Social media management packages: Recommendation Framing

This post will focus on the social recommendation framing of the message which is generally seen as a crucial dimension by researchers enga...

This post will focus on the social recommendation framing of the message which is generally seen as a crucial dimension by researchers engaging in analyses of eWOM. Several studies on the topic of UGC found that the valence of the message (positive or negative) influences consumer behavior and sales (Sen and Lerman 2007; Vermeulen and Seegers 2009; Ye et al. 2011) sometimes in different ways according to the type of product (hedonic versus utilitarian). There is a direct relationship between valence of the message and booking intentions and decisions (Sen and Lerman 2007; Ye et al. 2011; Sparks and Browning 2011; Mauri and Minazzi 2013). This means that a prevalence of positive messages impacts positively on travelers’ behavior and, in turn, a prevalence of negative WOM has a negative impact on customers’ purchase intentions and decisions (Chatterjee 2001; Bambauer-Sachse and Mangold 2011; Mauri and Minazzi 2013).

Moreover, the balance of positive and negative comments can be a factor which consumers take into account. (Purnawirawan et al. 2012). In fact, if consumers perceive a low level of consensus, they may infer that the authors of negative reviews are unable to use or evaluate the product. On the contrary, in the case of wider consensus on the negative side, customers will develop negative inferences toward the product and the brand (Laczniak et al. 2001). Furthermore, a recent study of Tanford and Montgomery (2014) found that, at the stage of travel decision, the presence of a single negative review can influence in a negative way the decision process, even if the majority of reviews offered favorable feedbacks.

According to various studies, the influence of negative WOM is greater than that of positive WOM because of its detrimental impact on businesses. Moreover, dissatisfied customers are more likely to share negative experiences with other people (Richins 1983; Morris 1988; Hart and Heskett 1990; Tax et al. 1998). Negative consumer reviews have negative effects on perceptions of company reliability and purchase intentions, especially when a company is unfamiliar to the consumer15 (Chatterjee 2001) and especially for experience goods (Park and Lee 2009; Pan and Chiou 2011). Although the majority of researchers endorse this opinion, other studies on the contrary showed that the influence of negative and positive WOM can be very similar (Ricci and Wietsma 2006). Both positive and negative reviews increase consumers’ awareness of hotel existence, balancing the effect of negative comments on consumer opinions (Vermeule and Seegers 2009). This is true especially when the volume of negative WOM is small.

WOM valence can have an influence on customer expectations too (Grönroos 1982; Zeithaml et al. 1993).16 During the stage of information research, customers gather information about the service from various known (WOM) and generally unknown (eWOM) sources, with a positive or negative valence (Mauri 2002), and try to determine what to expect by a specific service (Mauri and Minazzi 2013). If negative WOM could have a detrimental impact on customer booking intentions, a prevalence of positive reviews could increase customer expectations. This is sometimes risky for companies as they have to monitor the online environment continuously to align actual service to customer expectations. Therefore, consulting guests’ reviews can be an effective way to tune into the market, improving the service offered and gaining a competitive edge (Zhang et al. 2010; Ye et al. 2011).

Credibility of User-Generated Content


Due to the possible biased information of the review, decontextualization, and frequent anonymity, before adopting online information customers try to find cues of credibility in the messages. This is particularly true of the tourism sector because of the intangible nature for tourism services and the psychological risk perceived during the travel decision-making process.

Credibility perceptions of eWOM are influenced by informative determinants (argument strength, recommendation framing, recommendation sidedness, source credibility, and confirmation with receiver’s prior belief) (Zhang and Watts 2008; Cheung et al. 2009; Park and Lee 2009) and normative cues (recommendation consistency, recommendation rating) that may be able to supplement informational ones (Cheung et al. 2009).

Information usefulness, information relevance, and eWOM credibility have been demonstrated to impact positively on eWOM adoption and, consequently, on purchase intentions (Cheung and Thadani 2012). Argument quality of an online message and source credibility have proved most influential in relation to information adoption. For what concerns recommendation framing, although positive messages can be helpful in promoting positive attitudes, the presence of a few negative recommendations about the product has been demonstrated to be not so critical, since, on the contrary, it reduces the suspicious behavior of receivers (Doh and Hwang 2009).17 Moreover, considering the content of the message, two-sided information (with both positive and negative information) is generally considered more credible because the consumer thinks that each product has positive and negative features. Therefore, two-sided descriptions are perceived as more detailed information positively influencing argument strength (Cheung et al. 2009). In fact, as noted in the previous sections, the presence of details (Sparks et al. 2013) and personal identifying information (PII) of the reviewers (Xie et al. 2011) are generally considered cues of the validity and credibility of the message (Ayeh et al. 2013). A study of Xie et al. (2011) found that the presence of PII has a positive effect on online reviews perceived credibility, which in turn significantly affects users’ intention to book the hotel. Besides, the presence of personal information about the reviewer enables the reader to assess her/his degree of affinity with the reviewer, an aspect which influences the way the message is interpreted. In light of this, websites that publish recommendations require reviewers to provide personal identifying information (PII) in their profiles (e.g., name, state of residence, gender, and date of visit/stay) (Xie et al. 2011). Since in the online environment similarities among people are evaluated mainly with respect to shared interests (e.g., likes, dislikes, values and experiences) (Brown et al. 2007; De Bruyn and de Lilien 2008), some websites stimulate reviewers, sometimes offering incentives, to add supplementary personal information such as motivations, kind of job, hobbies, etc.

Due to the uncertainty related to online WOM, customers try to find recommendation consistency with their prior knowledge or expectations (Xie et al. 2011) and with the opinions of others on the product (the consensus of other reviewers on the topic). In fact, Xia and Bechwati (2008) found that the influence of the comment depends on the cognitive personalization initiated by the reader. If she/he perceives the situation as familiar, she/he processes the information in a self-referential manner and the review becomes more credible, valid, and trustworthy. The same happens if the receiver of the message finds it congruent with the opinions of other customers publishing feedbacks on the topic.

Source credibility is another widely accepted cue that influences the credibility of the message and then information adoption. It refers to the reputation of the reviewer and the reputation of the platform where the comment is published (Brown et al. 2007). As mentioned above, the reputation of a reviewer is sometimes conferred by the administrator of the website and at other times it is indicated by specific and formal ranking on the base of the helpfulness of the message (Hennig- Thurau et al. 2004; Cheung et al. 2009). It shows how TripAdvisor gives information about the reputation of reviewers. In particular, these are classified as reviewers or contributors according to the number of published recommendations, while the helpfulness of feedbacks is represented by the number of people who found that review useful.

In particular, the trustworthiness of the source of the message (reviewer and website) has been demonstrated to be more influential than expertise (Ayeh et al. 2013). The degree of trustworthiness of the communicator is a significant predictor of trust in the travel sector (Yoo and Gretzel 2011 and 2012). Tiwari and Richards (2013) found that peer networks (Facebook, Linkedin, Twitter, etc.) are more influential than anonymous review websites (TripAdvisor, Yelp) in determining restaurant choice.

According to Brown et al. (2007) online communicators are more and more influenced by the websites rather than individuals credibility. In this case, source credibility depends on the expertise and trustworthiness of the website that publishes the review, rather than on the reviewer himself. Very popular blogs or websites can influence credibility perception, as well as the type of website. For example a corporate blog is generally regarded as less credible than those on consumer-to-consumer virtual communities (such as TripAdvisor, Zoover, etc.) (Park et al. 2007). This is why companies sometimes prefer to attach a link to the corporate website instead of creating a guest comment page.

Reviews, Rankings, and Ratings in the Tourism Sector: The TripAdvisor Experience TripAdvisor is the most popular travel website that enables tourists to plan their trip consulting reviews, rankings, and ratings of various travel services such as accommodation, restaurants, and attractions. It is a consumer-to-consumer virtual community where people share knowledge and search for recommendations about travel services. The website, launched in 2000, has now more than 260 million unique monthly visitors, employs more than 1,600 people, and operates in 42 countries worldwide. Over 150 million reviews and opinions covering more than 4 million accommodations, restaurants, and attractions are published from travelers around the world (TripAdvisor, July 2013).

TripAdvisor collects the recommendations of travelers producing informational and normative based cues of the product quality. In the case of accommodation, we can identify several indicators:
  • the rating, a numerical information on a scale from 1 to 5 (5 being the best) represented by green bubbles. Hotels have an aggregate rating that reflects the average of individual ratings for each review. The rating is also presented according to the type of consumer (families, couples, solo, business) and to the service quality area (location, sleep quality, rooms, service, value, cleanliness);
  • the ranking (popularity index), refers to the position of the hotel with respect to other competitors in the same area on the base of quality, quantity and recency18 of its content on TripAdvisor;
  • the volume, refers to the number of reviews published. It is generally interpreted as another indicator of the popularity of the hotel;
  • the certificate of excellence, that is an award for hotels with high performances concerning rating and ranking;
  • the reviewer reputation, refers to the indicators of reviewers’ expertise. Since 2012 TripAdvisor introduced “badges” for reviewers according to the number of feedbacks published, classifying them from basic to top levels which are visually represented by a star of different color on the base of the level;
  • the number of reviews in the same category, for example regarding accommodation, the number of recommendations the reviewer has published in the same category (hotels);
  • the recommendation rating, refers to the usefulness of judgments expressed by other customers about the topic of the review. TripAdvisor asks each reader: Was this review helpful? The number of reviewers who view the message as helpful is then published under reviewer’s score.

Credibility of reviews, especially those of TripAdvisor and other travel review websites, has been criticized because it is easy to publish fake feedbacks. In fact, all customers, including those who have never visited a certain hotel, can publish a review (Feng et al. 2012; Mayzlin et al. 2012). This is an opportunity for companies to publish positive reviews to enhance their reputation, and negative ones to damage competitors. Hotels sometimes offer incentives to consumers in order to lead them to publish positive comments by rewarding them with discounts and service upgrading. Moreover, some companies specialize in techniques aimed at hiding their identities by creating fake online profiles on consumer review websites or paying freelance writers (this phenomenon is called “astroturfing”). On the other hand, a study of O’Connor (2010) on 100 hotels randomly selected from the 1,042 listed on TripAdvisor’s site for the London market, suggests that, unless some reviews are suspect, the majority of them seems not to be fake.

Nowadays, customers pay more attention to the credibility hints of messages and virtual communities’ validation procedures are more and more under control by public authorities. Following a request by some hotels, UK’s Advertising Standards Authority (ASA) has recently ordered TripAdvisor to rewrite its trust claim (remove the term “trust” from the website communication) (Ayeh et al. 2013). The Attorney General’s office of New York has investigated on the topic and has penalized 19 companies which have to pay more than $ 350 000 for violation “of multiple state laws against false advertising” and engagement “in illegal and deceptive business practices” (New York State office of Attorney General, 23rd September 2013)

Considering this current trend, Google has communicated the intention to fight against fake reviews by changing its algorithm in order to ensure more authentic recommendations (Google 2013). In response to criticism, TripAdvisor explains the methods employed to manage the legitimacy of reviews:
  • Systems, reviews are systematically screened by TripAdvisor proprietary site tools;
  • Community, users warnings about suspicious content;
  • Quality Assurance Teams, an international team of quality assurance specialists investigate suspicious reviews that are flagged by the previous two tools.

However, recent statistics about the travel sector confirm that also customers who purchase offline use mainly the Internet to compare prices and to read reviews by other customers (PhoCusWright 2012). Therefore, despite criticism, TripAdvisor and other similar virtual communities are increasingly employed by customers who are generally able to interpret the messages considering biased information previously described. These trends should be seriously considered by travel companies.

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