Bachelor’s Thesis
Different motivations behind writing positive and negative online reviews
Specialization: Management in the digital age
Name: Yuhuan Shu
Student number: 12341827
Supervisor: Daphne Dekker
Date of submission: 21-06-2020
Faculty of Economics and Business
Statement of Originality
This document is written by Student [Yuhuan Shu], who declares to take full responsibility for the contents of this document.
I declare that the text and the work presented in this document are original and that no sources other than those mentioned in the text and its references have been used in creating it.
The Faculty of Economics and Business is responsible solely for the supervision of completion of the work, not for the contents.
Abstract
Word-of-mouth is becoming a more and more popular topic today. Understanding why customers decide to engage in online reviews is important for hotel marketers because the more online reviews the hotels have, the more impacts will be on the reservation. Thus, the reasons why customers decide to write reviews online need to be learned to make suitable strategies that can foster more positive reviews. However, fewer studies have discussed about the motivations to write online reviews, and the evident distinctions between positive and negative ones have not been focused on. Thisstudy attempts to explore the different motivations behind writing online reviews, and to examine whether there are any differences between positive and negative online reviews. In addition, this study also finds that different reviewers consider different groups of people as the readers of the messages they try to convey (such as making suggestions to hotel managers, warning future customers, etc.). A total number of 140 reviews posted on TripAdvisor were collected in this study. The results of analysis revealed that customers were most frequent to express their own feelings in the reviews. For positive reviews, the three most frequent categories of motivations are expressing positive feelings for reviewers themselves to record experience, showing willingness to return to the hotel as indirect messages to hotels and future customers, and expressing appreciate or thank as direct messagesto the hotel. In contrast, negative reviewers are most likely to vent negative feelings, to show unwillingness to return, and to warn future customers.
Table of contents 1. Introduction ...5 2. Literature Review ...6 3. Method ...10 3.1 Data Collection ...10 3.2 Procedures ...10 3.3 Data Analysis ...13 4. Results ...16 5. Discussion ...19 6. Conclusion ...22 Reference List ...24 Appendices ...28
1. Introduction
Word-of-mouth has become an essential aspect for marketing researchers to focus on, and the impact of eWOM (electronic word-of-mouth) on consumers’ behaviors is more vital in the service industries, such as the hotel industries (Hu & Kim, 2018). Therefore, to understand why customers decide to engage in writing positive or negative online reviews is an essential task for hotels’ marketers, which can help them provide more valuable service for customers and manage the eWOM influences to the hotel in an effective way. There are many studies that have already researched the use or impacts of online reviews (e.g., Fagerstrøm et al., 2016), while less emphasis has been put into researching the motivations behind writing online reviews. Nevertheless, the motivations are important to know because the higher the number of hotels’ online reviews, the higher of the reservation will be made by customers (Tsao et al., 2015). Furthermore, Ong (2012) reports that nearly a half of the business travelers are agree with the opinion that online reviews made by other reviewers have an impact on their choices of hotels. More positive reviews will result in more possible reservations, on the contrary, negative online reviews of hotels may reduce the number of online bookings. Thus, the hotel managers should also take this part into account when defining the strategies because the customer behaviors are complex that not all the customers will behave in the same way due to their different experiences (Gonçalves et al., 2018). In other words, different customers’ motivations to write positive and negative online reviews may have differences.
There are some motivations that have already been pointed out in existing researches. For example, Hu & Kim (2018) point out that customers may write positive reviews for expressing the enjoyment or helping suggest other people have the same positive experience, and they may leave negative reviews to vent their negative feelings or to prevent potential future customers experiencing their bad experience. However, there may be many other motivations behind writing online reviews have not been mentioned in the study. This study will further determine the motivations of writing both positive and negative reviews by looking into the content of online reviews in depth.
The main purpose of this study is to determine the different motivations behind why people writing online reviews, and to research whether the motivations are different from the positive reviews and negative reviews. To develop further, this study also aims to find out who do the online reviewers consider as the readers of their messages contained in the reviews when they write, for example, they write reviews with the intention to convey the messages to themselves (such as recording the experience), to the hotels (such as suggestions or criticism), or to potential future customers (such as recommendations or warnings). By doing this research, managerial implications for the hotel managers are proposed.
To be more specific, there are two main objectives and one major contribution to managerial aspect of this study. Firstly, the motivations behind writing online reviews will be researched in detail, and the receivers of the reviewers’ messages will be determined. Secondly, the differences of motivations between positive reviews and negative reviews will be investigated by listing a cross-table with all the reviews falling into different categories. Combining these two objectives, this study attempts to further widen the views of hotel managers, which may help them better manage the influences of online reviews to achieve higher reservation rates. Moreover, hotel companies can hold the eWOM campaigns to make marketing communications, even though the eWOM is enforced by the customers (Godes & Mayzlin, 2009).
The rest of the paper is structured as follows. Firstly, the relevant studies are introduced in the literature review section. Then it is followed by the method section, which explains the methods used in this study and the data analysis. Next, the study shows the overall findings in the results section. Then it comes to the discussion and conclusion part. In the end of the conclusion, it comes to the limitations of this study and the suggestions for further research in the future.
2. Literature Review
According to Matta and Frost (2011), online reviews is a pretty novel topic. Although there are already some studies that have researched the use, content, impacts, and helpfulness of
online reviews, fewer studies have discussed about the motivation behind writing online reviews, yet understanding the customers’ motivations to write electronic word-of-mouth (eWOM) is quite important for some reasons (Gonçalves et al., 2018). Firstly, Dickinger & Mazanec (2008) stated that online reviews, together with friends’ recommendations, are the two most significant factors that have impacts on hotel reservations. Secondly, when
evaluating which hotel will be a good choice to stay, some difficulties may exist due to the lack of detailed information about the hotel. For this reason, customers may rely more on the online reviews written by the previous customers who have stayed in the hotel before (Liu & Park, 2015). Similarly, since the customers rely more on the peers than the companies, they trust eWOM more than the advertisements, which are the marketer-generated information (Piller, 1999; Filieri, 2016). In addition, Chevalier & Mayzlin (2009) found that companies whose eWOM is more favorable will have a better opportunity to increase their sales volumes, along with the illustration that when customers see the hotel has many positive reviews, they are more likely to choose that hotel (Sidali et al., 2018). On the contrary,
negative online reviews of hotels may reduce the number of online bookings (Ye et al., 2009). Therefore, managing the complaints in online reviews is important, which may have a major impact on subsequent opinions in a positive way (Wang & Chaudhry, 2018).
Berman (2005) suggested that customer delight has a significant effect on positive WOM behaviors. In order to gather more positive reviews, the way to create customer delight should be learned first. According to Kano’s model, customers cannot be satisfied merely by meeting the basic needs, including the service and goods with basic standard (Kano et al., 1984). Basic requirements are the features that customers have already expected and take them up for granted, which will result in serious dissatisfaction if they are not fulfilled, and such negative experience may lead to negative reviews. However, if these must-be features have been fulfilled, consumer satisfaction will not be necessarily occurred. Distinct from customer satisfaction, which exists when one’s expectation is exceeded, customer delight occurs when a customer receives a positive surprise beyond his or her expectations (Magnini et al., 2011). Kano's model made an assumption that a firm can achieve a long-term competitive advantage only through providing
customers delightful experiences constantly to promote positive W-O-M behaviors, which will make its key competitors difficult to imitate (Berman, 2005).
Besides understanding the ways to promote more positive online reviews, understanding the motivations of engaging in online reviews is another key issue that lacks attention. Yoo & Gretzel (2011) demonstrated that the number of customers that engaged in eWOM communications is increasing, nevertheless, the gap between the number of users and the number of reviewers who write actual content is large. In order to foster the benefits from eWOM, hotel markets have to derive a deeper understanding of the reasons why some customers write online reviews while other customers do not, which means that they need to understand the motivations of online reviewers (Hu & Kim, 2018). In the prior study, Cheung & Lee (2012) also stated that there is a lack of understanding of the reasons why the customers decide to share their experiences with others by writing online reviews. Some dimensions of eWOM motivation have been pointed out in the aspects of hospitality and tourism, such as Hennig-Thurau et al. (2004), who are the pioneers in the area of eWOM’s motivations that assisting the platform. They identified 8 different motivations that consumers may have when they engage in eWOM communication, including assisting the platform, venting negative emotions, seeking the advice, concerning other customers, intending to help the company, social benefits, extraversion and positive self-enhancement, and the economics incentives. However, the evident distinctions between positive and negative ones were not shown in the dimensions, while it is reasonable to make the set of eWOM motivations separated because the motivations behind positive eWOM are probably different from that behind negative eWOM. Specifically, customers’ different motivations to write online reviews are related to their different experience of consumption (Hu & Kim, 2018). Some customers who have positive experiences may write positive reviews, while others who experience relatively negative ones may leave negative reviews. As a consequence, different motivations behind writing online reviews should be taken into consideration, and the understanding of if and how are the motivations of writing positive online reviews different from that of writing negative ones is another research area which should be focused on (Gonçalves et al., 2018). Cheung & Lee
(2012) researched the reasons of customers’ positive eWOM, and the result turned out that the enjoyment of helping others is a crucial factor of motivations. In addition, they encouraged further research to explore the motivations of spreading negative eWOM. For example, the reasons why some customers decide to write down negative experience with negative feelings and choose to give low scores/stars in the reviews. When considering the negative reviews, Wetzer et al. (2007) pointed out that negative emotions in such reviews are associated with negative purposes, such as warning others, which may have an impact on the content of the reviews spread to other potential customers. To be more specific, the negative online reviews are likely to convey messages that are hostile to the hotels with the intention to send away potential future customers by warning them to stay away from the hotel.
Different reviews contain different messages. Some of the reviewers write the reviews just for expressing their own emotions, such as expressing positive feelings or venting negative feelings (Hennig-Thurau et al. 2004), without clearly considering who will read their reviews. In other words, they write reviews mainly to record the experiences for themselves (such as ‘I really enjoyed that!’, ‘I like it!’, ‘Disappointed experience!’, etc). Thus, under this situation, the reviews may contain some messages that have impacts on others indirectly or implicitly, but there are no real messages conveyed to other people directly. However, some of the reviewers write the reviews with the clear intention to leave the message for other people directly. For example, the reviews may contain the messages that reflect suggestions to the hotels, or there may be a recommendation/ warning for potential future customers (such as ‘I'd suggest this hotel with no doubts to anyone’, ‘Stay elsewhere!’, etc). As Cheung & Lee (2012) stated, customers can be beneficial to others through writing online reviews, especially when they can prevent others from having the negative experiences that they had.
Sundaram et al. (1998) suggested that hotels’ marketers are imperative to create an environment which is beneficial to develop and spread the positive WOM, and marketing managers also have to understand the ways of WOM operating in the marketplace, by which they can learn to
manage them effectively. Therefore, due to the importance of understanding the motivations of writing online reviews, this study attempts to research the following questions:
What is the motivation behind people writing online reviews, and does the motivation differ from the positive reviews and negative reviews? Furthermore, who do the reviewers consider as the reader of the messages contained in the reviews (themselves, hotel managers, or potential future customers, etc.)?
3. Method
3.1 Data Collection
Gonçalves et al., (2018) encouraged to use qualitative research approaches, which can explore real motivations of writing online reviewers thoroughly. Since online reviews include rich textual information in depth, it is hard to quantify the ambiguous information inside them (Cao et al., 2011). Thus, in this study, online reviews from TripAdvisor were collected for content analysis. Namely, this study is a qualitative research. In order to better explore the motivations behind writing online reviews of hotels, Paris was targeted to be the place to focus on in this study because of its popularity as an international tourism destination.
3.2 Procedures
An inductive approach has been chosen for the purpose of this research. Instead of assuming the existing literature was correct and then test it, which was used in a deductive approach (Saunders et al., 2016), this study is open-minded, which attempts to look further into the data to explore specific phenomenon. In other words, this study aims to generate meanings from the data collected to observe the pattern of the overall data set. For example, to explore whether customers who wrote positive reviews were more likely to give suggestions to others or customers who left negative reviews were more likely to do so, the key messages related to suggestions contained in each review were focused on to see whether the overall reviews showed a regular pattern.
During the process of data collection, firstly, 60 positive reviews and 60 negative reviews were collected from 5-star luxury hotels in Paris in order to maintain the same sample size. All the reviews were collected from TripAdvisor- one of the biggest online international tourism review website. In the beginning, the reviews from the top ranking three 5-star luxury hotels in Paris which met the requirements of data collection were focused on. For each of the three hotels chosen, 20 positive reviews and 20 negative reviews were collected initially. Later on, more reviews from other 5-star luxury hotels in Paris were collected to do further analysis.
You et al. (2000) and Legohérel et al. (2012) stated that travelers with different cultural backgrounds would result in considerably different demand, which might significantly influence their satisfaction and evaluations of the experience in the end. As the most widely used language throughout the world, English speakers, such as most of the Western travelers, were likely to share similar cultures which were very different from non-English speakers, such as many of the Asian customers (Schuckert et al., 2015). Thus, to avoid any cultural differences between Western travelers and Asian travelers that might cause some influences on the results, only reviews written by Western travelers were collected. Similarly, in order to avoid the possible inaccuracy of translation websites, only English reviews were collected. For differentiating the positive reviews between the negative reviews, the star ratings that the reviewers gave to the hotel could be seen as a good indicator. In this study, reviews with 3-star star ratings were considered as a neither positive nor negative option because it corresponded to ‘average’ category on the TripAdvisor website. Therefore, reviews with 3-star star ratings were excluded in this study, only the rest categories were focused on. More specifically, along with the categories on the TripAdvisor website, reviews with 5 stars (Category- Excellent) and 4 stars (Category- Very Good) were considered as the positive reviews, and the reviews with 2 stars (Category- Poor) and 1 star (Category- Terrible) were measured as the negative reviews.
When choosing the hotels to collect reviews, the hotels were sorted by the order of ‘Traveler Ranked’, ranking from the highest scores to the lowest scores. However, since this study only focused on 5-star luxury hotels, the overall scores of the hotel were generally high, which led
to a situation that the amount of negative reviews were far less than that of positive reviews. For example, ‘Le Bristol Paris’- a 5-star luxury hotel that was top ranked 1 in Paris, which only had 13 negative reviews in total. This kind of hotels did not meet the requirement of data collection in this study (20 negative reviews per hotel). Furthermore, although some hotels had more than 20 negative reviews, not all of them were written in English, such as ‘Relais Christine’, which had 23 negative reviews in total while only 19 of them were written in English. In addition, many reviewers did not indicate their locations or nationalities. To ensure accuracy of data that only the reviews written by Western travelers were collected, all this kind of reviews with unknown locations were filtered out. Owing to the difficulty of collecting negative reviews, the hotels were first filtered to come out the ones that meet the data-collection requirements in this study.
During the process of data collection, the reviews were shown according to the default timeline, which displaced from the most recent review to the earliest review. After reading all of the reviews collected, different messages contained in the reviews were analyzed, by which can further categorize them into different groups corresponding with different motivations behind writing reviews. When all the 120 reviews have been categorized, the frequency of positive reviews and negative reviews appeared in each category were then calculated to see whether the positive or negative experience had different impacts on the motivations behind writing online reviews.
After that, further check was done by looking into more reviews, so as to see whether they all fitted into the categories that had been listed in the first data set. If all of them fit into the categories in the list, which means the same things start repeating themselves, then it reflects that the overview is clear enough to complete. However, if some reviews do not fit in either one of the listed categories, it means some other motivations behind writing online reviews exist. Under this situation, the categories have not been completed yet, and more reviews should be collected to do further analysis until all the reviews gathered can be put into the listed categories. To do so, 10 more positive reviews and 10 more negative reviews were collected first, and the
control variables remained the same that only reviews written by Western travelers for 5-star luxury hotels in Paris were gathered. All of these 20 reviews fell into the categories that had been listed before, thus, the overview was clear enough to finish the further check. In the end of this study, the overall result was shown by a cross-table with all the reviews and corresponding categories of motivations on that (Excel file). Additionally, a table with all the motivations was also displayed in the result section, together with the frequency and the percentage of different motivations in positive reviews and negative reviews.
The method used to do the content analysis in this study was inspired by color coding. Firstly, the ‘conditional format’ function in Excel was used to identify different categories of motivations by filling the blocks with different colors. However, a problem occurred that one block could only be filled in one single color, while one review might contain more than a single motivation. To address this limitation, the method based on color coding was adjusted to some extent. For example, one reviewer wrote ‘It is for me a home away from home and makes a very stressful business trip the most enjoyable experience ever. Make sure you enjoy dinner in the hotel’s restaurant Camelia and please book a garden table.’ The first sentence expressed the positive feelings, while the second sentence conveyed suggestions to potential future customers. Under such situation that one review involved more than one motivation, the review was colored by two different colors, corresponding two different motivations (the first sentence was filled in green color, and the second sentence was colored by pink color). Different categories of motivations corresponding to different colors were shown at the beginning of the Excel file (For example, ‘Recommendations to future customers- Brown’ means sentences that demonstrated the reviewers’ recommendations to future customers were colored in brown).
3.3 Data Analysis
To compare the motivations between positive online reviews and negative online reviews, the keywords or key phrases in the reviews were initially paid heavy attention to, which helped to explore the reasons behind writing the reviews. For example, if customers had a positive experience which they were willing to share with others and suggested them to stay, they might
write ‘I highly recommend this hotel!’. In this sentence, the key phrase ‘highly recommend’ showed the strong recommendation and explicit endorsement of this hotel for future customers. To be more specific, it was also the declaration of the reviewer that they found this choice would also be appropriate to others. However, sometimes the recommendation was also stated in an implicit way, such as ‘I like this hotel.’, which showed reviewers’ assertion of their own positive emotion that reflected their own tastes (Packard & Berger, 2017). In the analysis of this research, this kind of implicit endorsement was categorized as the message for reviewers themselves about the expression of their own feelings. Likewise, although many positive reviews did not contain explicit endorsement to potential future customers, the reviewers showed their own strong willingness to return to the hotel next time instead, which was seen as an implicit signal of indirect recommendation to other customers by showing their own satisfaction. Such messages were also viewed as a kind of implicit message to the hotel that they might become their loyal customers. Moreover, some of the reviewers did not recommend the hotel directly, but they mentioned some tips, such as recommending a specific hotel or a specific menu in that hotel, which could also be categorized as a kind of implicit or indirect recommendation to future customers. However, in this study, only explicit recommendations were categorized as direct recommending messages for potential future customers because implicit endorsements might contain other possible messages that needed further research.
On the contrary, Packard & Berger (2017) also stated that if reviewers wrote ‘I did not like it’, the message was more likely to be considered as expressing their own emotional catharsis. Under these circumstances, the reviews were categorized as implicit negative endorsements or negative emotion expressions, which were viewed as the messages to record for reviewers themselves in this study. Reversely, when reviews contained the phrases like ‘do not recommend’, which stated the explicit negative endorsement, then these reviews would be categorized as the direct messages to future customers as a kind of warning signal. Some negative reviews showed criticism to the hotel directly, while although many other negative reviews did not complain or criticize the hotel directly, they described the negative experience
related to hotel’s facilities or staff’s service, which could be seen as implicit messages of criticism to the hotel.
Some of the reviewers could be described as true altruists, which provided much information about the hotels’ facilities and the evaluation of the convenience to tourisms. By providing the related information, they indirectly helped future customers know more about the hotel. In addition, sometimes they also gave some explicit suggestions to future customers and hotels. During the analysis, almost all of the reviews were found to contain the concern for other customers, no matter explicitly (such as explicit recommendations and warnings) or implicitly (such as providing more information to future customers in the description of the experience), which was a primary motivation. To make clear distinctions between different motivations, only the explicit messages wrote with the concern for other customers were categorized as the direct messages for future customers in this study.
Several reviewers stated that it was not the first time they stayed in this hotel. Under these situations, the comparison with the experience in the previous times was likely to exist. For example, some customers had a great stay last time and this experience made them have higher expectations, while worse experience at this time led to the comparison that would cause deeper negative feelings, which would eventually result in more serious negative reviews.
After finishing analyzing all of the 120 reviews, further check was taken by looking into 10 more positive reviews and 10 more negative reviews of 5-star luxury hotels, so as to see whether they all fit into the categories that have been found in the previous analysis. When completing the analysis of the 20 extra reviews, the result showed that all the reviews fell in the listed categories. To put it from another angle, the same categories of motivations started repeating themselves, which reflected that the analysis of the categories was clear enough to complete.
4. Results
Based on the analysis of 140 reviews collected for this study, the overall findings that showed the frequency of each category of motivation in positive reviews and negative reviews were summarized in Table 1.
Firstly, as the most frequent motivation among all the positive reviews collected in the data set, 64 reviews out of 70 (91.43%) expressed positive feelings, and 17 of them just fell in this category of motivation without combining with other motivations. In other words, 53 positive reviews had other motivations besides expressing positive reviews. This kind of motivation was the messages that the reviewers wrote for themselves mainly to record the experiences. Although some reviewers gave positive reviews, 9 reviews mentioned both positive and negative sides of the hotel, rather than describing solely on positive sides. However, surprisingly, 3 positive reviews contained some complaints of some aspects that haven’t met the customers’ expectations by venting negative feelings, especially one review expressed more negative feelings than positive feelings. Moreover, within all the positive reviews collected, the result showed that only 3 people out of 70 left completely objective reviews without expressing their own feelings (without writing emotional words), instead, they mentioned both positive and negative sides of the hotel by describing the facilities they used and the service they experienced.
In addition, 25 out of 70 (35.71%) positive reviews showed their willingness to come back next time, which were indirect messages to both hotels and future customers. Furthermore, 17 out of 70 (24.29%) positive reviews explicitly stated their recommendations to future customers (such as the reviews contained the word ‘recommend’). In this category, reviewers considered
the future customers as the readers of the direct messages they try to convey. Similarly, 14 out of 70 (20%) positive reviews stated explicit suggestions as direct messages to future customers. As frequent as the motivation of showing willingness to return, 24.29% (17 out of 70) positive reviews explicitly expressed thank or appreciate to the hotel and its staff because of the enjoyable experience, which were seen as the direct messages to the hotel. However, only 7.14% (5 out of 70) positive reviews gave definite suggestions as direct messages to the hotels.
When considering other categories of motivations in positive reviews, taken for granted, no reviews conveyed warning to future customers, only 2 reviewers stated criticism to the hotel, and nearly no reviewers stated unwillingness to come back next time except one of them.
Secondly, within all the negative reviews collected, 66 reviews out of 70 (94.29%) vented negative feelings, which were the messages that the reviewers wrote mainly to record the experiences for themselves. Specifically, 8 of them purely wrote reviews under this motivation by telling the unpleasant story with negative feelings while without suggesting anything, namely, 58 of them wrote negative reviews together with other motivations. However, 31 reviews mentioned both positive and negative sides of the hotel instead of only telling negative aspects, which could be viewed as implicit tips to future customers by providing more detailed information about the hotel. Moreover, 27.14% (19 out of 70) negative reviews stated explicit warning to future customers (such as ‘would not recommend’, ‘Do not waste your time/ money’, ‘Skip this hotel!’, etc), which considered future customers as the readers of the direct messages in order to prevent them having the same negative experience.
In addition, among these negative reviews, 24 out of 70 (34.29%) reviewers showed definite unwillingness to return back to the hotel next time as indirect messages to hotels and potential future customers. Within these reviewers, several of them were even loyal customers of the hotel’s brand, while the one-time negative experience in one hotel in a specific location caused their loss of loyalty to all the hotels under the whole brand. Likewise, 13 negative reviews included clear information that they had stayed in this hotel before, which caused the comparison of this time’s experience to the previous experience. The results showed that when
people had a positive experience last time or they had loyalty to the hotel, their expectations about this hotel or hotel’s brand would be higher in the future, which would cause deeper negative feelings when they had worse experiences than in the past. Nevertheless, some reviewers mentioned that they already had negative reviews last time, and this time the experience was still bad.To explain why they still chose this hotel after last time’s negative experience, one possible reason came out from the analysis. A few negative reviewers illustrated that they might still consider return to the hotel if the hotel brushes up the overall service although they already had the bad experience. To put it from another way, they were willing to give the hotel one more chance. For example, one positive review mentioned that this was the second time they stayed in this hotel, while during the first time, their expectation has not been met and they complained. After they left, the hotel contacted them and promised to make it up to them during their second time around, and they gave the hotel one more chance. Fortunately, the hotel eventually delivered what they promised when the customers returned back. At the end of the review, the reviewer wrote ‘They didn't simply meet expectations. They blew them away. I'm giving them five stars, but I think for this trip that's not good enough. They deserve six.’, which was an extremely high praise and expressed highly positive feelings. This review showed the importance of hotel’s attitude and reaction to deal with guests’ complaints and negative expression, and a good solution to the problem that satisfied customers was assumed to foster customers’ deeper motivation to express more positive feelings in the reviews than in the normal.
In contrast to the positive reviews, not surprisingly, within all the negative reviews, no reviewers (0%) chose to express positive feelings, to express thank to the hotel or the staff, to show willingness to return, or to recommend to future customers. Instead, 10 out of 70 (14.29%) negative reviews criticized the hotel directly as the messages to the hotel managers. Moreover, 27.14% (19 out of 70) of them explicitly indicated warning to future customers or they suggested potential future customers stay in another specific hotel directly, which were direct messages conveyed to future customers as their readers. However, only a few negative reviews gave suggestions to the hotel (7.14%), comparing to 24.29% of them that gave explicit tips to
future customers, which indicated that people were more willing to write messages to express their own feelings and to give suggestions to future customers, rather than to the hotels.
Furthermore, among all the positive reviews and negative reviews gathered, almost all of the reviews contained the concern for other customers, no matter explicitly or implicitly, which was a primary motivation. To be more specific, explicit concern were direct messages to future customers, such as direct recommendations, warnings, or suggestions to them, etc., while the implicit concern included providing more detailed and objective information for future customers, such as the hotels’ facilities, services, the description of the distance and convenience (the methods to go, such as the metro or bus) from the hotel to go to the famous tourisms in Paris, etc. Such indirect messages with implicit concern was a kind of tips for future customers that they might consider these aspects when choosing hotels.
5. Discussion
First, the findings in this study further develop the idea that motivations of writing positive reviews are different from that of negative ones, which is consistent with Hu & Kim (2018)’s opinion that the distinctions of motivations between positive and negative reviews should be focused on because the eWOM customers spread are related to their different positive or negative experiences. Different people tend to have different motivations, corroborating the findings of Gonçalves et al., (2018), not all consumers are the same or similar. Therefore, hotels’ marketing managers should take this aspect into account when determining suitable strategies. However, contradictory to the finding of Gonçalves et al., (2018) that stated one motivation alone was not enough to predict the hotels’ online reviews, this study showed that although 70% (98 out of 140) of the reviews revealed more than one explicit motivation, 30% (42 out of 140) of the reviews contained only one single motivation. In addition, positive economic incentives and negative economic incentives were the two other categories of motivations mentioned by Hu & Kim (2018), while these two categories could not be found by doing the content analysis in this study.
This study shows that the most frequent motivation in positive reviews is ‘express positive feelings’, in contrast to the category of ‘vent negative feelings’, which is the most frequent motivation in writing negative reviews. This is in line with the findings of Hu & Kim (2018) that customers are likely to write positive reviews for expressing the enjoyment and leave negative reviews to vent their negative feelings. Besides, the findings showed that 27.14% negative reviews stated explicit warning to future customers, such as ‘Skip this hotel!’, which were direct messages to potential future customers in order to prevent them having the same negative experience. This finding is also in conformity with Hu & Kim (2018)’s finding that reviewers who stated warning to future customers wrote online reviews with the potential motivation to help prevent potential future customers experiencing the bad experience like them.
Wetzer et al. (2007) stated that negative emotions in the reviews were related to negative purposes, which were likely to have an impact on the content of the reviews spread to other potential customers. However, partly inconsistent with Wetzer et al. (2007), although some of the negative reviews that vent negative emotions were associated with negative purposes, such as warning others, not all of them were related to negative purposes. In this study, only 19 out of 70 of the negative reviews collected made a warning signal to future customers that they would better stay away from this hotel, which would possibly make a negative influence on potential reservations, while the rest did not.
The results also revealed that some of the reviewers could be described as true altruists that they made many suggestions to future customers and to the hotels. For example, one review wrote that ‘Service is very good, but smoking should not be allowed on the terrace inside. It penalizes all the guests that do not smoke.’, which left direct message to the hotel with suggestion and provided information that would help people who hate the smell of smoking avoid experiencing that. In keeping with the previous finding suggested by Hennig-Thurau et al. (2004), true altruists were both motivated by helping other customers and helping the hotel company strongly. Additionally, this study found that almost all of the reviews involve the concern for other customers, explicitly or implicitly, in line with Hennig-Thurau et al. (2004)’s
statement that the concern for other customers is a common category of motivation for all customers’ motivation collections.
Besides, this study assumes that if the hotel gives a good solution or reaction to the problem that a customer complained and makes them satisfied by delivering the promise, customers will have deeper motivation to express more positive feelings in the reviews than normal positive reviews. In line with Wang & Chaudhry (2018), who stated that managers should customize responses to each negative review for complaint management, which will enhance the subsequent positive effects. However, only one review in this study matches with this situation, which needs to be tested by more data in the further research.
A surprising finding shows that 3 positive reviews contained some complaints, and one of them even expressed more negative feelings than positive feelings. As a new finding, the motivation behind giving positive reviews while having negative experience needs to be examined in the future. Moreover, the result showed that reviewers are more willing to express their own feelings and to make suggestions to future customers, instead of giving suggestions to the hotel (the frequency of this category is the same in positive and negative reviews). It means that reviewers have deeper motivation to convey direct messages to themselves and future customers, rather than to the hotels, which is a novel contribution to the existing literature, and the further research needs to test this finding more deeply.
This study mainly contributes to the management aspects of the hotels by applying managerial implications. By researching the motivations behind writing online reviews and the differences of motivations between writing positive reviews and negative reviews, this study further widens the thoughts of hotel managers by letting them understand more deeply about the motivations of writing online reviews, which can help them better manage the influences of online reviews of the hotel in the future. After that, more benefits may be followed by, such as more possible reservations.
6. Conclusion
Although the use and impacts of eWOM have been researched in many studies, fewer studies have researched about the motivation behind writing online reviews. Nevertheless, this aspect is quite important for hotels’ marketing managers to understand because customers may trust the online reviews that written by previous customers as much as the recommendations from their friends, which will further cause significant impacts on the number of hotel reservations in the future. Since the more positive reviews, the more possible reservations, the hotels’ managers should take this part into account when thinking about the strategies. Although some studies researched some motivations to spread eWOM (such as Hennig-Thurau et al., 2004; Yoo and Gretzel, 2011; etc.), the differences of motivations between positive reviews and negative ones were not indicated, which should be separated because customers had different reactions according to different experiences. Namely, customers’ motivations to write online reviews may be influenced due to the differences of experiences. Thus, this study examined the different motivations behind writing positive online reviews and negative online reviews, and who do the reviewers consider as a reader of the messages the reviews they tried to convey.
The results showed that in positive reviews, the most frequent motivation is to express positive feelings for reviewers themselves to record experience. The following second frequent motivation is to show willingness to return to the hotel, which is the kind of indirect messages to hotels and future customers. In addition, to express appreciate or thank to the hotel as direct messages is the third popular category of motivation in positive reviews, which is as frequent as the motivation to recommend to future customers explicitly and directly. However, no reviews conveyed warning to future customers, and nearly no reviewers criticized to the hotel or stated unwillingness to return next time.
In contrast, the most frequent motivation in negative reviews is to vent negative feelings, followed by the messages showed unwillingness to return. As the third popular category of motivation among negative reviews, warning to future customers are direct messages to prevent them from experiencing the same disappointed experience. Distinguishable to positive reviews,
no reviewers chose to express positive feelings, to express thank to the hotel or the staff, to show willingness to return, or to recommend to future customers.
The findings in this study have to be explained in light of some limitations. Firstly, this study only focuses on Western travelers, which ignores the Eastern travelers. However, Eastern travels occupy a large part in the tourism, which should also be analyzed. Secondly, Paris is the only place that focused on in this study, and the data set is not big enough to allow for the generalization. Likewise, a large majority of the reviews collected were written by Americans and Europeans from several specific countries, which caused the lack of diversity of reviewers.
Furthermore, besides the luxury hotels, other types of hotels can be further analyzed to come up with a deeper and more completed conclusion. Also, only the reviews written in English were collected, while if possible, reviews in other languages should also be looked at to gather more different views which can result in a more concrete outcome. Lastly, only the explicit motivations are categorized in this study due to the ambiguity of the implicit ones, while further research should also research the implicit messages to gather more comprehensive outcomes. In short, despite these limitations, this study provides evidence for the distinctions between motivations behind writing positive and negative online reviews, and the managerial implications for the hotel managers are strongly proposed as the main contribution.
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Appendices
