THROUGH THE EYES OF THE TRAVELER: CONSUMER EVALUATION OF HOTELS IN EASTERN EUROPEAN CAPITALS COMPARED WITH WESTERN, SOUTHERN, AND NORTHERN EUROPE

The tourism and hospitality industry in Eastern Europe has undergone substantial transformations since the fall of the Iron Curtain and the European Union eastward enlargement. This study investigates how Eastern European hotels are evaluated by travelers in comparison with other regions in Europe and what perceived strengths and weaknesses of Eastern European hotels can be identified. For this purpose the study analyzes travelers’ evaluations of 2,153 hotels in 25 European capitals on the leading travel platform Tripadvisor.com. The research methodology applies a novel approach by conducting content analysis of the structured five-point ratings on seven evaluation criteria. The findings show that hotels in Eastern European capitals are very positively evaluated in the 4 and 5-star classification categories. Perceived drawbacks of hotels in Eastern European capitals are the location as well as the performance in the 3-star hotel category. Based on the findings the paper discusses implications for research and practice


INTRODUCTION
The fall of the Iron Curtain and the enlargements of the European Union during the past decade resulted in the economic and political integration of a number of postcommunist Eastern European countries.This had a large impact on the tourism industry in this region.The political developments increased its opportunity to be accessible and attractive for international tourists.Formerly stateowned tourism companies such as the Russian Aeroflot or the Intourist hotel operator expanded their services especially to tourists from regions who had limited access before (Anonymous, 1991).
For a better understanding of how the Eastern European tourism industry developed with increasing openness and economic integration deeper insights into the current situation in this area are needed.A region's image and attractiveness is influenced by several local conditions, including the attractions as well as the tourism infrastructure.One important dimension that impacts a destination's image is the quality of the local hotels as perceived by travelers (Law and Cheung, 2010;Tavitiyaman and Qu, 2013).
The study presented in this paper addresses this topical issue by empirically evaluating travelers' perceptions of hotels in European capitals.For this purpose the study utilizes a selection of the large amount of data that is being disseminated voluntarily by consumers on the Internet, also referred to as user-generated content.More specifically, the study analyzes travelers' consumer reviews provided on the online travel platform Tripadvisor.com.This research design allows the collection of aggregated quantitative data consisting of consumer evaluations to provide insights into how travelers perceive the performance of European hotels in different dimensions (Jeong and Jeon, 2008).The analysis of user-generated content received increasing attention in research as it offers valuable insights into experiences, ratings, and opinions of customers who are the ultimate target group of all institutions involved in the travel business.These findings are not only relevant against the background of the interrelations between economic integration and tourism from a scholarly perspective.They also have strong practical implications for organizations in the tourism industry, including hotels, travel agencies, transportation service providers, and governmental tourism bureaus.
The paper is organized as follows: The next section discusses Eastern Europe as an emerging tourism region, followed by a literature review on the methodology of content analysis of online consumer reviews.The subsequent section presents the analysis results of the customer evaluations of 2,153 hotels in 25 European capitals.The paper closes with a discussion of the findings and implications for research and practice.

TOURISM DESTINATIONS IN EASTERN EUROPE
During the communist era, tourism in Eastern Europe was dominated by domestic traveling or traveling across countries within the region.Leading institutions in the transportation and hospitality business were state-owned corporations that expanded their services after the end of communism (Anonymous, 1991).The fall of the Iron Curtain led to two developments.First, there was a partly decrease of Eastern European tourists who now traveled to other destinations.Second, Eastern European destinations got opportunities to open themselves for Western European and overseas tourists (Hughes and Allen, 2009).Eastern European countries emerged as tourism destinations over a period of two decades, although the individual countries experienced different developments (Hughes and Allen, 2009).The accession of some Eastern European countries to the EU further facilitated traveling and positively impacted the image of these countries among travelers because they were now viewed more "European" (Puczko and Ratz, 2006).As a result, the number of tourists visiting Eastern European countries increased significantly during the last years (see Table 1).Substantial changes in the Eastern European hospitality landscape were driven by the expansion of international hotel chains (Churchill, 2004) that lead to a substantial modernization and increased attractiveness for international business and private travelers (Spritzer, 2005).The 2009 economic crisis had a strong impact on the hotel business in Eastern Europe and affected the hotel value per room more than the average in Europe.Since 2010, however, Eastern European hotels recovered and reached the highest value per room throughout Europe in 2011 and 2012 (Bertschi and Perret, 2014).(Hughes and Allen, 2008).Perceived facilitators of traveling to Eastern European destinations are low costs whereas perceived inhibitors are personal safety and the weather.Visitors have a better overall attitude toward Eastern European destinations as their image is more influenced by the positively associated cultural attractions whereas non-visitors are more influenced by perceptions on conflicts and the communist past (Hughes and Allen, 2008).

ANALYSIS OF ONLINE CONSUMER REVIEWS Online Consumer Reviews as a Source of Consumer Insights
The Internet enabled interactive communication that allows users to express their views and opinions in many different ways by providing user-generated content.Especially when it comes to consumer evaluations of products and services that are offered by commercial firms, the analysis of user-generated content can provide valuable insights into consumer attitudes and behavior to an extent that goes far beyond traditional word-of-mouth and marketing research (Godes and Mayzlin, 2004).
Previous research showed that online consumer reviews can have a significant positive impact on sales (Chen, Wu, and Yoon, 2004;Chen and Xie, 2008;Chevalier and Mayzlin, 2006).Consumer reviews appear in a structured and unstructured, text-based form (Miao and Li, 2010) as well as a combination of both (e.g. on Amazon.com, Tripadvisor.com, Expedia.com).Structured reviews include numerical ratings, comparable to Likert scales whereas text-based reviews consist of freely written text.Research on information systems discovered the potentials of analyzing the content of consumer reviews in order to gain deeper insights into product evaluations, but also relevant product attributes, concepts, attitudes, or sentiments appearing in consumer reviews (Miao and Li, 2010).

Online Consumer Reviews in the Tourism Industry
Online consumer reviews play a particularly important role in the tourism industry due to its key characteristics as a service sector.Tourism services can only be evaluated after consumption, thus they are experience goods.They differ in quality and are largely influenced by the consumers themselves (Madlberger, 2014).Among the different tourism services, hotels are one key component that has a large impact on travelers' experiences with a trip.Customers cannot verify the quality of a hotel prior to consumption.This increases customers' uncertainty about the expected quality and raises the desire to obtain more information prior to booking (Lockyer, 2007).
Consumers are consulting online reviews to an increasing extent in many contexts.In 2013, 85 percent of North American consumers read online consumer reviews, among them 30 percent who do this regularly.This number had increased sharply compared to 2011 and thus is expected to increase further.Hotels are ranked third in terms of online consumer review consumption by industry.27 percent of North American consumers read online reviews on hotels during the last 12 months, compared to 61 percent readers of reviews on restaurants/cafes and 32 percent on doctors/dentists (Anderson, 2013).
A sensitive issue of online reviews is their authenticity, that is, the extent to which reviews were indeed written by consumers and not manipulated by service providers such as hotels.An investigation by the Advertising Standards Authority concluded that Tripadvisor was not allowed to claim that reviews posted on this site were "from real travelers, or were honest, real, or trusted" as the site does not provide any verification of reviews (Hall, 2012).Thus it has to be expected that not all reviews are true consumer evaluations.On the other hand, several information systems researchers investigated the issue of fake or manipulated reviews and showed that the majority of reviews are accurate (Ong, 2012;Barsky and Honeycutt, 2011).Further, consumers largely trust online reviews on platforms such as Tripadvisor (Hsu, Chen, and Ting, 2012), thus it can be concluded that the impact of consumer reviews on purchasing decisions is not substantially harmed by fake reviews.Since the study at hand provides a comparison of average numerical ratings, it is further not expected that fake reviews will significantly distort the results.

RESEARCH METHODOLOGY
The goal of this research is a first in-depth analysis of consumer evaluations of hotels located in European capitals.For this purpose we collected data on the structured consumer ratings of 2,153 hotels in 25 capitals on European territory from www.tripadvisor.com.This traveling platform was selected because of its size and market position.As of mid 2014, Tripadvisor had 280 million unique monthly visitors and more than 170 million reviews on 4 million accommodations, destinations, and restaurants (Tripadvisor, 2014).Tripadvisor contains reviews in numerous languages from different types of travelers, such as families, couples, single travelers and business travelers.Like previous studies (Jeong and Jeon, 2008;Melián-González, Bulchand-Gidumal, and López-Valcárcel, 2013) we used consumer review data from Tripadvisor because of its market position.This allows us to investigate a large scope of online consumer reviews and at the same time to collect data from one source which increases comparability.All European capitals (inside and outside the European Union) were considered for the study.Several capitals, however, were excluded from the study because they showed a small number of evaluated hotels on Tripadvisor.To avoid any potential bias due to small sample size, we set a cutoff point at 50 eligible hotels per city.For this reason, for example the capitals Belgrade, Helsinki, Nicosia, Ljubljana, Reykjavik or Bern were excluded.For the selection of the hotels we applied the following procedure: For capitals that showed between 50 and 100 eligible hotels on Tripadvisor, we included all hotels in the sample.Among capitals with more hotels we randomly selected 100 hotels.Table 2 shows the number of analyzed hotels.
Next, we accounted for a possible impact of the official hotel star classifications on consumer expectations and evaluations (Ramanathan, 2012;Jeong and Jeon, 2008).We selected hotels between the 3-star category and the 5-star category but excluded hotels classified in lower categories and hotels without a star classification.With an increasing number of stars hotels have to fulfill a growing number of predefined service categories (e.g., as specified on www.hotelstars.eu).Hence we conclude that the variance of performance is decreasing and the comparability between hotels is increasing the higher the classification is.Since we did not differentiate between hotel chains and independent hotels in this initial study, we aimed at reaching a maximally similar number of hotels within each star category across the investigated cities by determining a sampling quota.
The data collection procedure was as follows: For each city within the sample, a list of all hotels reviewed on Tripadvisor was created.Next, the list was split into 3-star or 3.5-star hotels, 4-star or 4.5-star hotels, 5-star hotels, and others.Hotels in the category "others" were deleted.For the remaining hotels, a random selection within each category was made so that the following quota was reached: • 10 5-star hotels per city • 40 4-star or 4.5-star hotels per city • 50 3-star or 3.5-star hotels per city If a city had less than 100 hotels rated on Tripadvisor we analyzed all hotels of that city with at least 3 stars but keeping the share of each star category as constant as possible.For each hotel, the following average numerical ratings were collected (see also Figure 1): • Overall rating  The analyzed ratings are displayed by Tripadvisor and show the average of each rating category.Tripadvisor rounds the data to 0.5 points, that is, the best average ratings are rounded to 5.0, the second best average number is 4.5 etc.For hotels that have a small number of ratings, these average values are not displayed.In such cases, these hotels were replaced with other randomly selected hotels from the same star classification.
The data was entered into a spreadsheet, exported, and analyzed with SPSS 22. Data analysis was done with single-factor analysis of variance (ANOVA).

Data collection took place between late 2013 and mid
2014 by four graduate students who received a thorough training beforehand.Samples of the collected data were double-checked for correctness and accuracy on all steps of the data collection procedure including hotel selection.

City Ranking by Average Overall Performance
First, the overall ratings were analyzed.Overall ratings ranged from 4.01 to 3.55 on a 5-point scale (5 being the best rating).The median is 3.92.The differences between the cities' rating means were tested for significance with ANOVA.The F value is 4.195 with a p value < 0.001, thus the differences are significant.Table 3 summarizes the average overall ratings.Copenhagen The data shows that among cities that are ranked higher than the median of the city averages (3.92) there are many Eastern European cities.In order to control for any possible differences in average ratings caused by city characteristics, we ran an ANOVA on the impact of city size as well as the number of visitors on the consumer evaluations.We operationalized city size by the number of inhabitants, conducted a median split, and compared cities with more inhabitants than the median (1.2 million) with those that have less.Similarly, we considered the number of visitors as specified by Euromonitor (2014), and conducted again a median split (at 3 million annual visitors).The analyses show that there are no significant differences in the overall ratings between the groups by city size and number of visitors.Table 4 shows the respective top five cities in terms of the sub-categories.Especially hotels in Lisbon, Bratislava, and Warsaw are repeatedly placed at favorable positions on the subcategories.An analysis by city size and number of visitors shows few significant differences in several sub-categories.When it comes to location, hotels in cities below 1.2 m inhabitants are rated better which can be caused by overall smaller distances in these cities and a resulting better perception on the hotel location.Also service is evaluated significantly better in the group of smaller cities.When it comes to the number of visitors, we observe significant better ratings on sleep quality in cities with less annual visitors.All other differences are not significant.

Hotel Ratings by Star Classification
The performance of hotels varies largely by star classifications.Although customers are likely to reflect star classifications in their evaluations, we expect to see significant differences between hotels in different star classifications, even if they vary across countries.In particular, we expect that 5-star hotels will receive the overall best evaluations and 3-star hotels the most critical ones.This expectation is fully met as the data in Table 5 shows.All mean differences are highly significant at a p < 0.001 level.The differences between the evaluations across the star ratings are generally high as the range lies between 0.59 and 0.78 with one exception, that is, value where the range amounts to only 0.29.This result is plausible since value is the only criterion that is related to the price of a hotel.Higher star classifications are usually associated with higher rates although hotel rates are also influenced by other factors including the season, duration of stay, overall price level of the country, or location within the city.For all criteria except for rooms, the difference between 4 or 4.5-star hotels and 5-star hotels is larger than the difference between 3 or 3.5-star and 4 or 4.5-star hotels.

Hotel Ratings by European Regions
To investigate particular differences in hotel evaluations across Europe and compare Eastern European hotels with hotels in other geographic areas, we defined four European regions based on the classification by the United Nations Statistics Division (2014) and assigned the cities accordingly: Western Europe (Amsterdam, Berlin, Brussels, Paris, Vienna), Eastern Europe (Bratislava, Bucharest, Budapest, Kiev, Moscow, Prague, Sofia, Warsaw), Southern Europe (Athens, Lisbon, Madrid, Rome), and Northern Europe (Copenhagen, Dublin, London, Oslo, Riga, Stockholm, Tallinn, Vilnius).To control for differences in city characteristics again we compared city sizes and number of visitors in the regions.For this purpose we created a cross table that displays the relationship between city size and region.This analysis shows that Eastern European cities in the sample have significantly more observed large cities above 1.2 m inhabitants than it would be expected in a random distribution (p = 0.027).Further we created a cross table on the number of visitors in the four regions.The data shows no significant differences here.
We calculated the means of the consumer evaluations on the sub-categories and analyzed the significance levels of mean differences between the regions with ANOVA.The results are shown in Figure 2. Significant differences between the regions are marked with an asterisk.

Figure 2. Average Ratings by Regions
The findings show that all differences between the regions except the overall ratings and cleanliness are significant.The average overall rating is 3.87 and therefore lower than the average ratings on the sub-categories.Among the sub-categories, the largest differences in the cross-regional comparison can be found on location where Eastern European hotels were evaluated significantly lower than hotels in the other regions.It has to be considered however that consumers' perceptions on location can be determined by several factors that go beyond the mere place a hotel is located at.The larger the city and/or the smaller a city's transportation infrastructure the more hotel location can be viewed critically.Thus the consumer ratings on location can be influenced by the larger city sizes of Eastern European capitals.Concerning sleep quality and rooms Eastern European hotels achieved the highest ranking whereas Western European hotels are ranked lowest.In terms of service and value, Southern European hotels are ranked most favorably.Eastern European hotels were also ranked high in terms of value.Cleanliness did not show any significant differences between the regions and was generally evaluated positively with an average rating of 4.16.

Hotel Ratings by European Region and Star Classification
As research showed, consumers' expectations on hotels are influenced by hotels' star classifications (Ramanathan, 2012).Hence we differentiated the data by regions and star classifications.This differentiation may also be useful for travelers who consciously decide on a particular hotel star category, for example if they book a hotel for a business trip and must select a particular hotel star category or hotel chain.The following Figure 3 shows the ratings by regions in the 3 and 3.5-star categories.In this star category all differences between the regions are highly significant.In all evaluation criteria hotels in Southern European capitals are ranked best.Eastern European hotels show the least favorable rankings particularly on location as well as in the overall ranking.The location rating can again be partly explained by the city size.Figure 4 shows the average ratings by regions in the 4 and 4.5-star category, respectively.The picture is different in this star classification category.The average ratings on location, sleep quality, rooms, and value show significant differences between the regions.In contrast to the 3-star category 4-star hotels in Eastern European capitals perform significantly better compared to the other regions.For sleep quality, rooms, and value, Eastern European hotels show the highest ranking.Only again in terms of location this region shows the poorest evaluations although the difference to the other regions is smaller in this star category.

DISCUSSION
The findings of the analysis provide insights into how travelers reported their experiences with hotels on Tripadvisor in different European capitals.It is important to mention that these findings represent a part of the travelers' views and not an objective performance evaluation of the hotels analyzed in the sample.However, the traveler view is important information in different ways.First, online reviews serve as an orientation and decision support for other travelers who plan their trips and select hotels.Since they largely trust the information displayed in online reviews their booking behavior is influenced by the reviews.Second, the perceived performance of tourism services such as hotels influences travelers' image of the destination (Law and Cheung, 2010;Tavitiyaman and Qu, 2013).Thus the traveler ratings on hotels can be considered a possible impact factor on city image and perceived attractiveness.Third, data from consumer reviews can be used as a helpful source of information for the hotels themselves as they can compare their average performance with those of comparable competing hotels and thus identify areas of strengths and improvement potentials.
The results show that in general hotels located in Eastern European cities are favorably evaluated by travelers and frequently exceed the ratings of hotels in Western, Southern, and Northern Europe.The results also show strengths and improvement potentials of hotels in Eastern European capitals.First, we can observe a clear pattern of performance particularly in Eastern Europe.Across all star classifications Eastern European hotels were reviewed most critically on location.Besides the actual location within a city, the perception of location quality can be influenced by key characteristics of the city, most importantly by its size.Among the investigated cities, Eastern European capitals show a higher portion of large cities than the other regions.As a result, distances within the city are likely to be larger and thus destinations are more difficult to reach.Another issue may be available transportation facilities.If travelers have satisfactory possibilities for public or private transportation, they are more likely to be satisfied with the location of a hotel.Further, the context of visit may influence the perception on the evaluation criteria as private tourists move to different attractions whereas business travelers may spend the time at fewer destinations.From the hotel perspective, location is the only investigated criterion that cannot be changed by a hotel without the excessive effort of relocation.Thus hotels that indeed suffer from an unfavorable location have to focus on other areas to compensate this weakness.The overall ratings, however, show that consumers' critical perceptions on one criterion can be offset by a high performance in other criteria.
Second, there are significant differences in performance across the hotel star classifications.Eastern European hotels are perceived very positively in the 5-star category and favorably in the 4 and 4.5-star category.In the 3 and 3.5-star category Eastern European hotels are evaluated more critically.Thus to increase customer satisfaction, particularly 3 and 3.5-star hotels in Eastern Europe should raise their quality to catch up with other European regions.
The reasons for the favorable rating of Eastern European hotels cannot be derived directly from the collected data without analyzing the review texts.However, a possible driver may be a fast modernization of the hospitality infrastructure in the 1990s (Ghitelman and Nigro, 1996) as well as the expansion of Western hotel chains into Eastern Europe (Churchill, 2004).According to the Hotel Valuation Index, Eastern European hotels recovered from the economic crisis 2009 more than hotels in the other European regions.Between 2011 and 2012 Eastern European hotels showed the highest value per room (based on 4 star and 5 star hotels) among European hotels (Bertschi and Perret, 2014).This development is highly consistent with the collected Tripadvisor data.Since hotel quality impacts a destination's image (Law and Cheung, 2010;Tavitiyaman and Qu, 2013), this overall favorable evaluation can further contribute to a positive image of Eastern European travel destinations.

CONCLUSION
The study is based on data that was provided voluntarily by travelers, it represents a consolidated view on hotels in the investigated cities and the corresponding regions that can influence expectations and purchase decisions of users consulting Tripadvisor for planning their trip.Although the study is based on a large database that reflects the aggregate evaluations of a big community of travelers it has some noteworthy limitations.We could not control for any potential bias in the consumer reviews, e.g., whether consumers who evaluate Eastern European hotels significantly differ from consumers who evaluate hotels in other regions in terms of geographic or demographic attributes.On the other hand, this information is not primarily relevant for the readers of online reviews and thus is not expected to influence their attitudes.Another limitation is that we did not control for potentially further relevant traveler characteristics, e.g., the share of reviews posted by business travelers.Concerning the hotel characteristics, additional attributes of hotels, e.g., hotel chain vs. independent hotel, average room rate etc. could influence the evaluations, but were not included in the analysis.Traveler and hotel characteristics might influence the results if they are Despite the limitations of the study, we can draw important implications from this research.The findings show several avenues of further performance improvement of hotels not only in Eastern European, but also other European cities.The data shows a performance profile of the hotels in the different star classification criteria.Although each single traveler usually looks at only a small number of consumer reviews, it is more likely that s/he will find positive evaluations on hotels in a particular city if the average rating is positive, too.Thus we can conclude that the current performance of hotels in Eastern European capitals will positively influence the cities' image and attractiveness and travelers' willingness to visit them.For hotels in the capitals of the other European regions, the findings show that Eastern European capitals are a counterpart that should not be underestimated, but must be perceived as important players that may be in a favorable position when it comes to competition between European cities as travel destinations.

Figure 1 .
Figure 1.Screenshot of a Hotel Review Page on Tripadvisor.com

Figure 3 .
Figure 3. Average Ratings by Regions in the 3 and 3.5-Star Category

Figure 4 .
Figure 4. Average Ratings by Regions in the 4 and 4.5-Star Category

Figure 5 .
Figure 5. Average Ratings by Regions in the 5-Star Category the investigated cities. Lastly, we focused on descriptive results, thus future research should consider causal antecedents of perceived hotel performance.

Table 2 .
Sample Description

Table 3 .
Cities by Average Overall Consumer Ratings

Table 4 .
Top Five Cities by Sub-Categories

Table 5 .
Hotel Ratings by Star Classification