Online Reviews Influence on Travel Industry

Introduction

Active development of the newest technologies and their introduction to most of the spheres of human interactions have a direct influence on the evolution of social and economic relations (Audretsch & Welfens 2013; Burns 2015). It is true for all countries regardless of the level of their development and the state of industrialisation as well as companies regardless of their size and sectors of operations (Etzkowitz & Leydesdorff 2014; Gatautis 2015; Gilpin 2016). Doing business is not an exception to the overall rule, as the newest technologies, especially free access to the Internet, have greatly affected the way this area of relations is organised due to the unlimited communication opportunities that affect consumer behaviour (Besley 2015; Morgan 2013; Sudweeks & Rumm, 2012). Regardless of the overall influence of the Internet on doing business, the scope of the paper at hand is limited to review websites and their impact on the travel and hospitality industry.

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The rationale for selecting this topic is its connection to the modern business environment because review websites serve as a common word-of-mouth marketing tool in the chosen sector that has proved to foster changes in consumer behaviour and affect choices (Browning, So & Sparks 2013; Wu 2013). Therefore, those involved in this industry are forced to estimate the role of online websites and implement corresponding marketing strategies aimed at managing these reviews and incorporating them into business practices to keep up with the times (Casaló et al., 2015; Wu 2013; Xie, Zhang & Zhang 2014). It is essential to note that regardless of the popularity of TripAdvisor due to user-generated content (Baka 2016), the paper will not be limited to this online tool only. Instead, it will focus on online reviews as a collective concept.

Therefore, this paper aims at addressing the following research question: To what extent do online reviews in the travel and hospitality sector affect travelling decisions?

To find a relevant answer to the central research question, it is essential to achieve several research objectives:

  1. To investigate the role of review websites in the travel and hospitality sector;
  2. To find out whether review websites are popular;
  3. To determine the relative weight of online reviews on travel decisions and consumer behaviour.

Literature Review

Documentation

The foundation for completing this chapter is conducting a thorough online search of relevant sources. For this purpose, Google Search and Google Scholar were chosen. Different keywords were targeted, including “role of online reviews in the travel industry”, “use of the Internet in hospitality and travel industry”, “relation between online reviews and consumer behaviour”, “credibility of online reviews”, “online consumer reviews and hotel popularity”, etc. Due to the specificities of the research, there were no limitations regarding the place of publishing a source to assess international aspects of the issue under considerations and its perception around the globe. Nevertheless, there were some time limitations because only recent works (published during the last five years) were taken into consideration to guarantee that findings and opinions are relevant and up to date (Cargill & O’Connor 2013).

Moreover, only scholarly sources (books and articles) were included to make the research persuasive. Special attention was paid to the travel and hospitality industry. However, papers on other business sectors were reviewed as well to determine the overall trends in the influence of online reviews on shaping consumers’ purchasing behaviour and decisions. As for the organisation of the literature review section, it will include several subsections focusing on related issues to make it well-constructed and to avoid oversaturation with unnecessary facts and repetitions.

The Influence of Online Reviews on Consumer Behaviour

The issue of online reviews and their influence on consumers’ behaviour is well investigated. Scholarly interest can be explained by the fact that consumers find them interesting and believe in their credibility (Li et al. 2013; Zhang, Zhao, Cheung & Lee 2014). Nevertheless, it is essential to note that regardless of the increased popularity of online reviews, not all scholars believe in the helpfulness of online reviews due to numerous instances of posting fake reviews and hiring specially trained people in order to write reviews for the companies as a form of digital marketing (Park & Nicolau 2015; Xie, Zhang & Zhang 2014; Wu 2013).

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Still, regardless of acknowledging potential untruthfulness of posts shared on review websites, consumers tend to read them before making some vital decisions, especially regarding spending money, and the popularity of online reviews is constantly increasing (Darban & Li 2013; Ye, Li & Law 2012). In addition, there are several dimensions of the influence of online reviews on consumers (Filieri and McLeay 2013). Nevertheless, in most cases, they shape consumer behaviours, decreasing demand for some products and places and increasing for others (Ketelaar, Willemsen, Sleven & Kerkhor 2015; Schepers 2013). Here, it is also essential to point to the fact that not all reviews are similarly popular because only detailed ones, with pictures and ratings, are believed to be the most useful (Ashby, Walashek, & Glöckner 2015; Ban 2015; Mo, Li & Fan 2015).

Relation Between Online Reviews and Purchasing Decisions

Except for affecting consumers’ behaviours, online reviews are associated with changes in purchasing decisions (Holleschovsky 2015; Katawetawaraks & Wang 2012). Regardless of the relative complexity of predicting the influence of online reviews on purchasing outcomes, numerous scholars do believe in the existence of a strong connection between the two (Browning, So & Sparks 2013; Cui, Lui & Guo 2012; Hu, Koh & Reddy 2014; Park & Nicolau 2015; Zhang, Ji, Wang & Chen 2016). It can be explained by the psychological specificities of people, especially those conducting at least minimal research before making purchases (Kwon, Bae & Phelan 2012). In this case, it is essential to note that, in most instances, negative reviews are more powerful compared to positive ones because of the commonality of negativity bias in the society (Cui, Lui & Guo 2012; Park & Nicolau 2015; Wu 2013). Still, it is critical to keep in mind that this trend is only when making expensive purchases or, for example, planning to visit a luxurious hotel (Lawlor, Gorham & O’Connor 2015).

On the other hand, when reading a negative review of a cheap hotel or product, people are unlikely to be affected by it because this review corresponds with their expectations (Mauri & Minazzi 2015; Wu 2013). On the other hand, it is complicated to foresee the impact of positive online reviews on purchasing behaviours because consumers either will not believe in its trustworthiness or continue searching for a negative one (Casaló et al. 2015; Zarco 2015). At the same time, moderate reviews are of lesser interest to consumers (Ioanas & Stoica 2014; Park & Nicolau 2015).

Also, when it comes to estimating the influence of online reviews on purchasing behaviours, it is essential to mention that consumers tend to believe what is perceived as expert opinions instead of posts shared by ordinary consumers (Li et al. 2013; Bianchi & Andrews 2012). This is connected to the belief that expert opinions are more helpful and specialised and thus more trustworthy (Utz, Kerkhof & Bos 2012; Vimaladevi & Dhanabhakaym 2012). In some cases, expert opinions posted online are even more influential than the reputation of a company offering particular products or hotel offering services (Anderson & Lawrence 2014; Cherdchamadol & Sriboonjit 2013; Sparks, Perkins & Buckley 2013). Moreover, purchasing behaviour is directly influenced by arguments and details provided in online reviews as well as the interest in a particular product, service, or destination (Ayeh, Leung, Au & Law 2012; Zhu & Zhang 2012). In other words, just stating an opinion is not justifiable if it is not supported with powerful arguments or other similar reviews (Xie, Chen & Wu 2015; Zhang et al. 2014).

The Credibility of Online Reviews

The issue of online reviews’ credibility is closely connected to their influence on consumer behaviour. It can be explained by the fact that, in some cases, reviews are shared to manipulate readers and motivate them to make wrong decisions (Mayzlin, Dover & Chevalier 2014). This belief is closely connected to the existence of negative bias. However, it is deeper and more complicated because it is related not to psychological specificities of readers but rather the desire of companies and facilities to improve their reputation or destroy their competitors (Park & Nicolau 2013; Mayzlin, Dover & Chevalier 2014). From this perspective, companies and institutions choose to hire specially trained managers who post fake reviews to manipulate consumers regardless of potential risks related to consumer trust in case the truth is found out (Ayeh, Au & Law 2013; Schuckert, Liu & Law 2015). The issue of manipulation can also be connected to the existence of hotel networks because chain hotels are usually promoted just because of their operation under the name of a famous network (Banerjee & Chua 2016).

The Influence of Online Reviews on Hospitality and Travel Industry

Nowadays, there are numerous popular review websites. They vary in review options. However, all of them operate to achieve the same objective: help tourists choose the perfect destination for a journey and remain satisfied with their choice (Milano, Baggio & Piatelli 2012). In this case, it is imperative to note that there is also an offline population coming to hotels—those who never read online reviews (Xie, Chen & Wu 2015). It is vital for the understanding of asymmetry of positive and negative reviews because these people do not share opinions online (Fong, Lei & Law 2016). At the same time, it is critical to keep in mind that fake reviews on hospitality and journey review websites are also a common challenge affecting consumer choices (Sigala 2015).

Except for the influence on consumer expectations and intentions, online reviews have a positive impact on hospitality and journey industries (Rathonyi 2013). It can be explained by the fact that reviews commonly reveal consumers’ expectations so that both travelling agencies and hotels know how to satisfy them (Lam, Tan & Oh 2014; Phillips, Barnes, Zigan & Schegg 2017). This can be achieved by implementing specific management strategies aimed at identifying the latest reviews and determining the ways to incorporate them in hotels’ activities with the focus on performance improvement (Proserpio & Zervas 2016; Tuominen 2012). At the same time, online reviews have a direct influence on travel agencies as people commonly comment on their performance and quality of services (Inversini & Masiero 2014; Yazdanifard & Yee 2014). The same is true about transporting companies (Zhao, Wang, Guo & Law 2015). In this way, all institutions operating in the travel and hospitality industry might benefit from reading reviews and using them for promotion (Khoo-Latimore & Ekiz 2014; Moisescu & Gica 2015; Yang, Jou & Cheng 2012).

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Nevertheless, it is critical to keep in mind that the influence of online reviews on consumers and their behaviour depends on a variety of factors. For instance, age and gender of visitors affect the perception of both reviews and services provided by transporting companies and hotels (Ban, Ancusa, Bogdan & Tara 2015; Pavlina 2013; Rajesh 2013). More than that, travelling experiences are related to satisfaction with the provided services because more experienced travellers may compare their journey with previous ones; thus the influence of the reviews and the reviews themselves, in case of posting them, will differ (Li & Lin 2013; Shahrivar 2012; Suanmali 2014). Finally, the length of stay also matters because the shorter the stay, the harder it is to identify all the disadvantages of a hospitality facility, therefore estimating the quality of services (Ban, Costangioara & Nedelea 2016; Jones & Chen 2012). In this case, the credibility and trustworthiness of reviews are also affected, and that in turn, leads to further changes in consumer behaviour among other people (Mills & Law 2013).

Methodology and Data Collection Process

Research Approach and Design

To answer a research question, a mixed research design is selected. The rationale for making this choice is the fact that this method is beneficial for estimating the influence of online reviews on consumer behaviour to the maximum possible extent as it incorporates the elements of both qualitative and quantitative designs (Caruth 2013; Frels & Onwuegbuzie 2013; Lund 2012). Therefore, there are two interconnected parts combined to make appropriate conclusions. The first part—qualitative—is based on a thorough literature review to identify common trends in the hospitality and travel industry and the overall influence of online reviews on making decisions.

The second part—quantitative—is based on survey results. Here, it is essential to mention that no cause-and-effect relationships (a common element of quantitative research) will be tested (Caruth, 2013; Frels & Onwuegbuzie, 2013). Instead, the idea is to identify the percentages of tourists making their decisions based on online reviews. From this perspective, the major objective of the research is to compare literature review findings with the survey findings. This choice is appropriate because mixed research design increases research capacity and makes it easier to answer the research question in case of limited resources and skills in using statistical tools for analysing collected data (Bazeley 2015; Cameron & Azorin 2012).

Data Collection

As mentioned above, there are two parts of the paper. As for the literature review (qualitative part), the search process is described in the documentation section above. Here, it is still imperative to note that this part is the source of secondary data—findings of other researchers (Flick 2014; Roller & Lavrakas 2015).

Speaking of the quantitative part, the foundation of data collection is conducting an online survey. It is the source of primary data—that collected directly from respondents (Grbich 2013). The rationale for choosing this data collection tool is the fact that it does not require the organisation of real-life conversations that are impossible because of the limited resources of the research (Rhodes 2013). Moreover, it is easier to find respondents and cover people from different regions with different experiences (i.e., diversified population) (Sue & Ritter 2012). Finally, online surveys are flexible and easier to work with because all collected data is already digital so that the risks of errors during processing the results are lower (Lilien & Grewal 2012). All questions included in the survey are close-ended (i.e., can be answered in one word) (Leung 2001). The idea is to make the questionnaire easy to complete and to understand the overall trends in the perception of the issue under consideration (Bryman & Bell 2015; Eriksson & Kovalainen 2015).

Moreover, open-ended questions that commonly help to gain a better understanding of the phenomenon are avoided because they are irrelevant when choosing a mixed research design (Bryman & Bell 2015; Eriksson & Kovalainen 2015). The specificities of the questionnaire are its anonymity, using simple language, and being designed in a way that requires little time to fill it. Also, all questions are arranged in a way that the most important ones are mentioned first so that they are more likely answered (Weathington, Cunningham & Pittenger 2012). The developed questionnaire can be found in Appendix 1.

At the same time, it is imperative to focus on the sample. Patton (2014) states that a sample is a group of people chosen to participate in research. To select them, several sampling techniques are used. However, because this survey is an online one and the participation is voluntary, it is evident that the sampling technique is random; no special criteria are used for choosing respondents (Miles, Huberman & Saldaña 2014). The sample size is 15 people.

Data Analysis

Once enough filled questionnaires are collected, the data analysis process will begin. The idea is to make sense of the collected information and answer the research question (Roller & Lavrakas 2015). The first step is the creation of a table combining all answers to survey questions. This stage is connected to coding answers and organising them (Shaw & Holland, 2014). Once responses are coded, relevant graphs and charts will be created in order to visually represent data (Evergreen 2013). Microsoft Excel is a tool for data analysis due to its feasibility. Drawing conclusions and making recommendations is the final step of the research. Also, it is essential to mention that all data will be presented both graphically and verbally for making the conclusions persuasive (Saunders, Lewis & Thornhill 2015).

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Reliability and Validity

Due to conducting the survey online and voluntary participation, the threats to data reliability are significant. This means that it is impossible to guarantee that the respondents provided truthful and accurate answers regardless of the filled-in consent form (Patton 2014). Moreover, because the sample size is small, there is a validity risk connected to excessive or deficient diversification of respondents (Flick 2014). In order to overcome these challenges, it is critical to make sure that only completely filled in questionnaires are analysed. Moreover, conclusions should be made based on the literature review section for comparing findings (Johnson & Christensen 2014; Harper & Cole 2012). This is a deductive approach.

Limitations

Except for reliability and validity issues, there are as well other potential limitations. First and foremost, the sample size is small. Even though it is appropriate given the limited resources and time constraints, collected data cannot be used for generalising findings (Emmel 2013; Yin 2013). Moreover, there is a potential risk of little interest in filling the questionnaire because no respondents are directly invited, and the participation is voluntary (Saunders, Lewis & Thornhill 2015).

Ethical Considerations

Regardless of the anonymity of the questionnaire and voluntariness of participation, there are still some ethical considerations to keep in mind. First and foremost, it is essential to provide potential respondents with all necessary information regarding the research, which is mentioned in the participant information sheet. Also, it is still critical to obtain participants’ consent before collecting data. More than that, guaranteeing that no sensitive topics are brought up in the questions, as well as using obtained results with other than the stated studies, is paramount (Hennick, Hutter, & Balley, 2012; Miller, Mauthner, Birch, & Jessop, 2012; Milton, 2013). Finally, it is imperative to cite all the borrowed ideas in order to avoid plagiarism, especially in the literature review section.

Presentation of Data

The paper at hand focused on collecting data regardless of the perception of online reviews and their influence on the decisions and behaviour of consumers. Special attention was paid to activity and logging in as well as the impact of both negative and positive online reviews. In order to collect the needed volume of data, 67 surveys were collected. However, among them, only 50 questionnaires were completely filled in. Therefore, the sample size was 50. The collected information is presented in the following subsections with a specific focus on different aspects of the research.

Age of Respondents

The study turned out to be popular among different age groups (see figure 1): under 20 years (11 respondents), between 21 to 30 (16 respondents), 31 to 40 (10 respondents), 41 to 50 (6 respondents), 51 to 60 (5 respondents), and over 60 years old (2 respondents).

Age of respondents.
Figure 1. Age of respondents.

Gender of Respondents

The survey involved both male and female respondents. In particular, 22 male and 28 female respondents showed an interest in completing the questionnaire. Detailed information is shown in Figure 2 below.

 Gender of respondents.
Figure 2. Gender of respondents.

Most respondents reported reading reviews, although not every time. That said, 18 people stated that they always read online reviews before making significant purchasing decisions, 15 respondents never read online reviews, and 17 respondents read them but not before each purchase or journey (see Figure 3 for details).

Reading Online Reviews

Reading reviews
Figure 3. Reading reviews.

Among those having filled the questionnaires, ten men and eight women stated that they read online reviews all the time, six men and nine women never read them, and six men and 11 women did not do it every time (see Figure 4 for details).

 Reading reviews (gender distribution).
Figure 4. Reading reviews (gender distribution).

As for age groups, younger respondents turned out to be more active. Six aged between 21 and 30 and 6 between 31 and 40 always read online reviews. On the other hand, six respondents younger than 20 years old never read them. It should be noted that preferences change over time as older respondents stated that they either read online reviews more rarely or never do it, while younger people were more active. See details in Figure 5 below.

Reading reviews (age distribution).
Figure 5. Reading reviews (age distribution).

Logging In to Online Review Websites

Although reading online reviews is a popular activity, most respondents (30 out of 50) stated that they were not registered users of review websites (see Figure 6).

Registered respondents.
Figure 6. Registered respondents.

Still, among those registered, there were 9 (out of 22) male respondents and 11 (out of 28) female participants. It means that regardless of gender, people do not prefer logging into online review websites (see Figure 7 below).

Registered respondents.
Figure 7. Registered respondents (gender distribution).

As for age groups, logging in is more popular among younger Internet users (aged under 20 and up to 40) even though the majority of all respondents are not registered readers (see Figure 8 for detailed information).

Registered respondents (age distribution).
Figure 8. Registered respondents (age distribution).

Posting Online Reviews

Speaking of posting online reviews, this aspect is identical with logging in activities because most review websites require logging in for similar activities. That is why most respondents (30 out of 50) do not post them (see Figure 9). As for age and gender distribution, it is as identical to the previously mentioned data (see Figures 10 and 11).

 Posting online reviews.
Figure 9. Posting online reviews.
Posting online reviews (gender distribution).
Figure 10. Posting online reviews (gender distribution).
Posting online reviews (age distribution).
Figure 11. Posting online reviews (age distribution).

Among 50 respondents, the majority (19 participants) stated that positive reviews have a direct influence on their decisions when it comes to choosing products or hotels. Fourteen respondents marked that they are partially influenced by positive reviews. Finally, 17 participants do not feel the impact of positive reviews (see Figure 12).

Influence of Positive Reviews on Consumer Behaviour

Influence of positive reviews.
Figure 12. Influence of positive reviews.

During analysing survey data, a peculiar trend was revealed: Women are more influenced by positive online reviews (14 “yes”, 7 “no”, and 7 “partly”) compared to men (5 “yes”, 10 “no”, and 7 “partly”). Detailed information is provided in Figure 13 below.

Influence of positive reviews (gender distribution).
Figure 13. Influence of positive reviews (gender distribution).

As for the gender distribution of respondents, those aged from 21 to 40 (13 in general) stated that positive reviews affect their behaviour. On the other hand, respondents younger than 20 and those over 60 years old never felt influenced by positive reviews (see Figure 14 for details).

Influence of positive reviews (age distribution).

Positive Reviews and Purchasing Behaviour

At the same time, positive online reviews are directly connected to changes in purchasing behaviour. This means that people are eager to spend more after reading a positive review. Among 50 respondents, 22 participants stated that it was true and 16 people claimed that is was partly true (see Figure 15).

 Influence of positive reviews on purchasing behaviour.
Figure 15. Influence of positive reviews on purchasing behaviour.

As for gender distribution, men were less affected by positive reviews compared to women, just like in the previous aspect (see detailed information in Figure 16 provided below).

In case of age distribution, the trend is a bit different compared to the previous aspect of the research as people younger than 20 years recognised that positive reviews affect their purchasing behaviour although they stated that their choices were not influenced by the reviews earlier in the survey. Detailed information regarding other age groups is provided in Figure 17 below.

Influence of positive reviews on purchasing behaviour (gender distribution).
Figure 16. Influence of positive reviews on purchasing behaviour (gender distribution).
Influence of positive reviews on purchasing behaviour (age distribution).
Figure 17. Influence of positive reviews on purchasing behaviour (age distribution).

Impact of Negative Reviews on Consumers

The case of negative online reviews is closely connected to that of positive as most respondents (30 out of 50) stated that negative reviews do affect their behaviour (17 “yes” and 13 “no”). Detailed information is provided in Figure 18 below.

Influence of negative reviews.
Figure 18. Influence of negative reviews.

As for gender distribution, women again are more affected by negative reviews compared to men (see Figure 19 below for details).

 Influence of negative reviews (gender distribution).
Figure 19. Influence of negative reviews (gender distribution).

Speaking of age distribution of respondents, younger participants were more affected by negative online reviews compared to older ones. It is also similar to the instance of positive online reviews in the case of gender distribution and the overall trend (see figure 20 for detailed information).

Influence of negative reviews (age distribution).
Figure 20. Influence of negative reviews (age distribution).

Reliability of Online Reviews

Among 50 respondents, 32 believed that online reviews are a reliable source of information regarding a product, service, or destination (15 “yes” and 17 “partly”). Detailed information is provided in Figure 21 below.

As for gender distribution, female respondents were more trustful compared to men, as most of them believed in the reliability of the online reviews. Still, it is essential to note that half of the male respondents (11 out of 22) found reviews reliable (4 “yes” and 7 “partly”). See Figure 22 below for details.

Believing in the reliability of reviews.
Figure 21. Believing in the reliability of reviews.
Believing in the reliability of reviews (gender distribution).
Figure 22. Believing in the reliability of reviews (gender distribution).

As for age distribution, younger respondents (up to 40 years old) found online reviews reliable, while those over 40 mainly did not believe in their reliability (see Figure 23).

Believing in the reliability of reviews (age distribution).
Figure 23. Believing in the reliability of reviews (age distribution).

Value of Online Reviews

Regardless of the reliability issue, most of the respondents believe that online reviews are a valuable source of information (20 “yes” and 20 “partly”). See details below (Figure 24).

Believing in the value of reviews.
Figure 24. Believing in the value of reviews.

As for gender distribution, both men and women find online reviews valuable without significant differences in opinions (see Figure 25 below).

Believing in the value of reviews (gender distribution).
Figure 25. Believing in the value of reviews (gender distribution).

Speaking of age distribution, most respondents also believe in the value of reviews (see Figure 26 for details).

Believing in the value of reviews (age distribution).
Figure 26. Believing in the value of reviews (age distribution).

Online Reviews and Booking Decisions

According to the findings of the conducted survey, online reviews do affect booking decisions. This is true for choosing hotels and transport options as well as travel agencies. See detailed information on Figure 27 below.

Reviews and booking.
Figure 27. Reviews and booking.

Female respondents were more affected by online reviews when it came to booking decisions (just like in the case of other aspects of the research). See details in Figure 28 below.

 Reviews and booking (gender distribution).
Figure 28. Reviews and booking (gender distribution).
Reviews and booking (age distribution).
Figure 29. Reviews and booking (age distribution).

As for age distribution, younger respondents again were more affected by online reviews in booking choices compared to elder participants (Figure 29).

Online Reviews and the Choice of Online Booking Services

Finally, online reviews have a direct influence on online booking choices. Among 50 respondents, 38 participants stated it was true (19 “yes” and 19 “partly”). See figure 30.

Reviews and online booking.
Figure 30. Reviews and online booking.

As for gender distribution, women again are more influenced compared to men (Figure 31 below). The trend is also positive in the case of all age groups (see Figure 32).

Reviews and online booking (gender distribution).
Figure 31. Reviews and online booking (gender distribution).
Reviews and online booking (age distribution).
Figure 32. Reviews and online booking (age distribution).

Discussion and Evaluation

The conducted survey helped to support the primary statements made in the literature review section. In particular, it was proved that the issue of online reviews is an ambiguous one because the perception of reviews depends on age and gender (Ban, Ancusa, Bogdan & Tara 2015; Pavlina 2013; Rajesh 2013). Moreover, reviews are a common tool for manipulation because it was shown that both negative and positive online reviews are associated with the changes in choices and purchasing behaviour (Ayeh, Au & Law 2013; Besley 2015; Banerjee & Chua 2016; Morgan 2013; Schuckert, Liu & Law 2015; Sudweeks & Rumm, 2012). Finally, it was concluded that the issue of relevance the and accuracy of online reviews is critical because most respondents question the credibility of published posts (Li et al. 2013; Park & Nicolau 2013; Zhang, Zhao, Cheung & Lee 2014).

In this way, the conducted research is of significant importance because it helps to obtain a better understanding of the perception of online reviews. However, there are still some limitations because the data was collected from a small sample of respondents; therefore, it cannot be generalised.

Conclusions and Recommendations

Regardless of a significant limitation, the conducted research can be used as a tool for improving the performance of travel agencies, transportation companies, and hotels. It can be achieved by implementing relevant management strategies aimed at studying reviews on a timely basis and embodying the changes mentioned in them (avoiding delays and low-quality services). More than that, it is advisable to respond to negative reviews identified on the most popular review websites explaining the potential causes of low-quality services and consumer dissatisfaction in order to avoid similar incidents in the future and increasing consumer satisfaction, thus making them loyal. Finally, positive online reviews can be used as a framework for turning the strengths into the further improvement of performance and productivity.

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