Exploring the Perceived online Review Credibility and Management Response Influence on Purchase Intention

Document Type : Research Paper


1 Associate Prof., Department of Business and Management, Northumbria University, Northumbria, England.

2 MSc., Department of Business and Management, Northumbria University, Northumbria, England.



Online reviews play a crucial role in the consumer decision-making process in the glamping industry. Some reviews are misleading; therefore, users need to identify credible reviews to form objective opinions. This study examined dimensions of perceived review credibility and its influence on purchase intention within the glamping business. Online surveys were conducted with respondents with relevant travel experiences to examine the key credibility factors. Findings identified that review length, amount of detail, writing style, and travelers’ images; as well as mixed, moderate, and two-sided reviews influence perceived review credibility. It was also found that perceived review credibility influences purchase intention; that management response impacts perceived company credibility and purchase intention; and that personalized management response is valuable for the perceived credibility and purchase intention. A revised conceptual framework was developed to demonstrate the sources of perceived credible online reviews and the role of management responses in the reviews. In addition to the theoretical contribution, this study can have practical marketing implications for businesses when creating online promotional material for their products and engaging with customers


Main Subjects


Glamping combines natural scenery with high-quality accommodations and indoor luxuries (Lee et al., 2019). Information learned from online reviews enables users to understand prior guests’ experiences which is essential for a new industry such as glamping. User-generated online reviews are more credible and persuasive than marketing sources (Plotinka & Munzel, 2016; Reimer & Benkenstein, 2016). Several factors can influence consumers’ perceived review credibility including source trustworthiness, message trustworthiness, review valence, and medium type (Filieri, 2016).

Business responses to online reviews can further influence consumer brand confidence (Jakic et al., 2017). Management response to reviews is not only beneficial to the customer who wrote the review but also to prospective customers as they can see the interaction between customer and hotel management (Xie et al., 2014). This can have an impact on consumers’ perception of company trust (Sparks et al., 2016; Zinko et al., 2021). There is no current literature exploring perceived review credibility and its impact on purchase intention in the glamping industry. Despite its growing popularity, glamping is still under-researched. This study aimed to identify the dimensions that lead to perceived review credibility and explore how perceived review credibility influences purchase intention. It also examined how management response influences perceived company credibility and purchase intention in the glamping industry.

Literature Review 

Due to its intangible nature, online reviews are used by prospective travelers to gather ideas about glamping accommodations. Guests are more likely to share their experiences through online reviews when they are satisfied with the service they received (Li & Ryan, 2020). Online reviews contain a large amount of experience-based information, which can be used to make purchase decisions (Yagci & Das, 2018). Online reviews can influence purchase intention, particularly in the hotel industry, where online reviews can have a significant impact on behavioral intentions and decision-making processes (Boo & Busser, 2018; Tran, 2020).

Theoretical Framework

Filieri’s (2016) framework was used in this study to understand the impact of eWOM trustworthiness on the purchase intentions of consumers in the glamping industry. This model identifies source trustworthiness, consumer involvement, message trustworthiness, review valence, pattern in reviews, and medium type as factors that influence perceived review trustworthiness, which ultimately leads to persuasion. These dimensions are explored further in the following sections.

Message Trustworthiness

Consumers base their judgments of trustworthiness on different cognitive heuristics which fall into two categories: source cues and content cues (Machackova & Smahel, 2018). The present study seeks to understand the latter due to most of the recent research to understand source trustworthiness not only within the online review context (Banjeree et al., 2017; Lin & Xu, 2017; Filieri, 2016; Chakraborty, 2019b; Filieri et al., 2018a) but also with other aspects of eWOM, such as social media influencers (Weismueller et al., 2020; Djafarova & Rushworth, 2017).

Some 37% of online review users pay attention to the length and detail of a review (Tankovska, 2021a). Longer reviews tend to contain more product details which can be perceived as more helpful and indicate that consumers put more time into writing the review (Mudambi & Schuff, 2010; Liu & Park, 2015). Often consumer complaints include a combination of negative, neutral, and even positive reviews, which can make a review longer (Bradley et al., 2015). Consequently, consumers with negative experiences tend to write more detailed reviews to make their reviews more persuasive whilst seeking support from the online travel community (Salehan & Kim, 2016). Very short reviews are perceived by the receiver as untrustworthy (Filieri, 2016). Consumers write more words and details with negative aspects in comparison to positive aspects (Xu & Li, 2016). In comparison to reviewer rating and reviewer helpful attributes, review length does not have a noticeable impact on review helpfulness (Yang et al., 2017). Thus, the following hypotheses were formed:

H1a: Review length influences perceived review credibility.

H1b: Review detail influences perceived review credibility.

The writing style can influence the perceived trustworthiness of online reviews. Fake reviews generally involve the use of strong emotional expressions (Filieri, 2016). Factual reviews can lead to higher purchase intention. In addition to emotional vs. factual details, writing style can also harm perceived review trustworthiness. Some marketers take advantage of this and pretend to be a consumer by writing fake reviews (Goh et al., 2013). 

Well-written reviews are perceived as more credible in comparison to reviews that are hard to understand (Fang et al., 2016). Accordingly, the following hypothesis is proposed:

H2: Writing style influences perceived review credibility.


Consumer images of the purchased product/service are extremely useful in determining the trustworthiness of the review as well as the reviewer (Filieri, 2016). Prior research demonstrated the positive impact of visual information alongside textual information on consumer attitude as this can improve information quality (Lee et al., 2010). Visual information is only beneficial for experiential products when a different variety is provided (Kim et al., 2021). If a hotel provides multiple pictures of one room from different angles rather than several images of different rooms, then this information is not valuable (Kim et al., 2021). The following hypothesis is proposed:

H3: Consumer pictures influence perceived review credibility.

Review Valence

The valence of online reviews has a significant influence on consumers’ purchase intentions (Tsao et al., 2015; Tata, 2020). Positive online reviews have a significant impact on purchase intention (Ghasemaghaei et al., 2018). Hotels that have a vast number of positive reviews are more likely to be remarked for higher levels of performance and in turn have higher occupancy rates in comparison to competitors with less positive online reviews (Phillips et al., 2017).

The effect of positive online reviews can be determined by the amount of detail in the review (Zhong et al., 2014). Positive reviews can be perceived as less trustworthy as some hotels tend to have fake positive reviews and in turn, reviews are perceived as an extension of marketing activities (El-Said, 2020). Reviews describing negative aspects of a product or service are more credible as it is unlikely that it has been created by the seller (Folse et al., 2016; Chakraborty, 2019a). When there is a combination of positive and negative reviews, this is perceived as more credible than if there are only positive reviews (Purnawirawan et al., 2015). Only positive reviews influence review credibility in comparison to a mix of positive and negative (Leung, 2020). Negative online reviews have a stronger influence on purchase intentions than positive reviews (Zhao et al., 2015). Once consumers read negative reviews, their attitude toward the hotel significantly lowers (Casado-Diaz et al., 2020). The following hypotheses are proposed:

H4a: Positive reviews negatively influence perceived review credibility.

H4b: Negative reviews positively influence perceived review credibility.

Extreme ratings refer to a review that contains particularly a negative or positive evaluation of products or services (Park & Nicolau, 2015). A low amount of extremely negative ratings stands out and attracts the attention of consumers who seek extreme reviews (Wu, 2013; Filieri et al., 2019). Existing research concludes that extreme ratings are the most helpful (Fang et al., 2016; Liu & Park, 2015; Park & Nicolau, 2015; Filieri et al., 2020). However, other research suggests that extreme reviews are questionable (Mudambi & Schuff, 2010). Filieri (2016) found that extreme reviews are often perceived as untrustworthy by consumers because they are likely to have been manipulated by the owner, competitors, or overly critical people. As a result, consumers seek to understand why the reviewer has extreme satisfaction/dissatisfaction by looking at the content in the review. Moreover, extremely positive reviews are more likely to be perceived as untrustworthy in comparison to extremely negative reviews (Filieri, 2016). Extreme ratings are the most helpful in hotels which are regarded as a higher category due to consumers forming different expectations depending on the hotel category (Banjeree & Chua, 2019; Filieri et al., 2020). Therefore, the following hypothesis was formed:

H5: Extreme reviews positively influence perceived review credibility.

This study is mixed regarding review sidedness and its influence on review trustworthiness. Moderate reviews that include two-sided information are perceived as highly trustworthy because it provides a balanced argument in comparison to extreme reviews (Filieri, 2016). Two-sided reviews are more persuasive and unbiased in comparison to one-sided reviews because they portray the pros and cons of a product (Cheung et al., 2012). Although two-sided reviews can influence credibility, it has also been found to reduce the likelihood of consumer purchase intention, due to the negative aspects of the two-sided review encouraging the consumer to look elsewhere (Pizzuti et al., 2016). Two-sided reviews have no significant impact on helpfulness and persuasiveness (Kim et al., 2017). The present study proposes:

H6: Two-sided reviews positively influence perceived review credibility.

Pattern in Reviews – Review Similarity and Consistency

Patterns in reviews can be perceived as suspicious. A company that has many complimentary reviews by one-time posters can be questionable. Often these reviews are posted within a short time, which intends to mislead the consumers (Filieri, 2016; Xie et al., 2012). Similar reviews are more likely to be fake in comparison to genuine reviews (Day et al., 2017). Previous research suggests that false reviewers write a few fake reviews and can manipulate the readers (Zhang et al., 2016). As a result, the fake reviewers use similar language to genuine reviews, which can make it even more difficult to detect review trustworthiness (Mukherjee et al., 2013; Chen & Chen, 2015). When there is a consensus amongst reviewers about a product, it can improve perceived trustworthiness. When there are mixed and contradictory reviews this can lead to poor information processing and uncertainty (Penz & Hogg, 2011; Akhtar et al., 2020). Therefore, the following hypothesis was formed:

H7: The pattern in reviews influences perceived review credibility.

Medium Type

There are three major types of online review platforms: direct-sale, third-party, and social media. The direct-sale platform relates to the company’s website and serves the role of an online store (Wang et al., 2015). Consumers use third-party platforms to compare hotels and book rooms (Toh et al., 2011). Social media is used by consumers to socialize, share their experiences, and gain information from their peers, such as reviews (Ayeh et al., 2013; Chang et al., 2019; Kim & Lee, 2019).

Reviews available on companies’ websites are often positive, which can influence their trustworthiness (Filieri, 2016). Social media is a more independent forum compared to direct-sales and third-party. This encourages consumers to fully express themselves and reveal their emotions, resulting in a narrow focus and thus low diversity (Zhang et al., 2017; Xu & Lee, 2020). Consumers perceive reviews through social media as trustworthy as often these reviews come from familiar users such as family members or friends. The following hypothesis was accordingly proposed:

H8: Medium type influences perceived review credibility.

Message Credibility and Purchase Intention

Previous research has identified online review credibility as a crucial factor in influencing purchase intention (Chih et al., 2013; Fan & Miao, 2012; Thomas et al., 2019; Arora & Mail, 2018). Arora and Mail (2018) found that review credibility has an impact on the purchase intention of valuable products. Consequently, it was proposed: 

H9: Perceived review credibility influences purchase intention.

Management Response

Companies can influence consumer brand confidence through their response to comments on social media (Jakic et al., 2017). The mere appearance of management responses can enhance a consumer’s perception and trust in the hotel (Sparks et al., 2016). Effective management response can not only appease dissatisfied customers but also reinforce the compliments in positive reviews (Xie et al., 2017; Levy et al., 2013).

Hotel management needs to understand how to respond to customers’ online reviews so they can contribute to the company’s objectives (Moreno & Locket, 2016). Soler and Gemar (2017) argue that management response to guest reviews can be a good indicator of customer-based brand equity. The value of hotel reviews can increase due to managerial responses (Kwok & Xie, 2016). When management responds to reviews this can help potential consumers to perceive the company as trustworthy and concerned about the consumer (Sparks et al., 2016). Moreover, if the brand is perceived as wanting to develop a good customer relationship, this can increase positive emotions and trust (Casidy et al., 2018). The frequency of management response to reviews can increase ratings (Kwok & Xie, 2016; Li et al., 2017).

As a result, the following hypotheses were proposed:

H10a: Management response influences perceived company credibility.

H10b: Management response to reviews influences purchase intention.

Derived from the available literature, the following conceptual framework was formed to foresee how perceived review credibility and management response influence purchase.

Figure 1. Conceptual Framework


This study adopted a quantitative approach to the research data collection and analysis of the findings. A questionnaire was developed to obtain data with questions relating directly to the hypotheses. Respondents were directly asked if perceived credible reviews influenced their decision to book a trip with a glamping company. This enabled the researchers to gain data that is reflective of the respondents’ opinions.

In conformance with the literature, the questionnaire was comprised of 8 sections. The first section of the survey was designed to obtain respondents’ socio-demographic data including gender, age, and education. The second section was designed to understand the respondents’ experience with glamping. If they had not been on a glamping trip, they were asked to state which type of glamping experience they would consider. The third section was designed to understand respondents’ experience with online reviews. The fourth section included questions relating to message credibility such as review length, valence, etc. Section five was designed to understand review credibility on different platforms. The sixth section included questions relating to suspicious reviews. Section seven asked respondents directly whether perceived credible reviews influence purchase intention. The final section discussed management responses to online reviews.

Part of the questionnaire included multiple-choice questions and Likert scales, which are important to generalize findings (Bell et al., 2018). Open-ended questions were asked to gain a more enriched, in-depth picture of respondents’ opinions on online review credibility and management response. The survey was designed, distributed, and analyzed using JISC online surveys with the link posted on glamping Facebook groups. Due to the research focusing on online reviews, respondents needed to have experience using these forums. The respondents were approached through glamping Facebook groups, as it is more likely that they are interested in the study and have knowledge and experience in glamping tourism. Thus, a purposive sample was used to select the respondents for this study.

Results and Discussion

Responses consisted of 152 participants. 78% were female, 21.1% were male and 0.7% selected others. In terms of age distribution, respondents aged between 18-24 and 25-34. Regarding time spent reading online reviews, 45.4% spent 10-30 minutes, 26.3% 10 minutes or less, 17.8% 30-60 minutes, and 10.5% more than 60.

Message Credibility

H1a: Respondents were asked whether they believed the length of a review influences perceived review credibility. Of them, 12.5% rated ‘strongly agree’, 34.9% ‘agree’, and 32.9% ‘neither agree nor disagree’. Due to a high number of responses stating: ‘neither agree nor disagree’, a further analysis was undertaken through a Pearson correlation comparing review length and whether consumers trust reviews in general. This is due to trust playing an essential role in perceived credibility. The results showed a weak positive correlation of 0.270. Thus, H1a can be accepted.

Previous studies say that longer reviews are more helpful than shorter reviews (Liu & Park, 2015, Mudambi & Schuff, 2010). Brief reviews are perceived as untrustworthy (Filieri, 2016). While Yang et al. (2017) found review length to have no significant impact on review helpfulness. Filieri (2016) concluded that not all long reviews are trustworthy. This could therefore explain why some respondents selected ‘neither agree nor disagree’. It is important to understand how review detail influences perceived review credibility.

H1b: Respondents were asked whether the detail in a review influences perceived credibility. 88.1% of respondents agreed with the statement. The results of the Pearson correlation showed a moderate positive relationship of r = 0.346. To gain a more enriched insight into the population, respondents were asked what type of detail they expect to see in a credible review. The responses were analyzed and organized into categories demonstrated in Table 1. Most respondents identified that they expect to see detail regarding facilities, location, the reviewers’ experience, and how welcoming the staff is. Others mentioned that detail about the reviewer was important such as reason and date of stay.

Table 1. The type of detail respondents expect to see in a review.

Review Detail




Cleanliness, detail of facilities, details about food, beds, quality/standard of accommodation, parking, how well maintained, activities available, style, comfort, what is offered, WIFI, hot-tub, fire-pit, log burner


Things to do in the area, local amenities, environment, why it is a good location/view, how to get there if it is easy to find, nearby shops


What was good and why, a full breakdown of the experience not just negatives, a mix of good and bad, the property as described, images to prove the experience, whether they will return/recommend, how they slept, atmosphere, whether it lived up to their expectations, examples, explanation of check-in/out procedures, booking process, what time of year they went


Welcoming, if there were problems how were they solved, support, helpful, friendly, went out of their way to make their experience memorable, customer service


Worth the money, price, honest pricing


Real name, photo, the reason for stay, date of stay, genuine opinions, advice, would they go again, critical outlook, not like an automated statement


H2: Respondents were asked several questions regarding their writing styles. The first question asked whether they believed factual reviews influence perceived credibility. The results showed an almost unanimous decision with a combined 94.1% stating either ‘strongly agree’ or ‘agree’. Barbu et al. (2019) also suggest that factual reviews are more trustworthy and can lead to higher purchase intention.

Respondents were then asked whether they believe reviews written with emotional expressions were credible. Findings show that 14% selected ‘strongly agree’, 40.1% ‘agree’, and 29.6% ‘neither agree nor disagree’. These findings contradict prior research. When reviews are written with emotional expressions, they are likely to be fake (Carbonell et al., 2019; Filieri, 2016). There are a few reasons that could explain why the present study’s findings differ from previous research: the survey did not include a definition of emotional expressions which may have led to confusion amongst participants; emotional expressions can play an important role in influencing potential consumers; female readers are more likely to be influenced by emotional expressions in comparison to males (Chen & Farn, 2020), where 78.3% of the present study’s respondents were female.

The third question respondents were asked whether writing style was related to promotional language and whether they perceived these reviews as suspicious. Most respondents confirmed this with 88.9% agreeing. Marketers sometimes pretend to be other consumers and write fake reviews, which can lead to them being suspicious (Goh et al., 2013). The final question regarding writing style asked respondents about the readability of reviews and how this influences perceived credibility. 19.1% selected ‘strongly agree’, 40.1% ‘agree’, and 31.6% ‘neither agree nor disagree’. Well-written reviews are more credible than those which are more difficult to understand (Fang et al., 2016) and this can influence review helpfulness (Fang et al., 2016; Korfiatis et al., 2012).

A new variable was then created by combining the questions relating to factual, emotional, readability, and promotional language to create one variable for writing style. This was measured against trusting reviews and found a moderate positive relationship of r = 0.364. Consequently, due to many respondents either strongly agreeing or agreeing with the above questions, as well as a moderate positive relationship, H2 is accepted.

H3: Respondents were asked whether they believed consumer images influence perceived review credibility. A large proportion of the respondents (88.1%) selected either ‘strongly agree’ or ‘agree’. Consumer images can be extremely useful in determining the trustworthiness of both the review and the reviewer as well as having a positive impact on consumer attitude (Lee et al., 2010).

Respondents were then asked whether a variety of images were important. 82.3% of the respondents agreed. Prior research suggests that consumers may have difficulty processing a lot of visual information due to its perceived complexity (Sohn, 2017). Therefore, respondents were asked about the extent they believe that multiple images of the same room enhance perceived review credibility. 20.4% selected ‘strongly agree’, 40.1% ‘agree’, and 26.3% ‘neither agree nor disagree’.

Due to 60.5% selecting either ‘strongly agree’ or ‘agree’, these findings contrast prior research regarding a vast amount of visual information and perceived complexity.  Respondents were asked to expand on their opinion regarding consumer images. Some participants agreed that a variety of images are important:

      “It’s nice to see a variety of images with reviews to offer another perspective to the professionally-shot images you see on the company’s website and listings”. [ID 144]

Thus, multiple images of the same room allow consumers to view it from the reviewers’ perspective and not just what the marketers/glamping site owners want the consumer to see. As a result, reviewer images provide additional information to the consumer which can help to reduce uncertainty and therefore enhance the decision-making process (Zinko et al., 2020).

There was a consensus among respondents that a variety of images are important, and they must not be edited or appear as if they have been taken by a professional photographer. This is further shown in Table 2. Additionally, most respondents expressed the importance of backing up any statements with images. For example, respondent 21 said: “Images to prove any points made, be it positive or negative – this would help to confirm that the review isn’t biased, or issues are made up”.

Table 2. Images respondents expect to see in a credible review.

Type of Images




Beds, bathroom, windows, decoration, washing up area, kitchen, exterior


Views, food, surrounding areas, a variety of images within the property, different angles, nearby hikes pubs, etc., a wide range, not just one angle, anything provided by the company, landscape, anything associated with the purchase


Pictures to support statements, if something goes wrong then provide proof, if something is good then offer proof, back up points that are made, if something was not as advertised

Consumer images

Include reviewer in the photo, non-edited photos, clearly taken by not a professional photographer, clear photos, different angles to what is used on the website, not blurry, realistic, no filter, pictures of what is advertised on the site but from the consumer perspective


H4a: The survey asked respondents their opinion on positive reviews and perceived credibility. A large proportion of the survey participants (63.8%) disagreed. Therefore, this hypothesis must be accepted. These findings support El-Said (2020) who finds that positive reviews are often perceived as untrustworthy as some hotels tend to have fake positive reviews. To further understand how positive reviews play a role in the decision-making process, respondents were asked to rate how strongly they agree that positive reviews influence booking a glamping trip. A combined 90.1% selected either ‘strongly agree’ or ‘agree’. This supports numerous prior research that positive reviews influence purchase intention (Ghasemaghaei et al., 2018; Somohardjo, 2017). Similarly, 92.8% of respondents agree that they feel favorably towards a glamping business when they have mostly positive reviews.

H4b: The survey then asked respondents to what extent they agree that negative reviews are credible. Results show that 2.6% selected ‘strongly agree’, 13.8% ‘agree’, 20.4% ‘neither agree nor disagree’, 44.1% ‘disagree’ and 19.1% ‘strongly disagree’. Results can conclude that negative reviews are perceived as not credible, and this hypothesis must be rejected. These findings contrast existing research which suggests that negative reviews are perceived as credible as it is unlikely that they will have been created by the seller (Chakraborty, 2019a; Lee et al., 2017). Perhaps this is because some competitors post fake negative reviews for their financial gain (Wang et al., 2018).

The survey asked participants about the influence of negative reviews on purchase intention. Results show that 90.8% agree that if there are mostly negative reviews, this will deter them from booking a glamping trip with that company. Similarly, 85.5% agree that if a glamping site has mostly negative reviews, they feel negative toward the company. These findings are supported by Casado-Diaz et al. (2020) who discovered that once consumers read negative reviews, their attitude toward the hotel is significantly lowered. A combined 74.3% selected ‘strongly agree’ or ‘agree’ suggesting that reviews are perceived as more credible when they describe both positive and negative aspects. Previous research suggests that if there is a combination of positive and negative reviews then this has more of an influence on perceived credibility, than if it was only positive (Kusumasondjaja et al., 2012; Purnawirawan et al., 2015). Mixed reviews that discuss both positive and negative aspects of a glamping site are perceived as more credible, with 50.7% of respondents agreeing that mixed reviews influence purchase intention.

H5: The survey aimed to understand the extent to which consumers believe that extreme reviews are credible. Respondents were first asked about extreme positive reviews. Opinions were mixed among respondents with 5.3% selecting ‘strongly agree’, 30.3% ‘agree, 27.6% ‘neither agree nor disagree’, and 31.6% ‘disagree’. Participants were then asked the same question but regarding extreme negative reviews. 5.3% chose ‘strongly agree’, 28.3% ‘agree’, 27% ‘neither agree nor disagree’, and 33.6% ‘disagree’.

Respondents were further asked their opinions on moderate reviews and perceived credibility. A combined 65.7% agreed that moderate reviews are credible. Moderate reviews are credible and extreme reviews are not, consequently this hypothesis must be rejected. This contrasts with much of the travel and tourism pieces of research which suggest that extreme ratings are the most helpful (Park & Nicolau, 2015; Filieri et al., 2018a). Extreme reviews may look suspicious. Filieri (2016) finds that extreme reviews may have been manipulated by competitors or critical people. It can therefore be assumed that even if an extreme review is perceived as helpful, it does not necessarily mean that it is perceived as credible.

Results achieved from the Pearson correlation showed there to be a very strong positive relationship of r = 0.820 suggesting that there is no real difference between extreme positive and negative.

H6: Respondents were asked their opinions on two-sided reviews and perceived review credibility. Most respondents strongly agreed that two-sided reviews are credible. Respondents were given the option to provide more detail regarding their opinions on review credibility. 21 respondents stated that they want to see an honest opinion that balances the positives and negatives:

“I think a review is credible when it has both good and bad points” [ID 25]

It can therefore be concluded that two-sided reviews are credible resulting in this hypothesis being accepted. These findings are consistent with prior research which finds that two-sided reviews are perceived as highly trustworthy as it provides a balanced argument (Filieri, 2016; Uribe et al., 2016) as well as being more persuasive due to their unbiased nature (Cheung et al., 2012).

H7: Respondents were asked if a consensus amongst reviewers influenced perceived review credibility. Most respondents (83%) agreed with this. When reviews are consistent, this influences perceived credibility (Chakraborty & Bhat, 2018). Moreover, when a product feature is criticized by several reviews, then this increases review trustworthiness (Filieri, 2016). Contradictory reviews can lead to poor information processing and uncertainty (Huang et al., 2018). If one review is inconsistent with the rest of the reviews, the reader tends to regard that comment as untrustworthy (Zhao et al., 2018). Respondents were also asked if the similarity in the structure of the reviews made them suspicious. Results showed that a combined 79% either strongly agreed or agreed. Similar reviews were more likely to be fake (Day et al., 2017).

Reviews can be perceived as suspicious if they are overly positive and posted directly after a negative review. For example: “If the review is very over the top and contradicts a few negative reviews that have all said the same thing” [ID 30]

The pattern in reviews influences perceived credibility, thus this hypothesis can be accepted.

Medium Type

H8: The platform in which the reviews are posted can also contribute to perceived credibility. 82.3% of respondents agreed that reviews are credible when they are on a third-party platform such as TripAdvisor, and 66.5% agreed that reviews are credible on social media. This is in comparison to reviews available on the company’s website where only 36.2% believed that they are credible. Respondents suggested that reviews on a company’s website are biased. Sometimes social media reviews are biased because they are made by influencers. “I am skeptical about people leaving reviews when they are paid to do so. I think that it reduces credibility” [ID 99].

However, not all reviews on social media were suspicious as they can be reviewed by friends and family, and in them the reader trusts more than other anonymous reviewers.

      “Perhaps social media reviews are the most genuine as people have their friends and family on there, and in a sense, it’s the same as recommending to friends and family in real life, just online”[ID 21].

Reviews written on a third-party booking platform and social media are more credible than on a direct-sales platform. This is supported by a moderate positive correlation of r = 0.342 between the third-party platform and trusting online reviews. As well as a moderate positive correlation of r = 0.343 between social media and trusting online reviews. Therefore, the review platform influences perceived credibility, and this hypothesis can be accepted. Reviews available on companies’ websites are often positive or overly positive which can be suspicious (Filieri, 2016). On social media, users can express their real emotions (Zhang et al., 2017; Xu & Lee, 2020).

Review Credibility and Purchase Intention

H9: Respondents were asked directly whether they believe credible reviews influence them to book a glamping trip with that company. Most respondents agreed with this statement with 36.2% selecting ‘strongly agree’, 56.6% ‘agree’, and 6.6% ‘neither agree nor disagree’. Similarly, respondents were asked if they were deterred from booking a glamping trip with that company if they perceived reviews as suspicious. Most respondents agreed with 30.9% ‘strongly agree’, and 53.9% ‘agree’.

The message credibility variable was a new variable created on SPSS combining the answers to several questions which were questions relating directly to the hypotheses. Results show a moderate-strong positive correlation of r = 0.450. Consequently, with a combined score of 92.8% and a strong-moderate positive correlation, this hypothesis can be accepted. Online review credibility is a crucial factor in influencing purchase intention (Chih et al., 2013; Arora & Mail, 2018).

Management Response

H10a: Respondents were asked their opinions regarding management’s response to all reviews and perceived company credibility. Findings showed that 27.6% of respondents ‘strongly agree’, 56.5% ‘agree’, 14.5% ‘neither agree nor disagree’, and 1.3% ‘disagree’.

When managers respond to reviews, the company is perceived as customer-focused, and this; therefore, enhances company credibility. “Managers that respond to negative comments in a positive or apologetic way seem more reliable. Replying to both positive and negative comments shows a manager that cares about their business and customers”. [ID 78]

Accommodative management response is the most effective (Casado-Diaz et al., 2020). Personalization of the response can have an impact on perceived company credibility. 67.8% of respondents agree that when management uses the same response to each review, this can have an adverse effect on perceived company credibility. “The specificity and personalization of each response are essential, that way you know that the company a) remembers the customer, b) cares, and c) is making a genuine effort to improve”. [ID 91]

It can be concluded that management response to reviews enhances perceived company credibility, and this hypothesis can be accepted (Perez-Aranda et al., 2019; Sparks et al., 2016).

H10b: The survey then asked respondents whether management response influences purchase intention. A large proportion of respondents agreed with this statement with 26.3% ‘strongly agree’, 44.7% ‘agree’, 25% ‘neither agree nor disagree’. Additionally, two new variables were created on SPSS. One combined the answers to management response and perceived credibility and the other combined the answers to management response and purchase intention. These two variables were compared together using a Pearson correlation and found a strong positive correlation of r = 0.696. It can be concluded that there is a relationship between those who believe management responses to reviews are credible, and those who believe management response influences purchase intention. Therefore, with a combined 71% for ‘strongly agree’ and ‘agree’, and a strong positive correlation, H10b can be accepted. This is in concordance with existing research which concludes that management response to reviews can increase ratings and popularity rankings (Kwok & Xie, 2016), and enhance future consumers’ likelihood of purchase intention (Zinko et al., 2021). 56.6% of respondents agree that when managers use the same response to each review, this deters them from booking a glamping trip with that company.

Previous research suggests fake reviews are particularly problematic with an average of 20% of all online reviews being suspicious (Schuckert et al., 2016). Respondents were therefore asked for their opinion on which aspects of a review make it suspicious. These findings are summarised in Table 3.

Table 3. Aspects of a review enhancing perceived suspicion

Suspicious Reviews




When the review comes across as a ‘witch hunt’ and cannot give praise for anything, overly negative, overly positive, too one-sided in comparison to other reviews when its positive and other reviews are negative, spiteful, emotional, inflated feelings when a companies’ website shows only positive and TripAdvisor show mixed, too positive with no justification


Short, too much information, only a few sentences with not much to say, non-descriptive, too vague, lacks detail

Writing style

Promotional language, formal language, the same language used in a few reviews, similar writing style to another; if it is inconsistent with other reviews, mentions all USP, gives a biased opinion, if it sounds like a paid review, extra detail that a regular customer wouldn’t mention, robotic language, repetition of phrases/sentences, fake tune, gaslights other reviews, bad grammar, anger


Positive and wooden posted straight after a very negative one, multiple reviews coming in at once, multiple overly positive reviews all posted on the same day, very close dates


Anonymous, the name, random user, username looks fake, over-exaggeration, new account, the name sounds like a bot, no verified tick, someone who has been paid to do a review


No images to back up the claim, no images that prove they were there

Most respondents claimed that when reviews are extreme, this makes them suspicious, whether this is extremely positive or negative. Respondents agreed that writing style can have an impact on perceived suspicion. This is apparent for reviews that are written with promotional language, a similar writing style to another, and bad grammar.

Some respondents suggested that a review is suspicious when they do not include a picture to support their claims, whether this is positive or negative. Possibly glamping goers have different expectations in comparison to holidaymakers in hotels or alternative holiday accommodations. Glamping sites are usually smaller than hotels, and less well-known, consequently, consumers may believe that there is a higher chance of manipulated reviews, as bad ratings will have more of a devastating impact on a smaller, family-run business in comparison to larger hotels. Therefore, images are essential to back up any claims made. 69.1% of respondents agree that suspicious reviews deter them from booking a glamping trip with that company.


The obtained findings showed that review length, writing style, consumer images, and mixed, moderate, and two-sided reviews all positively influence perceived review credibility. When management responds to reviews, the reader perceives the company as credible. This is seen as a sign that the company is customer-focused and it has good community engagement and damage control. It is also the way that management responds to reviews that enhances perceived credibility (Casado-Diaz et al., 2020). Findings suggest that managers must also respond in a personalized way. Responding in a personalized way shows that the company cares, remembers the customer and shows that they are making a genuine effort to improve (Wei et al., 2013).

Glamping sites are often smaller and less well-known in comparison to hotels and generally have more to lose if they are not perceived as credible and customer-focused. Most literature regarding management response has identified the importance of financial performance (Xie et al., 2017; Perez-Aranda et al., 2019). However, this study contributes to the literature by adding the importance of management response to company credibility. The present study finds that the lack of response to reviews has a negative impact on booking a glamping trip.

The findings show that bad grammar and the lack of images to support reviewers’ claims were perceived as suspicious. Suspicious reviews negatively impact purchase intention as readers believe that management may have manipulated the reviews to be in their favor which suggests the company has something to hide. It can therefore be concluded that suspicious reviews negatively influence credibility, and as findings from H9 conclude, credible reviews influence purchase intention.

Third-party review platforms are perceived as the most credible, followed by social media and then direct-sales platforms being the least credible. Promotional language, similar writing style, bad grammar, and lack of reviewer images can lead to review suspicion, which ultimately results in consumers being deterred from booking a glamping trip.

Based on the results from the current study, a revised conceptual framework is developed which shows the sources of perceived credible online reviews and the role in which management response plays to purchase intention. The new conceptual framework removes positive, negative, and extreme reviews from perceived review credibility and adds mixed and moderate reviews instead. The framework also removes the direct-sales platform as a contributor to perceived review credibility. A new dimension for suspicious reviews was added including bad grammar, lack of images, and promotional language. Finally, general response and management response were included which influence company credibility and purchase intention.

Figure 2. Revised Conceptual Framework


Further qualitative studies can be conducted to allow for more in-depth and detailed insight into consumer attitudes. As respondents to this study were aged 18-34, future studies could explore other age groups as attitudes and opinions are likely to differ. Management response to reviews is still a relatively under-researched area. Although this study gained further insight from respondents through open-ended questions, future research is needed to explore this element of online reviews in travel and tourism.


Conflict of interest

The authors declare no potential conflict of interest regarding the publication of this work. In addition, the ethical issues including plagiarism, informed consent, misconduct, data fabrication and, or falsification, double publication and, or submission, and redundancy have been completely witnessed by the authors.


The author(s) received no financial support for the research, authorship, and/or publication of this article.

Akhtar, N., Sun, J., Chen, J., & Akhtar, M. N. (2020). The role of ambivalence in conflicting online hotel reviews. Journal of Hospitality Marketing & Management, 29(4), 471-502.
Arora, L., & Mail, B. K. S. (2018). Influence of review quality, review quantity and review credibility on purchase intention in context of high involvement products. European Journal of Applied Business and Management, 4(4).
Ayeh, J. K., Aun, N., & Law, R. (2013). “Do we believe in TripAdvisor?” Examining credibility perceptions and online travellers’ attitude toward user-generated content. Journal of Travel Research, 52(4), 437-452.
Banjeree, S., & Chua, A. Y. (2019). Trust in online hotel reviews across review polarity and hotel category. Computers in Human Behaviour, 90, 265-275.
Banjeree, S., Bhattacharyya, S., & Bose, I. (2017). Whose online reviews to trust? Understanding reviewer trustworthiness and its impact on business. Decision Support Systems, 96, 17-26.
Bell, E., Bryman, A., & Harley, B. (2018). Business Research Methods. Oxford University Press.
Bhattacherjee, A. (2012). Social Science Research: Principles, Methods and Practices. Global Text Project.
Boo, S., & Busser, J. A. (2018). Meeting planners’ online reviews of destination hotels: A twofold content analysis approach. Tourism Management, 66, 287-301.
Bradley, G. L., Sparks, B. A., & Weber, K. (2015). The stress of anonymous online reviews: A conceptual model and research agenda. International Journal of Contemporary Hospitality Management, 27(5), 739-755.
Carbonell, G., Barbu, C. M., Vorgerd, L., & Brand, M. (2019). The impact of emotionality and trust cues on the perceived trustworthiness of online reviews. Cogent Business & Management, 6(1), 1586062.
Casado-Diaz, A. B., Andreu, L., Beckmann, S. C., & Miller, C. (2020). Negative online reviews and webcare strategies in social media: effects on hotel attitude and booking intentions. Current Issues in Tourism, 23(4), 418-422.
Casidy, R., Wymer, W., & O’Cass, A. (2018). Enhancing hotel brand performance through fostering brand relationship orientation in the minds of consumers. Tourism Management, 66, 72-84.
Chakraborty, U. (2019a). Perceived credibility of online hotel reviews and its impact on hotel booking intentions. International Journal of Contemporary Hospitality Management, 31(9), 3465-3483.
Chakraborty, U. (2019b). The impact of source credible online reviews on purchase intention: The mediating roles of brand equity dimensions. Journal of Research in Interactive Marketing, 13(2), 142-161.
Chakraborty, Y., & Bhat, S. (2018). Credibility of online reviews and its impact on brand image. International Journal of Internet Marketing and Advertising, 12(2), 159-180.
Chang, Y. C., Ku, C. H., & Chen, C. H. (2019). Social media analytics: Extracting and visualising Hilton hotel ratings and reviews from TripAdvisor. International Journal of Information Management, 48, 263-279.
Chen, M. J., & Farn, C. K. (2020). Examining the influence of emotional expressions in online consumer reviews on perceived helpfulness. Information Processing Management, 57(6).
Chen, Y. R., & Chen, H. H. (2015, May). Opinion spam detection in web forum: a real case study. In Proceedings of the 24th International Conference on World Wide Web. 173-183
Cheung, C. M. Y., Sia, C. L., & Kuan, K. K. (2012). Is this review believable? A study of factors affecting the credibility of online consumer reviews from an ELM perspective. Journal of the Association for Information Systems, 13(8), 2.
Cheung, C. M., & Thadani, D. R. (2010). The effectiveness of electronic word-of-mouth communication: A literature analysis. Bled eConference, 23, 329-345.
Chih, W. H., Wang, K. Y., Jsu, L. C., & Huang, S. C. (2013). Investigating electronic word-of-mouth effects on online discussion forums: The role of perceived positive electronic word-of-mouth review credibility. Cyberpsychology, Behaviour, and Social Networking, 16(9), 658-668.
Chua, A. Y., & Banjeree, S. (2015). Understanding review helpfulness as a function of reviewer reputation, review rating, and review depth. Journal of the Association for Information Science and Technology, 66(2), 354-362.
Day, M. Y., Wang, C. C., Chen, C. C., & Yang, S. C. (2017, July). Exploring review spammers by review similarity: A case of fake review in Taiwan. In the Third International Conference on Electronics and Software Science (ICESS2017), 166.
Djafarova, E., & Rushworth, C. (2017). Exploring the credibility of online celebrities’ Instagram profiles in influencing the purchase decisions of young female users. Computers in Human Behaviour, 68, 1-7.
El-Said, O. A. (2020). Impact of online reviews on hotel booking intention: The moderating role of brand image, star category, and price. Tourism Management Perspectives, 33, 100604.
Fan, Y. W., & Miao, Y. F. (2012). Effect of electronic word-of-mouth on consumer purchase intention: The perspective of gender differences. International Journal of Electronic Business Management, 10(3), 175.
Fang, B., Ye, Q., Kucukusta, D., & Law, R. (2016). Analysis of the perceived value of online tourism reviews: Influence of readability and reviewer characteristics. Tourism Management, 52, 498-506.
Filieri, R. (2016). What makes an online consumer review trustworthy? Annals of Tourism Research, 58, 46-64.
Filieri, R., & Mcleay, F. (2014). E-WOM and accommodation: An analysis of the factors that influence travellers’ adoption of information from online reviews. Journal of Travel Research, 53(1), 44-57.
Filieri, R., Hofacker, C. F., & Alguezaui, S. (2018a). What makes information in online consumer reviews over time? The role of review relevancy, factuality, currency, source credibility and ranking score. Computers in Human Behaviour, 80, 122-131.
Filieri, R., Raguseo, E., & Vitari, C. (2019). What moderates the influence of extremely negative ratings? The role of review and reviewer characteristics. International Journal of Hospitality Management, 77, 333-341.
Filieri, R., Vitari, C., & Raguseo, E. (2020). Extreme negative rating and review helpfulness: The moderating role of product quality. Journal of Travel Research.
Folse, J. A. G., Porter III, M., Godbole, M. G., & Reynolds, K. E. (2016). The effects of negatively valanced emotional expressions in online reviews on the reviewer, the review and the product. Psychology & Marketing, 33(9), 747-760.
Geetha, M., Singha, P., & Sinha, S. (2017). Relationship between customer sentiment and online customer ratings for hotels-an empirical analysis. Tourism Management, 61, 43-54.
Ghasemaghaei, M., Eslami, S. P., Deal, K., & Hassanien, K. (2018). Reviews’ length and sentiment as correlates of online reviews’ ratings. Internet Research, 28(3), 544-563.
Goh, K. Y., Heng, C. S., & Lin, Z. (2013). Social media brand community and consumer behaviour: Quantifying the relative impact of user-and marketer-generated content. Information Systems Research, 24(1), 88-107.
Jakic, A., Wagner, M. O., & Meyer, A. (2017). The impact of language style accommodation during social media interactions on brand trust. Journal of Service Management, 28(3), 418-441.
Kim, J., & Lee, K. H. (2019). Influence of integration on interactivity in social media luxury brand communities. Journal of Business Research, 99, 422-429.
Kim, M., Lee, S. M., Choi, S., 7 Kim, S. Y. (2021). Impact of visual information on online consumer review behaviour: Evidence from a hotel booking website. Journal of Retailing and Consumer Services, 60, 102494.
Kim, S. J., Maslowska, E., & Malthouse, E. C. (2017). Understanding the effects of different review features on purchase probability. International Journal of Advertising, 37, 29-53.
Korfiatis, N., Garcia-Bariocanal, E., & Sanchez-Alonso, S. (2012). Evaluating content quality and helpfulness of online product reviews: The interplay of review helpfulness vs. review content. Electronic Commerce Research and Applications, 11(3), 205-217.
Kusumasonkdjaja, S., Shanka, T., & Merchegiani, C. (2012). Credibility of online reviews and initial trust: The roles of reviewer’s identity and review valence. Journal of Vacation Marketing, 18(3), 185-195.
Kwok, L., Xie, K. L. (2016). Factors contributing to the helpfulness of online hotel reviews: Does manager response play a role? International Journal of Contemporary Hospitality Management, 28(10), 2156-2177.
Lee, M., Jeong, M., & Lee, J. (2017). Roles of negative emotions in customers’ perceived helpfulness of hotel reviews on a user-generated review website. International Journal of Contemporary Hospitality Management, 29(2), 762-783.
Lee, W., Gretzel, U., & Law, R. (2010). Quasi-trial experiences through sensory information on destination web sites. Journal of Travel Research, 49(3), 310-322.
Leong, L. Y., Hew, T. S., Ooi, K. B., & Lin, B. (2019). Do electronic word-of-mouth and elaboration likelihood model influence hotel booking? Journal of Computer Information Systems, 59(2), 146-160.
Levy, S. E., Duan, W., & boo, S. (2013). An analysis of one-star online reviews and responses in the Washington, DC, lodging market. Cornell Hospitality Quarterly, 54(1), 49-63.
Li, C., Cui, G., & Peng, L. (2018). Tailoring management response to negative reviews: The effectiveness of accommodative versus defensive responses. Computers in Human Behaviour, 84, 272-284.
Li, F. S., & Ryan, C. (2020). Wester guest experiences of a Pyongyang international hotel, North Korea: Satisfaction under conditions of constrained choice. Tourism Management, 76.
Lin, C. A., & Xu, X. (2017). Effectiveness of online consumer reviews: The influence of valence, reviewer ethnicity, social distance and source trustworthiness. Internet Research, 27(2), 362-380.
Liu, Z., & Park, S. (2015). What makes a useful online review? Implication for travel product websites. Tourism Management, 47, 140-151.
Machackova, H., & Smahel, D. (2018). The perceived importance of credibility cues for the assessment of the trustworthiness of online information by visitors of health-related websites: The role of individual factors. Telematics and Informatics, 35(5), 1534-1541.
Min, H., Lim, Y., & Magnini, V. P. (2015). Factors affecting customer satisfaction in responses to negative online hotel reviews: The impact of empathy, paraphrasing, and speed. Cornell Hospitality Quarterly, 56(2), 223-231.
Moreno, A. G., & Lockett, N. (2016), Social media use in European hotels: benefits and main challenges. Tourism & Management Studies, 12(1), 172-179.
Mudambi, S. M., & Schuff, D. (2010). Research note: What makes a helpful online review? A study of customer reviews on Amazon.com. MIS Quarterly, 185-200.
Mukherjee, A., Venkataraman, V., Liu, B., & Glance, N. (2013, June). What yelp fake review filter might be doing? In Seventh International AAAI Conference on Weblogs and Social Media.
Padma, P., & Ahn, J. (2020). Guest satisfaction & dissatisfaction in luxury hotels: An application of big data. International Journal of Hospitality Management, 84, 102318.
Park, S., & Nicolau, J. L. (2015). Asymmetric effects of online consumer reviews. Annals of Tourism Research, 50, 67-83.
Perez-Aranda, J., Vallespin, M., & Molinillo, S. (2019). Hotels online reputation management: benefits perceived by managers. International Journal of Contemporary Hospitality Management, 31(2), 615-632.
Phillips, P., Barnes, S., Zigan, K., & Schegg, R. (2017). Understanding the impact of online reviews on hotel performance: an empirical analysis. Journal of Travel Research, 56(2), 235-249.
Pihlaja, J., Saarijärvi, H., Spence, M. T., & Yrjölä, M. (2017). From electronic WOM to social eWOM: Bridging the trust deficit. Journal of Marketing Theory and Practice, 25(4), 340-356.
Pizzutti, C., Basso, K., & Albornoz, M. (2016). The effect of the discounted attribute importance in two-sided messages. European Journal of Marketing, 50(9/10), 1703-1725.
Plotinka, D., & Munzel, A. (2016). Delight experts, but never dissatisfy your customers! A multi-category study on the effects of online review source on intention to buy a new product. Journal of Retailing and Consumer Services, 29, 1-11.
Purnawirawan, N., Eisend, M., De Pelsmacker, P., & Dens, N. (2015). A meta-analytic investigation of the role of valence in online reviews. Journal of Interactive Marketing, 31, 17-27.
Reimer, T., & Bankenstein, M. (2016). When good WOM hurts and bad WOM gains: The effect of untrustworthy online reviews. Journal of Business Research, 69(12), 5993-6001.
Salehan, M., 7 Kim, D. J. (2016). Predicting the performance of online consumer reviews: A sentiment mining approach to big data analytics. Decision Support Systems, 81, 30-40.
Saunders, M. N. K., Lewis, P., & Thornhill, A. (2015). Research Methods for Business Students. Harlow, United Kingdom: Pearson Education UK.
Schouten, A. P., Janessen, L., & Verspaget, M. (2020). Celebrity vs influencer endorsements in advertising: The role of identification, credibility, and product-endorser fit. International Journal of Advertising, 39(2), 258-281.
Schuckert, M., Liu, X., & Law, R. (2016). Insights into suspicious online ratings: direct evidence from TripAdvisor. Asia Pacific Journal of Tourism Research, 21(3), 259-272.
Sohn, S. (2017). Consumer processing of mobile online stores: Sources and effects of processing fluency. Journal of Retailing and Consumer Services, 36, 137-147.
Soler, I. P., & Gemar, G. (2017). Brand equity research using online customer ratings of Spanish hotels. International Journal of Tourism Research, 19(2), 191-202.
Somohardjo, N. (2017). The effect of online reviews on the review attitude and purchase intention. Erasmus School of Economics, 1-67.
Sparks, B. A., So, K. K. F., & Bradley, G. (2016). Responding to negative online reviews: The effects of hotel responses on customer inferences of trust and concern. Tourism Management, 53, 74-85.
Tankovska, H. (2021, February). Effect of online reviews on local business customer opinion 2020.
Thomas, M. J., Wirtz, B W., & Weyerer, J. C. (2019). Determinants of online review credibility and its impact on consumers’ purchase intention. Journal of Electronic Commerce Research, 20(1), 1-20.
Toh, R. S., Raven, P., & DeKay, F. (2011). Selling rooms: Hotels vs. third-party websites. Cornell Hospitality Quarterly, 52(2), 181-189.
Tran, L. T. T. (2020). Online reviews and purchase intention: A cosmopolitanism perspective. Tourism Management Perspectives, 35, 100722.
Tsao, W. C., Hsieh, M. T., Shih, L. W., & Lin, T. M. (2015). Compliance with eWOM: The influence of hotel reviews on booking intention from the perspective of consumer conformity. International Journal of Hospitality Management, 46, 99-111.
Uribe, R., Buzeta, C., & Velásquez, M. (2016). Sidedness, commercial intent and expertise in blog advertising. Journal of Business Research, 69(10), 4403-4410.
Wang, H., Batra, R., & Chen, Z. (2016). The moderating role of dialecticism in consumer responses to product information. Journal of Consumer Psychology, 26(3), 381-394.
Wang, M., Lu, Q., Chi, R. T., & Shi, W. (2015). How word-of-mouth moderates room price and hotel stars for online hotel booking: an empirical investigation with Expedia data. Journal of Electronic Commerce Research, 16(1), 72.
Wei, W., Miao, L., & Huang, Z. J. (2013). Customer engagement behaviours and hotel responses. International Journal of Hospitality Management, 33, 316-330.
Weismeuller, J., Harrigan, P., Wang, S., & Soutar, G. N. (2020). Influencer endorsements: How advertising disclosure and source credibility affect consumer purchase intention on social media. Australasian Marketing Journal, 28(4), 160-170.
Wu, K., Vassileva, J., Zhao, Y., Noorian, Z., Waldner, W., & Adaji, I. (2016). Complexity or simplicity? Designing product pictures for advertising in online marketplaces. Journal of Retailing and Consumer Services, 28, 17-27.
Wu, P. F. (2013). In search of negativity bias: An empirical study of perceived helpfulness of online reviews. Psychology & Marketing, 30(11), 971-984.
Xie, K. L., Zhang, Z., & Zhang, Z. (2014). The business value of online consumer reviews and management response to hotel performance. International Journal of Hospitality Management, 43, 1-12.
Xie, S. L., So, K. K. F., & Wang, W. (2017). Joint effects of management responses and online reviews on hotel financial performance: A data-analytics approach. International Journal of Hospitality Management, 62, 101-110.
Xie, S., Wang, G., Lin, S., & Yu, P. S. (2012, August). Review spam detection via temporal pattern discovery. In Proceedings of the 18th ACM SIGKKD International Conference on Knowledge Discovery and Data Mining (pp. 823-831).
Xu, X., & Lee, C. (2020). Utilising the platform economy effect through EWOM: Does the platform matter? International Journal of Production Economics, 227, 107663.
Xu, X., & Li, Y. (2016). The antecedents of customer satisfaction and dissatisfaction toward various types of hotels: A text mining approach. International Journal of Hospitality Management, 55, 57-69.
Yagci, I. A., & Das, S. (2018). Measuring design-level information quality in online reviews. Electronic Commerce Research and Applications, 30, 102-110.
Yang, S. B., Shin, S. H., Joun, Y. J., & Koo, C. (2017). Exploring the comparative importance of online reviews’ heuristic attributes in review helpfulness: a conjoint analysis approach. Journal of Travel & Tourism Marketing, 34(7), 963-985.
Yi, Y., & Jeon, H. (2003). Effects of loyalty programs on value perception, program loyalty, and brand loyalty. Journal of the Academy of Marketing Science, 31(3), 229-240.
Zhang, H. Y., Ji, P., Wang, J. Q., & Chen, X. H. (2017). A novel decision support model for satisfactory restaurants utilising social information: A case study of TripAdvisor.com. Tourism Management, 59, 281-297.
Zhang, S., Zhou, L., Kehoe, J. L., & Kilic, I, Y. (2016). What online reviewer behaviours really matter? Effects of verbal and nonverbal behaviours on detection of fake online reviews. Journal of Management Information Systems, 33(2), 456-481.
Zhao, K., Styllianou, A. C., & Zheng, Y. (2018). Sources and its impacts of social influence from online anonymous user reviews. Information & Management, 55, 16-30.
Zhao, X., Wang, L., Guo, X., & Law, R. (2015). The influence of online reviews to online hotel booking intentions. International Journal of Contemporary Hospitality Management, 27(6), 1343-1364.
Zhao, Y., Xu, X., & Wang, M. (2019). Predicting overall customer satisfaction: Big data evidence from hotel online textual reviews. International Journal of Hospitality Management, 76, 111-121.
Zhong, Z., Yang, Y., & Zhang, M. (2014). Role of online reviews in hotel reservations intention based on social media. Journal of Applied Sciences, 14(4), 341-347.
Zinko, R., Patrick, A., Furner, C. P., Gaines, S., Kim, M. D., Negri, M., & Villarreal, C. (2021). Responding to negative electronic word of mouth to improve purchase intention. Journal of Theoretical and Applied Electronic Commerce Research, 16(6), 1945-1959.
Zinko, R., Stolk, P., Furner, Z., & Almond, B. (2020). A picture is worth a thousand words: how images influence information quality and information load in online reviews. Electronic Markets, 30(4), 775-789.