

(1) This study aims to quantify differences between platforms and countries by comparing Hilton’s ratings on Booking.com and Google.com in the V4 countries. (2) Data were collected directly from Booking.com and Google.com for selected Hilton hotels. Descriptive statistics were used to process and analyze the data, and a paired Student’s T-test was used to compare standard deviations between platforms. (3) The analysis showed that these differences can be applied not only to subjective preferences but also to sociotechnical devices, including cultural platforms and their associated norms and user expectations. Additionally, factors such as price, food quality, and atmosphere were shown to influence overall guest satisfaction, with ratings approximately indicating satisfaction or dissatisfaction. (4) From a practical perspective, these insights can help hotel managers optimize their online communication strategy, tailor content to different platforms, and manage their reputation more effectively. Overall, the findings highlight that effectively managing online reviews is key to establishing trust, increasing satisfaction, and ensuring the long-term success of the Hilton brand in diverse sociocultural contexts. Future research should focus on sociotechnical aspects and the impact of seasonal or marketing campaigns on reviews to gain a more comprehensive understanding of the dynamics of online reviews in the hospitality industry.

1. Introduction

Online reviews have become a key element in the hospitality industry, and their importance is constantly increasing alongside the growing digitalization and availability of information technologies. Online customer reviews are considered an important source of information to help customers make the right choice (Litvin et al., 2008; Ye et al., 2011).
Online reviews are playing an increasingly important role in the hospitality industry. As opinions and recommendations are shared by customers on social media, blogs, or booking and rating portals, they represent a valuable source of information not only for tourists in their decision-making process but also for businesses, which can better understand their customers and improve the services they provide (Ahani et al., 2019; Berezina et al., 2016; Oliveira et al., 2020). These reviews have a major impact on the choice of accommodation, as they provide customers with a wealth of information and facilitate a quicker assessment of offers, thus reducing the uncertainty associated with the purchase of products and services (Serra Cantallops & Salvi, 2014). At the same time, they give hoteliers the opportunity to gain more detailed insights into guests’ preferences and thus improve the quality of hotel services (Berezina et al., 2016). As customer knowledge is crucial in hotel management, and the sector is characterized by a diverse mix of guests with different expectations, needs, and perceptions of services, it is essential to segment the market and differentiate between groups of clients (Ahani et al., 2019; Francesco & Roberta, 2019; Talón-Ballestero et al., 2018).
The helpfulness of an online review refers to the perceived value of the information it contains (M. Li et al., 2013). M. Li et al. (2013) also measured review diagnostic—that is, the extent to which a review helps a reader to make an informed purchasing decision (Mudambi & Schuff, 2010).

2. Literature Review

We live in a digital era where information circulates between consumers and businesses at an unprecedented speed. Modern consumers are increasingly conscious of their environment, available choices, and rights, and they base their purchasing decisions on this awareness. Considering the significance of the service industry, and the hotel sector in particular, online visibility emerges as a critical factor for success. Younger generations are driving global change, and internet technologies have become essential tools for achieving marketing effectiveness (Pontes & Ramos, 2023).
To successfully attract potential visitors to a tourist destination, it is crucial to implement smart tourism systems that create added value for experiences and services (Chuang, 2023). Patafta and Milohnić (2022) emphasize the importance of hotel management communicating online and monitoring reviews of the hotel. Danish et al. (2019) found that the realism, volume, and positivity of reviews are key factors influencing consumers’ decisions to book a hotel, with trust serving as a mediator between these factors. Negative reviews, however, do not have any significant direct or indirect impact on booking decisions.
Several factors can influence customer experience and its evaluation, including the characteristics of the platform on which the reviews are published, as well as the demographic and psychographic characteristics of the users (Wang et al., 2020; Xiang & Gretzel, 2010).
The first pillar is the concept of ‘platform difference’, which suggests that different online platforms may create different environments for evaluating services, affecting the manner and content of customer feedback. For instance, accommodation-specialized platforms such as Booking.com may encourage more detailed, technical reviews, whereas general search engines and review platforms such as Google.com may reflect more overall impressions and subjective feelings (Park & Nicolau, 2015; Lu et al., 2018).
Another important factor is the ‘demographic and psychographic differentiation’ of users of these platforms, which can affect how they are rated. For instance, younger, tech-savvy, or travel-oriented customers may favor certain platforms and methods of expressing satisfaction or dissatisfaction (Chivu et al., 2018; Kalashnikova et al., 2023).
Another important factor is the subjectivity of customer reviews, which are considered a fundamental characteristic of reviews in the hospitality industry. These reviews are often influenced by personal expectations, emotional responses, and individual experiences, leading to variability in reviews and their interpretation (Arif & Waleed, 2022).
However, given that the technical quality of services such as Wi-Fi is often objectively measurable, its evaluation is expected to be less dependent on platform differences and subjective factors. Conversely, subjective aspects such as cleanliness, location, and staff can be influenced by the cultural, linguistic, and personal differences of users, which is consistent with the concept of ‘cultural perceptions of service quality’ (Durna et al., 2015; Ding et al., 2022). Based on these theoretical assumptions, platform differences are expected to have a significant impact on hotel ratings, particularly in areas of higher subjectivity, such as cleanliness, location, and staff. The results of empirical research can confirm or refute these assumptions, thereby contributing to a deeper understanding of customer rating dynamics in the digital hospitality environment (Gellerstedt & Arvemo, 2019).
In recent years, the number of studies focusing on online reviews shared through booking and opinion platforms has increased, reflecting a growing scholarly interest in this field. Research has demonstrated that guests tend to report higher satisfaction levels when staying in four- and five-star hotels (Ahn et al., 2017; H. Li et al., 2020; M. Li et al., 2013; Pacheco, 2016). As customer knowledge is recognized as a fundamental aspect of hotel management (Talón-Ballestero et al., 2018) and considering that the systematic use of online review analysis remains relatively underdeveloped within the hospitality sector, this study highlights the relevance of such insights. Table 1 presents an overview of selected research addressing online hotel reviews.

3. Materials and Methods

Online reviews and ratings are a key source of information in the hospitality industry. This study aims to quantify differences between platforms and countries by comparing Hilton’s ratings on Booking.com and Google.com in the V4 countries1. The intention is to gain knowledge that can contribute to improving services and enabling more informed strategic decision-making.
Booking.com is an online platform specializing in accommodation and travel services. It allows users to search for, compare, and book hotels, apartments, and other types of accommodations around the world. The site offers detailed information about facilities and guest reviews, as well as an easy booking process.
Google.com is a global search engine that provides a wide range of internet-based information. As well as searching for web pages and images, you can search for local businesses, including hotels, and view maps, reviews, and links to booking platforms. Although Google is not designed for direct bookings, it is useful for quickly finding information and navigating to available accommodations.
The main differences between Booking.com and Google.com lie in their functions and purposes. Booking.com is a specialized platform for booking hotels and travel services. It allows users to search for and compare accommodations and to book them directly on the site. It provides detailed hotel information, reviews, and direct booking options. Google.com, on the other hand, is a general search engine that provides a wide range of information from the internet, including hotel and accommodation searches. Google displays relevant results, maps, reviews, and links to various booking platforms, but does not offer direct booking. Google is more of a tool for quickly finding information and navigating to available accommodations through various sources (Booking.com; Google.com).
The reason for selecting variables to analyze Booking.com and Google.com reviews of selected hotels is based on the importance of these four aspects, which are key to overall guest satisfaction and significantly impact their decision-making process. Cleanliness is critical because a lack of cleanliness can significantly affect guest trust and comfort, as reflected in reviews. Location is another key factor because a convenient location increases a hotel’s attractiveness and affects guest satisfaction. Staff play a significant role in providing services and creating a positive experience, which is directly reflected in reviews. Wi-Fi is now considered a standard service, and its quality can significantly impact guests’ ability to work and their satisfaction during their stay. While other aspects such as the price–quality ratio, room comfort, and food quality are important, their selection is not as critical as the four aspects and often depends on individual guest preferences or the style of the hotel. Therefore, focusing on these four fundamental factors ensures a more comprehensive and relevant analysis that better reflects the basic requirements and expectations of guests. This is key for decision-making and service improvement.
Based on this, the following research question is addressed: RQ: Are there statistically significant differences in the average ratings of individuals (e.g., cleanliness, location, staff, Wi-Fi) of the Hilton between Booking.com and Google.com platforms?
The following research hypotheses were formulated for this research question:
  • H0: We hypothesize that there is no statistically significant difference in the average ratings of the Hilton hotel chain’s individual aspects (cleanliness, location, staff, and Wi-Fi) on the Booking.com and Google.com platforms.
  • H1: We hypothesize that there is a statistically significant difference in the average ratings of the Hilton hotel chain’s individual aspects (cleanliness, location, staff, and Wi-Fi) between the Booking.com and Google.com platforms.
To determine the relationship between the selected indicators, we analyzed publicly available customer reviews of the Hilton hotel chain in the V4 countries in 2024. The research sample consisted of reviews of selected Hilton hotels in each V4 country.
For the Slovak Republic, the sample included reviews for the following hotels: DoubleTree by Hilton Košice and DoubleTree by Hilton Bratislava; for the Czech Republic: Hilton Prague and Hilton Prague Old Town; Hungary: Hilton Budapest and Hilton Garden Inn Budapest City Centre; and Poland: Hilton Warsaw City Hotel and Hilton Gdańsk.
Data were collected directly from Booking.com and Google.com for each of these eight hotels. Descriptive statistics were used to process and analyze the data, and a paired Student’s T-test was used to compare standard deviations between platforms. Research hypotheses were verified at the significance level α = 0.05. Statistical analyses were performed using the JASP software program (version 0.95.1).

4. Results

To verify statistical significance, we used the t-test for dependent samples, which is suitable for comparing two related samples. In this case, we compared the same hotels on two different platforms. We also performed the Wilcoxon test for dependent samples to verify the results, as this is a non-parametric alternative to the Student’s t-test. Prior to applying these tests, we verified the normality of the differences between the paired ratings using the Shapiro–Wilk test.

4.1. Hilton Hotels in the Slovak Republic

There are two Hilton hotels in Slovakia: The DoubleTree by Hilton Košice and the DoubleTree by Hilton Bratislava. This study will analyze customer reviews and ratings for each hotel separately, comparing perceptions on the Booking.com and Google.com platforms.
The DoubleTree by Hilton Košice is a modern hotel located in the center of Košice. It is known for its location, which provides easy access to historical monuments and shopping centers. The hotel focuses on providing comfortable accommodations and quality services for tourists and business travelers.
The average ratings for the DoubleTree by Hilton Košice suggest high overall guest satisfaction on both platforms (Table 2).
Interestingly, Google.com users show a slightly higher tendency to give favorable ratings than Booking.com users. This suggests potential differences in expectations or evaluation methods between users of these two platforms. Although the average ratings at Booking.com are slightly lower, they still indicate a high level of satisfaction among customers who booked the hotel through this platform. A comparison of the ratings and feedback on the two platforms reveals that the average percentage ratings, when converted to a common scale, indicate slightly higher satisfaction on Google.com than on Booking.com. Positive feedback is consistent on both platforms, indicating clear strengths of the hotel. The differences are reflected in negative comments, where Google.com users are more likely to criticize the price of parking and the price–quality ratio, whereas Booking.com users criticize the price of breakfast.
The DoubleTree by Hilton Bratislava is a modern hotel located in the heart of the city. It is renowned for providing comfortable accommodations and quality services for tourists and business travelers alike. The DoubleTree by Hilton Bratislava has high average ratings on both platforms, with slightly higher satisfaction levels recorded on Google.com (Table 2). Google.com ratings are 0.1 points lower than those for the DoubleTree by Hilton Košice, and Booking.com ratings are 0.2 points lower.
A comparison of the ratings and feedback across the two platforms shows that when converted to a common scale, the average percentage ratings are high, with slightly higher satisfaction recorded on Google.com than on Booking.com. Positive reviews on both platforms praise the hotel for its staff, location, and cleanliness. Negative reviews on Google.com tend to focus on the state of the rooms and bathrooms, whereas on Booking.com, criticism centers on the price.

4.2. Hilton Hotels in the Czech Republic

There are two hotels in the country that are part of the renowned Hilton chain. Specifically, these are the Hilton Prague and the Hilton Prague Old Town. Strategically located in Prague, the capital of the Czech Republic, these two facilities are important providers of high-class accommodations and strengthen the presence of the Hilton brand in the Czech tourism market. In the following subsections, we will analyze customer reviews and ratings for each hotel separately to compare customer perceptions on the Booking.com and Google.com platforms.
The Hilton Prague is a luxury hotel located in the heart of Prague. It is particularly popular with discerning customers looking for accommodations in the heart of the Czech Republic, in a city with a rich history and many famous monuments.
While the average ratings for the Hilton Prague still indicate a high level of guest satisfaction on both key online platforms, they show a slightly lower rating compared to reviews for hotels in Košice and Bratislava (Table 3; Table 2). This difference suggests that certain factors may influence the overall perception of the Prague hotel’s services and accommodations. Google.com consistently shows a slightly higher average level of satisfaction among reviewers. Despite this slight difference, the Hilton Prague Hotel’s good reputation and ability to meet the needs and expectations of its guests is still evident in the overall ratings on both platforms.
When converted to a common scale, the average percentage ratings are positive, with a slightly higher value on Google.com than on Booking.com. The Hilton Prague received mostly positive reviews on both platforms, with guests praising its strategic location and amenities. Negative reviews on Google.com varied in their subjective experiences of the quality of accommodations, service, food, and perceived value, while complaints about staff, cleanliness, linen changes, and hotel amenities appeared on Booking.com.
The Hilton Prague Old Town is a luxury hotel located in the historic center of Prague. It caters for guests looking for accommodations near historical monuments who appreciate the elegant Art Deco style. The Hilton Prague Old Town achieved high satisfaction levels on both platforms, with an average rating that was slightly higher on Google.com. Compared to Hilton Prague, it received a slightly better rating on both platforms (Table 3).
A comparison of the ratings and feedback across the two platforms shows that when converted to a common scale, the average percentage ratings are high, with slightly higher satisfaction on Google.com than on Booking.com. As with the Hilton Prague, guests particularly appreciate the excellent location. Negative reviews on Google focus on service and the size of the rooms and amenities, while on Booking.com, guests have reservations about room amenities, temperature, vegetarian meals, and the wellness center.

4.3. Hilton Hotels in Hungary

There are four Hilton hotels in Hungary. For the purposes of this thesis, however, we will focus on two of these hotels: the Hilton Budapest and the Hilton Garden Inn Budapest City Centre. Selecting these two hotels allows us to compare customer reviews of different types of hotels in the Hungarian capital, Budapest. In the following subsections, we will analyze customer reviews and ratings for each hotel separately to identify differences in customer perception on Booking.com and Google.com.
Located in Budapest, the Hilton Budapest Hotel stands out from standard city hotels thanks to its connection to cultural heritage and aesthetic experience. Located in Buda, the historic part of the city, it offers guests breathtaking views of the Danube and its architectural landmarks. The hotel provides guests with an authentic experience of the city’s culture and history while meeting the requirements of premium-category accommodations.
The Hilton Budapest has received high average ratings on both platforms, with slightly higher satisfaction recorded on Google.com (Table 4).
A comparison of the ratings and feedback across the two platforms shows that when converted to a common scale, the average percentage ratings are high, with slightly higher satisfaction on Google.com than on Booking.com. Positive feedback primarily focuses on the hotel’s unbeatable location and breathtaking views. Negative reviews on Google.com were mostly about staff and noise, whereas complaints about rooms, amenities, and prices were mostly found on Booking.com.
The Hilton Garden Inn Budapest City Centre is a modern, mid-range city hotel. Focusing on providing comfort at a reasonable price, it is a practical choice, especially for business travelers. It is located near restaurants and shops, and the interior is modern, simple and functional. The average ratings for the Hilton Garden Inn Budapest City Centre are high and very similar on both platforms, although the average rating is slightly higher on Booking.com (Table 4).
A comparison of the ratings and feedback on the two platforms shows that the average percentage ratings are high and very similar on both platforms. Positive reviews tend to mention the location and management of the hotel. Interestingly, the rating is slightly higher at Booking.com. Negative reviews on Google were related to billing and parking, while complaints on Booking.com were about cleanliness, the shower, room temperature, and noise.

4.4. Hilton Hotels in Poland

For the purposes of this thesis, we will focus on a more detailed analysis of two hotels: the Hilton Warsaw City Hotel and the Hilton Gdansk. Selecting these two hotels, which are in two major Polish cities that differ in character (Warsaw and Gdansk), will enable us to gain a broader view of how customers perceive Hilton services in different contexts within the Polish market. In the following subsections, we will analyze customer reviews and ratings for each hotel separately to identify possible differences in perception on the Booking.com and Google.com platforms.
The Hilton Warsaw City Hotel is a modern, luxurious hotel located in the vibrant financial district of Warsaw. Its strategic location and comprehensive facilities make it an ideal choice for business and leisure travelers alike. The hotel boasts excellent transport links and proximity to major tourist attractions.
Hilton Warsaw City’s average ratings are high on both platforms, with slightly higher satisfaction reported on Google.com (Table 5).
A comparison of the ratings and feedback across the two platforms shows that when converted to a common scale, the average percentage ratings are high, with slightly higher satisfaction reported on Google.com than on Booking.com. Positive feedback focuses on the professional staff and good location. Negative reviews on Google.com were related to the state of the rooms and the staff, whereas complaints about room amenities and restrictions on families with children were found on Booking.com.
The Hilton Gdansk Hotel is in the historic heart of the Old Town and overlooks the Motława River. As well as offering luxurious accommodations, the hotel provides guests with an extensive spa center with panoramic views, restaurants serving local and international cuisine, a terrace bar, and an indoor pool. The hotel caters for families with children, offering special programs and amenities.
The average percentage rating of Hilton Gdansk Hotel is high, with slightly higher satisfaction with Google.com than with Booking.com. Positive feedback consistently praises the location and staff. The Hilton Gdansk is also praised for its eco-certification, the Mercato restaurant, the food, the room amenities, and the rooftop bar. Negative reviews on Google.com were mostly about drink prices and the language skills of the staff, while complaints on Booking.com were mostly about parking prices, breakfast, and the gym facilities.

4.5. Descriptive Statistics for Selected Indicators of Customer Ratings and Verification of Research Question

The second step of our analysis is descriptive statistics for selected indicators of customer ratings. We focus on these indicators: cleanliness, location, personnel, and Wi-Fi assessment (Table 6).
Table 6 shows the standard deviation for cleanliness, location, personnel, and Wi-Fi assessment ratings on Booking.com and Google.com. On average, the cleanliness rating, location rating, and personnel rating are higher on Google.com than on Booking.com. For the Wi-Fi assessment, the standard deviation is higher on Booking.com, which indicates greater consistency in the ratings.
After verifying the normality of the selected indicators of customer ratings, we conclude that all selected variables (cleanliness, location, personnel, and Wi-Fi assessment) have a normal distribution. We can use the Student’s t-test to verify the research question.
As can be seen from the results of the Student’s t-test shown in Table 7, there are statistically significant differences in the cleanliness, location, and personnel ratings on Google.com and Booking.com. However, statistically significant differences were not confirmed for the Wi-Fi assessment rating. Therefore, there is a rationale for researching and comparing the customer service ratings of Hilton hotels.

5. Discussion

Our study revealed significant differences in Hilton hotel reviews on Booking.com and Google.com across the V4 countries. We found statistically significant differences in the rating of cleanliness, location, and staff. These results suggest that customer review are influenced not only by subjective preferences but also by the design and characteristics of the platforms themselves, as well as by sociotechnical factors that shape how users express their experiences. From a sociotechnical perspective, it is interesting that platforms can encourage different review behaviors depending on their design, cultural norms, and user expectations.
For instance, Booking.com tends to emphasize more detailed reviews of services and amenities, which can result in higher ratings in these areas. In contrast, Google.com may encourage faster, more general reviews that reflect subjective impressions rather that detailed analyses. This difference may affect not only the way users’ rate but also their motivation and review behavior (Patafta & Milohnić, 2022; Lu et al., 2018).
Interestingly, in the case of Wi-Fi, there was no significant difference between the platforms, suggesting that the technical quality of Wi-Fi is perceived as objective and less susceptible to subjective evaluation culture. This may be because technical aspects are measurable and verifiable, whereas service evaluations such as cleanliness or staff depend on individual expectations.
Extending our analysis to include other evaluation criteria reveals that factors such as price, food quality, hotel atmosphere, and the availability of additional services can also significantly impact overall guest satisfaction. For instance, high food quality ratings can have a significant influence on hotel ratings, depending on the type of hotel and its target guest group. Similarly, the atmosphere and design of the hotel, including its aesthetics and level of comfort, are important factors that influence ratings and perceptions of quality.
From a social context perspective, cultural and linguistic differences between the individual V4 countries must also be considered, as these can influence how guests express satisfaction or dissatisfaction. Cultural norms regarding respect, openness, or criticality, for example, can influence how guests formulate their reviews, increasing the complexity of data interpretation.
Methodologically, the use of robust statistical tests such as Shapiro–Wilk to verify normality and the Student’s t-test to compare means increases the credibility and reliability of conclusions. However, limitations must also be considered, such as differences in the number of reviews, time periods for data collection, and the possible influence of seasonality or specific events that could distort the results.
From a practical point of view, higher ratings of a location or staff on one platform can influence a hotel’s marketing strategies and its market perception. This information can help hotel managers to understand which aspects of their service are most valued and where improvements are needed to increase overall satisfaction and the hotel’s reputation.
Finally, it is important to emphasize that reviews are subjective, and their perception is influenced not only by the factual characteristics of services but also by cultural, linguistic, and social norms, which differ between countries. Future research should examine these sociotechnical aspects, as well as the impact of seasonality, specific events, and marketing campaigns on reviews. This could provide a more comprehensive understanding of the dynamics of online reviews in the hospitality industry.

6. Conclusions

Customer reviews play a key role in a guest’s decision to book a stay. Guests often share their experiences in the form of review, whether they are completely satisfied or not. Therefore, accommodation providers should not ignore these ratings. Overall reviews are often based on partial ratings of factors such as price, cleanliness, location, and service. The number of reviews also affects how credible and appealing the property seems to future guests.
A property’s reputation is very important, and reviews play a key role in creating it. Ideally, someone should respond to reviews as soon as possible, and it is advisable to respond to both positive and negative reviews. If the property does not have someone assigned to manage reviews, then it is recommended that automatic response software is used. When writing a response, it is important to remain emotionally stable and consistent in tone, to use polite and professional language, to thank the reviews for their feedback, and to express gratitude for positive reviews. In the case of negative reviews, it is appropriate to offer a solution, remedy the situation, and ensure that the customer feels welcome on their next visit, for example by offering a discount or additional services.
The best way to avoid negative reviews is to prevent them from happening in the first place. During the stay, employees should assess guest satisfaction to avoid dissatisfaction after departure, when it is no longer possible to influence their rating.
Reviews can also represent a competitive advantage. Positive reviews can be used on the website or shared via links to rating portals, thereby increasing the establishment’s credibility and attractiveness.
From a management perspective, reviews are a valuable source of information that can be used to identify service weaknesses and guest preferences and to improve offerings. Responding to reviews helps the establishment to build trust and credibility with potential customers. Actively monitoring and managing reviews is essential for improving service quality and guest satisfaction and for maintaining competitiveness. Based on the feedback received, innovations can be introduced, staff training can be improved, and processes can be optimized, thereby increasing customer loyalty and business growth.
However, we consider the research to be limited in that it focuses only on Hilton hotels in the V4 countries. A broader international perspective, for example within the EU, could yield interesting results. At the same time, the classification of the selected Hilton hotels means that the ratings may be misleading or incomparable, which is another limitation of the research. For future research on customer reviews, we recommend expanding the research area and sample size to produce more consistent and relevant results.
In terms of improving ratings, Hilton could adapt its communication style for each individual platform. On Booking.com, for example, where reviews emphasize specific aspects such as service quality, cleanliness, and staff, the company should emphasize these factors. On Google.com, which has a wider reach and addresses a more diverse audience, Hilton could emphasize value, innovation, and positive experiences associated with the hotel. For example, this could be based on the food offered or visual campaigns. When creating content, hotels should take advantage of each platform’s specific features and tailor their message to appeal to their target audience. At the same time, it is crucial to maintain consistent branding, values, and communication style to strengthen customer trust. Responding quickly and appropriately to reviews and feedback improves reputation and builds loyalty. Regularly monitoring performance and feedback enables hotels to adjust their strategies in real time and gain a better understanding of how their brand is perceived. A coherent communication strategy across platforms forms the basis of effective reputation management, thereby increasing customer satisfaction and strengthening the Hilton brand’s position in the market.

Author Contributions

Conceptualization, S.K. and K.Š.; methodology, E.K.; software, S.K.; validation, A.Š., K.Š., and S.K.; formal analysis, E.K.; investigation, A.Š.; resources, K.Š.; data curation, E.K.; writing—original draft preparation, S.K.; writing—review and editing, K.Š.; visualization, A.Š.; supervision, A.Š.; project administration, E.K.; funding acquisition, S.K. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by EU NextGenerationEU through the Recovery and Resilience Plan for Slovakia under the project No. 09I03-03-V05-00006. The APC was funded by Prešovská university v Prešove.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

The original contributions presented in this study are included in the article. Further inquiries can be directed to the corresponding author.

Conflicts of Interest

The authors declare no conflicts of interest.

Note

1
The Visegrad Group (V4) is an informal grouping of four central European countries: the Slovak Republic, the Czech Republic, Hungary, and Poland. This vibrant regional structure comprises four EU and NATO member states that share the same values, history, culture, and geographical location. The V4 creates space for strengthening coordination and consultation mechanisms, with the aim of finding common positions and opinions on current foreign and European policy issues, regional development and economic and cultural cooperation.

References

  1. Ahani, A., Nilashi, M., Yadegaridehkordi, E., Sanzogni, L., Tarik, A. R., Knox, K., Samad, S., & Ibrahim, O. (2019). Revealing customer’s satisfaction and preferences through online review analysis: The case of Canary Islands hotels. Journal of Retailing and Consumer Services, 51, 331–343. [Google Scholar] [CrossRef]
  2. Ahn, D., park, H., & Yoo, B. (2017). Which group do you want to travel with? A study rating differences among groups in online travel reviews. Electronic Commerce Research and Applications, 25, 105–114. [Google Scholar] [CrossRef]
  3. Antonio, N., Almeida, A., Nunes, L., Batista, F., & Ribeiro, R. (2018). Hotel online reviews: Different languages, different opinions. Information Technology & Tourism, 18, 157–185. [Google Scholar] [CrossRef]
  4. Arif, A., & Waleed, A. (2022). The impact of online reviews on consumer restaurant and hotel selection decisions in Türkiye. Florya Chronicles of Political Economy, 8(2), 199–225. [Google Scholar] [CrossRef]
  5. Berezina, K., Bilgihan, A., Cobanoglu, C., & Okumus, F. (2016). Understanding satisfied and dissatisfied hotel customers: Text mining of online hotel review. Journal of Hospitality Marketing & Management, 25(1), 1–24. [Google Scholar] [CrossRef]
  6. Chivu, R. G., Stoica, I., Orzan, M. C., & Radu, A. V. (2018). New trends in marketing mix strategies for digital consumer behavior. New Trends and Issues Proceedings on Humanities and Social Sciences, 5(2), 89–95. [Google Scholar] [CrossRef]
  7. Chuang, C. M. (2023). The conceptualization of smart tourism service platforms on tourist value co-creation behaviors: An integrative perspective of smart tourism services. Humanities Social Sciences Communications, 10(1), 367. [Google Scholar] [CrossRef]
  8. Danish, Q. R., Ali, F. H., Shahid, R., & Nadeem, K. (2019). Impact of online consumer reviews on hotel booking intentions: The case of Pakistan. European Scientific Journal, 15(7), 144–159. [Google Scholar] [CrossRef]
  9. Ding, C., Guo, Q., Rehman, A., & Zeeshan, M. (2022). Impact of environment on hotel customer satisfaction in Southeast Asia: A study of online booking site reviews. Frontiers in Environmental Science, 10, 978070. [Google Scholar] [CrossRef]
  10. Durna, U., Dedeoglu, B. B., & Balikçioglu, S. (2015). The role of service scape and image perceptions of customers on behavioral intentions in the hotel industry. International Journal of Contemporary Hospitality Management, 27(7), 1728–1748. [Google Scholar] [CrossRef]
  11. Francesco, G., & Roberta, G. (2019). Cross-country analysis of perception and emphasis of hotel attributes. Tourism Management, 74, 24–42. [Google Scholar] [CrossRef]
  12. Gellerstedt, M., & Arvemo, T. (2019). The impact of word of mouth when booking a hotel: Could a good friend’s opinion outweigh the online majority. Information Technology & Tourism, 21, 289–311. [Google Scholar] [CrossRef]
  13. Kalashnikova, T., Panchuk, A., Bezuhla, L., Vladyka, Y., & Kalaschnikov, A. (2023). Global trends in the behavior of consumers of retail enterprises in the digital economy. IOP Conference Series Earth and Environmental Science, 1150(1), 012023. [Google Scholar] [CrossRef]
  14. Kitsios, F., Kamariotou, M., Karanikolas, P., & Grigoroudis, E. (2021). Digital marketing platforms and customer satisfaction: Identifying eWOM using big data and text mining. Applied Sciences, 11(17), 8032. [Google Scholar] [CrossRef]
  15. Li, H., Liu, Y., Tan, C. W., & Hu, F. (2020). Comprehending customer satisfaction with hotels: Data analysis of consumer generated reviews. International Journal of Contemporary Hospitality Management, 32(5), 1713–1735. [Google Scholar] [CrossRef]
  16. Li, M., Huang, L., Tan, C. H., & Wei, K. K. (2013). Helpfulness of online product reviews as seen by consumers: Source and content features. International Journal of Electronic Commerce, 17(4), 101–136. [Google Scholar] [CrossRef]
  17. Litvin, S. W., Goldsmith, R. E., & Pan, B. (2008). Electronic word-of-mouth in hospitality and tourism management. Tourism Management, 29, 458–468. [Google Scholar] [CrossRef]
  18. Lu, S., Wu, J., & Tseng, S. L. A. (2018). How online reviews become helpful: A dynamic perspective. Journal of Interactive Marketing, 44, 17–28. [Google Scholar] [CrossRef]
  19. Mudambi, S. M., & Schuff, D. (2010). What makes a helpful online review? A study of customer reviews on Amazon.com. MIS Quarterly, 34(1), 185–200. [Google Scholar] [CrossRef]
  20. Oliveira, A. S., Renda, A. I., & Correia, M. B. (2020). Online reviews: A pathway to improve hotel management. Dos Algarves a Multidisciplinary e-Journal, 36(26), 108–126. [Google Scholar] [CrossRef]
  21. Pacheco, L. M. (2016). An analysis of online reviews by language groups: The case of hotels in Porto, Portugal. European Journal of Tourism Research, 14, 66–74. [Google Scholar] [CrossRef]
  22. Park, S., & Nicolau, J. L. (2015). Asymmetric effects of online consumer reviews. Annals of Tourism Research, 50, 67–83. [Google Scholar] [CrossRef]
  23. Patafta, D., & Milohnić, I. (2022, October 21). Challenges of managerial communication in hotel business operations. Tourism and Hospitality Industry, Congress Proceedings, Opatija, Croatia. [Google Scholar] [CrossRef]
  24. Pontes, A., & Ramos, C. M. Q. (2023). How does social media influence the behavior of hotel consumers. Journal of Tourism, Sustainability and Well Being, 11(2), 116–135. [Google Scholar] [CrossRef]
  25. Serra Cantallops, A., & Salvi, F. (2014). New consumer behavior: A review of research on eWOM and hotels. International Journal of Hospitality Management, 36, 41–51. [Google Scholar] [CrossRef]
  26. Talón-Ballestero, P., González-Serrano, L., Soguero-Ruiz, C., Munoz-Romero, S., & Rojo-Álvarez, J. L. (2018). Using big data from customer relationship management information systems to determine the client profile in the hotel sector. Tourism Management, 68, 187–197. [Google Scholar] [CrossRef]
  27. Tsiotsou, R. H. (2019). Rate my firm: Cultural differences in service evaluations. Journal of Services Marketing, 33(7), 815–822. [Google Scholar] [CrossRef]
  28. Wang, X., Guo, J., Wu, Y., & Liu, N. (2020). Emotion as signal of product quality: Its effect on purchase decision based on online customer reviews. Internet Research, 30(2), 463–485. [Google Scholar] [CrossRef]
  29. Xiang, Z., & Gretzel, U. (2010). Role of social media in online travel information search. Tourism Management, 31(2), 179–188. [Google Scholar] [CrossRef]
  30. Ye, Q., Law, R., Gu, B., & Chen, W. (2011). The influence of user-generated content on traveler behavior: An empirical investigation into the effects of e word-of-mouth to hotel online bookings. Computers in Human Behavior, 27, 634–639. [Google Scholar] [CrossRef]
  31. Zhou, L., Ye, S., Pearce, P. L., & Wu, M. Y. (2014). Refreshing hotel satisfaction studies by reconfiguring customer review data. International Journal of Hospitality Management, 38, 1–10. [Google Scholar] [CrossRef]
Table 1. The most important research studies about online hotel reviews.
Table 1. The most important research studies about online hotel reviews.
ReferenceMain Finding
M. Li et al. (2013)Demonstrate that online hotel reviews can serve as a systematic means of identifying customer satisfaction factors.
Zhou et al. (2014)Offer comparative and benchmarking perspectives on customer satisfaction.
Antonio et al. (2018)Examine how guests from diverse origins and international destinations evaluate hotel experiences.
Tsiotsou (2019)Identify cross-cultural variations in the evaluations provided by tourists from central, eastern, northern, and southern Europe.
Ahani et al. (2019)Determine the key factors influencing hotel selection.
Kitsios et al. (2021)Examine and compare the dimensions of guest satisfaction and dissatisfaction.
Source: own processing.
Table 2. Average rating on Google.com and Booking.com platforms of Hilton hotels for 2024 in Slovak Republic.
Table 2. Average rating on Google.com and Booking.com platforms of Hilton hotels for 2024 in Slovak Republic.
DoubleTree by Hilton Košice
PlatformAverage RatingAverage Rating (%)Number of Reviews
Google.com4.6 from 5922278
Booking.com8.9 from 10892080
DoubleTree by Hilton Bratislava
PlatformAverage RatingAverage Rating (%)Number of Reviews
Google.com4.5 from 5901882
Booking.com8.7 from 10871808
Source: own processing.
Table 3. Average rating on Google.com and Booking.com platforms of Hilton hotels for 2024 in Czech Republic.
Table 3. Average rating on Google.com and Booking.com platforms of Hilton hotels for 2024 in Czech Republic.
Hilton Prague Hotel
PlatformAverage RatingAverage Rating (%)Number of Reviews
Google.com4.4 from 5889450
Booking.com8.2 from 10827615
Hilton Prague Old Town
PlatformAverage RatingAverage Rating (%)Number of Reviews
Google.com4.5 from 5903200
Booking.com8.5 from 10851729
Source: own processing.
Table 4. Average rating on Google.com and Booking.com platforms of Hilton hotels for 2024 in Hungary.
Table 4. Average rating on Google.com and Booking.com platforms of Hilton hotels for 2024 in Hungary.
Hilton Budapest Hotel
PlatformAverage ratingAverage Rating (%)Number of Reviews
Google.com4.6 from 5923504
Booking.com8.8 from 10882815
Hilton Garden Inn Budapest City Centre
PlatformAverage ratingAverage Rating (%)Number of Reviews
Google.com4.4 from 5881400
Booking.com8.9 from 10892315
Source: own processing.
Table 5. Average rating on Google.com and Booking.com platforms of Hilton hotels for 2024 in Poland.
Table 5. Average rating on Google.com and Booking.com platforms of Hilton hotels for 2024 in Poland.
Hilton Warsaw City Hotel
PlatformAverage RatingAverage Rating (%)Number of Reviews
Google.com4.5 from 5906600
Booking.com8.4 from 10842722
Hilton Gdansk Hotel
PlatformAverage RatingAverage Rating (%)Number of Reviews
Google.com4.6 from 5924072
Booking.com8.7 from 10872548
Source: own processing.
Table 6. Standard deviation of selected indicators of customer ratings.
Table 6. Standard deviation of selected indicators of customer ratings.
Cleanliness
PlatformAverage RatingStandard Deviation
Google.com7.9250.919
Booking.com9.0750.191
Location
PlatformAverage RatingStandard Deviation
Google.com8.3750.831
Booking.com9.3000.421
Personnel
PlatformAverage RatingStandard Deviation
Google.com8.2000.641
Booking.com8.9000.302
Wi-Fi Assessment
PlatformAverage RatingStandard Deviation
Google.com4.3752.729
Booking.com5.4874.550
Source: own processing.
Table 7. Verifying the research question trough Student’s t-test.
Table 7. Verifying the research question trough Student’s t-test.
ParametersCleanlinessLocationPersonnelWi-Fi
t-statistics3.88004.8054.8050.821
Average difference1.1500.9250.9251.112
SE difference0.2960.1920.1921.356
p-value0.0060.0020.0020.439
Source: own processing.
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MDPI and ACS Style

Kolesárová, S.; Šenková, A.; Kormaníková, E.; Šambronská, K. The Quality of Hilton Hotel Services in the V4 Countries: The Impact of the Platform on Ratings and Customer Satisfaction. Tour. Hosp. 2025, 6, 169. https://doi.org/10.3390/tourhosp6040169

AMA Style

Kolesárová S, Šenková A, Kormaníková E, Šambronská K. The Quality of Hilton Hotel Services in the V4 Countries: The Impact of the Platform on Ratings and Customer Satisfaction. Tourism and Hospitality. 2025; 6(4):169. https://doi.org/10.3390/tourhosp6040169

Chicago/Turabian Style

Kolesárová, Stela, Anna Šenková, Erika Kormaníková, and Kristína Šambronská. 2025. "The Quality of Hilton Hotel Services in the V4 Countries: The Impact of the Platform on Ratings and Customer Satisfaction" Tourism and Hospitality 6, no. 4: 169. https://doi.org/10.3390/tourhosp6040169

APA Style

Kolesárová, S., Šenková, A., Kormaníková, E., & Šambronská, K. (2025). The Quality of Hilton Hotel Services in the V4 Countries: The Impact of the Platform on Ratings and Customer Satisfaction. Tourism and Hospitality, 6(4), 169. https://doi.org/10.3390/tourhosp6040169

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