10.15178/va.2018.144.77-94
RESEARCH

COMMUNICATION IN THE TOURISM SECTOR. RATINGS AND USER COMMENTS AS STRATEGIC VARIABLES

COMUNICACIÓN EN EL SECTOR TURÍSTICO. PUNTUACIONES Y COMENTARIOS DE USUARIOS COMO VARIABLES ESTRATÉGICAS

COMUNICAÇÃO NO SETOR TURÍSTICO. PONTUAÇÕES E COMENTÁRIOS DE USUÁRIOS COMO VARIAVÉIS ESTRATÉGIAS

Diana Gavilán-Bouzas1 PhD in Economic and Business Sciences from the UCM where she teaches as Prof. Contratado Doctor. His line of research is communication and behavior in technological spaces.
Gema Martinez-Navarro1
Susana Fernández-Lores2

1Complutense University of Madrid. Spain
2ESIC Business & Marketing School. Spain

ABSTRACT
Ratings and reviews made by users on tourist accommodation sites now represent a form of social informational influence that has a great impact on decision-making. This research focuses on analyzing what contents are relevant during the first stage of the decision process when searching for accommodation. Specifically, how users integrate information from other users and the interactions that occur between ratings and reviews. Data were obtained through a qualitative methodology based on focus groups with Millennials and Generation X. Results suggest that in contexts where there is an abundance of options, users adopt strategies that help them discriminate among them. Ratings are particularly important because they facilitate and simplify the process of pre-selection of alternatives. The interaction between the ratings and the number of reviews increase trustworthiness and moderates the decision.

KEY WORDS: Social influence; Ratings; Reviews; Decision process; Communication; Hospitality sector.

RESUMEN
Las evaluaciones o puntuaciones numéricas y los comentarios hechos por usuarios en los sites de alojamientos turísticos representan actualmente una forma de influencia social informacional de gran impacto en la toma de decisiones. Esta investigación se centra en analizar qué contenidos son relevantes en la primera etapa del proceso de selección de alojamientos turísticos; como integran los usuarios la información procedente de otros usuarios y qué tipo de interacciones se producen entre las evaluaciones numéricas y los comentarios. Para ello, se ha llevado a cabo un estudio exploratorio cuyos resultados sugieren que, en contextos donde existe abundancia de opciones, los usuarios recurren a estrategias que les ayuden a discriminar entre ellas. Las evaluaciones numéricas adquieren especial relevancia porque facilitan y simplifican el proceso de preselección de alternativas. Se observa que la interacción entre la evaluación numérica y el número de comentarios confiere credibilidad y modera la decisión.

PALABRAS CLAVE: Influencia Social; Evaluaciones numéricas; Comentarios; Proceso de decisión; Comunicación; Turismo.

RESUME
As valorações ou pontuações numéricas e os comentários feitos por usuários nos sites de alojamentos turísticos representam atualmente uma forma de influência social informacional de grande impacto na toma de decisões. Esta investigação se centra em analisar que conteúdos são relevantes na primeira etapa do processo de seleção de alojamentos turísticos; como integram os usuários a informação procedente de outros usuários e que tipo de interação se produz entre as valorações numéricas e os comentários. Para isso, foi feito um estudo exploratório cujo resultado sugere que, em contextos onde existe abundancia de opiniões, os usuários recorrem a estratégias que os ajudem a discriminar entre elas. As valorações numéricas adquirem especial relevância porque facilitam e simplificam o processo de pré-seleção das alternativas. Observa-se que a interação entre a valoração numérica e o número de comentários confere credibilidade e modera a decisão.

PALAVRAS CHAVE: Influência social; Valorações numéricas; Comentários; Processo de decisão; Comunicação; Turismo

Received: 25/01/2018
Accepted: 19/03/2018

Correspondence: Diana Gavilán Bouzas. Complutense University of Madrid. Spain
dgavilan@ccinf.ucm.es
Gema Martinez-Navarro. Complutense University of Madrid. Spain
dgavilan@ccinf.ucm.es
Susana Fernández-Lores. ESIC Business & Marketing School. Spain
susana.fernandez@esic.edu

How to cite the article
Gavilán Bouzas, D., Martínez Navarro, G., & Fernández Lores, S. (2018). Communication in the tourism sector. Ratings and user comments as strategic variables [Comunicación en el sector turístico. Puntuaciones y comentarios de usuarios como variables estratégicas] Vivat Academia. Revista de Comunicación, nº 144, 77-94. doi: http://doi.org/10.15178/va.2018.144.77-94. Recuperado de http://www.vivatacademia.net/index.php/vivat/article/view/1094

1. INTRODUCTION

Our society relies more and more on the aggregation of digital opinions issued by others. Numerical evaluations, comments and recommendations made by anonymous users in innovative technology platforms facilitate interaction among those who share interests and have become the main source of social influence in purchases (Cisco System Report, 2013). The development of the internet brings with it this phenomenon of online social influence that poses innumerable challenges for companies, how to capture, analyze, interpret and manage social influence online (Litvin, Goldsmith, and Pan, 2008, p.462).
 Social sciences recognize that people have the ability to influence one another (Ditcher, 1966). Specifically, purchasing decisions are strongly influenced by others. On the Internet, this influence is ubiquitous and is exerted through three types of content: comments, recommendations and numerical evaluations (Amblee and Bui, 2012, p. 102). Initially, comments and recommendations received more attention as an object of research, in papers aimed at explaining their influence on the purchasing decision processes. Consulting the recommended products was shown to double the probability of selecting them. However, the influence of comments on purchasing decisions has also been proven in various products: books, hotel stays (Zhu and Zhang, 2010, p.139), cinema films (Reinstein and Snyder, 2005, p. 36). In addition, their ability to modify the notoriety of a product, its reputation, its brand, or the perception of reliability has been contrasted (Lee, Shi, Cheung, Lim, and Sia, 2011, p.189) and they have demonstrated to influence expectations, acting as a point of reference from which to focus the consumer experience (Moe and Schweidel, 2011, page 382).
However, the Internet is a dynamic environment where user behavior evolves rapidly, adapting to the transformation of the Network. Today we are faced with a greater volume of information, new ways of searching, accessing that information and making it useful in the face of future decisions. In this context, the numerical evaluations carried out by users have become one of the most used sources by Internet users. We rely on numerical evaluations and consider them solvent information; in fact, today they are the second most reliable source of information after recommendations made by friends and relatives (Nielsen, 2012). Trust extends to the availability of payment: consumers are willing to pay more for products with an “excellent” rating, numerically 5, than for products with a “good” rating, numerically 4, which does not go unnoticed to companies that translate them into prices above the average -premium- (ComScore, 2007).
 In this context is the objective of this paper: to analyze the online social influence to understand its scope and repercussion on the communication policies of tourist accommodation companies.

2. LITERATURE REVIEW

Year after year it is verified that the influence of the comments published in the Network grows. Users’ confidence in evaluations and comments today is as or more relevant than personal recommendations (BrightLocal, 2014). The literature recognizes that one of the most prevalent determinants of people’s behavior is the influence exerted by those around us. Burnkrant and Cousineau (1975) made this claim in pioneering paper on social influence on behavior. This influence involves the acceptance of information or advice from people who are not known by the subject but who provide credible evidence of reality.
 Informational social influence is especially important when subjects are faced with decision processes in which the following converge: time restriction, limited knowledge, perceived risk and / or lack of interest in making a decision with effort (Lee et al., 2011, p. 187). In such circumstances, the information provided by others, even if they are unknown, may modulate the decision.
The numerical evaluations of the products and services, as well as the comments, in particular their volume, speed up decisions by showing us information easy to understand and quick to process that comes from a large number of subjects, who can be expert professionals or mere users like us (Rao, Greve, and Davis, 2001, p. 512). The possible uncertainty that arises from having to choose from numerous alternatives without knowing which are better and which are worse, exposing oneself to a possible failure (Cialdini and Goldstein, 2004, p.601) and avoiding the cost of experimenting with oneself is resolved by reducing the search for those options that have the support of others. It is the others, users or professionals, who provide reliable clues as to the reality of each option, giving rise to a process of peripheral persuasion (Salmon et al., 2015, p. 116).
The influence of the others can crystallize in the purchase. However, the results obtained in several pieces of research are contradictory (Chen, Gillenson, and Sherrell, 2002, p. 709) because, in order to understand the dynamics of this process, it must be taken into account that multiple moderating factors are involved in it. Indeed, evaluations, comments and recommendations can favor sales, by increasing the likelihood that a product will be chosen, but questions such as the depth of the comment or the specific type of the good to which it refers moderate the relationship. For example, Mudambi and Schuff (2010) observed how the influence of the more detailed comments was greater in goods sought -technological devices- than in the experiential ones -accommodation or restoration-. The popularity of the products, the user’s Internet experience (Zhu and Zhang, 2010, p. 140), the professionalism of the author of the commentary or the expertise of the consumer (Park and Kim, 2009, p. 402) can moderate -intensify or reduce- informational social influence.
 The described characteristics are reproduced in the online purchasing decision processes of numerous products but they have special relevance in the contracting of leisure services, especially accommodation (Olabarri, Monge, and Usín, 2015, p. 713). Each year, hundreds of thousands of potential users of tourist accommodation consult these sites, 84% of whom have their decision affected by what they have seen on the page. Worldwide, the influence of comments and evaluations is estimated at around 10 billion dollars. According to data from PhoCusWright (2013), 83% of users say that opinions help them choose the most suitable accommodation, and 53% do not make any reservation without first having read a comment. We are therefore in an area especially sensitive to informational social influence.
The Spanish tourism market leads the world ranking of tourism competitiveness according to data from the World Economic Forum (WEF), an organization that analyzes the holiday industry of 141 countries around the world. In its 2015 report, it points out that Spanish tourism occupies one of the first positions on the international podium thanks to the richness of its cultural resources, its infrastructures and the adaptation to digital consumption habits. We refer, therefore, to a relevant and expanding market. The latest Report on Electronic Commerce in Spain (Study on Electronic Commerce B2C of 2015, 2016) published by the Ministry of Industry, estimates that accommodation reservations or tour packages have more than 6,300,000 online buyers.
In this context, users face decision processes that can be researched with an academic focus. Adopting a decision is the result of a multistage process. The subjects construct sets of acceptable or satisfactory alternatives that progressively narrow until the decision is consolidated into an option (Roberts and Lattin, 1991, p.435). In the first stage of this process, the objective is to reduce the universe of alternatives to a numerically manageable set of highly relevant options. Therefore, in the first phase, an option acquires relevance if it is sufficiently well-known and reliable. Apart from advertising and the previous experiences that are an unquestionable source of relevance, user evaluations today are an effective way to increase the relevance of an alternative. The scores or numerical evaluations provide information easy to process that allow us to hierarchize the options, applying criteria of selection, for example, only options above 4 in a scale of 5 positions.
 However, these evaluations are accompanied by the number of comments, which suggests the volume of reviewers that the evaluation has generated. The number of comments, when it is high, could give relevance to an option. As users must manage the information provided through both contents –evaluations and comments- they resort to the heuristic of the social test (Cialdini, 2009), a high evaluation accompanied by many comments is a reliable evaluation because it results from the opinion of a lot of people. This way, the volume of comments would act as a moderator of the credibility or confidence the user gives to the evaluation, helping to build the first set of potential relevant options, which will narrow in the following stages, after reading the comments and / or their comparison with other sources.

3. OBJECTIVES

It is in the context described above where the objective of this paper lies: to analyze online social influence. Specifically, the interaction between the influence exerted by numerical evaluations and the volume of evaluators in the first stage of the tourist accommodation decision process. The ultimate goal of this paper is to answer two research questions:

– What contents are relevant to guide the decision process in the first stage?
– How do users integrate the information inputs that come from other users -evaluations and volume of comments- to make a first selection and what kind of interactions occur between these evaluations and comments?

All this is in order to understand how these recommendation mechanisms work and how they can affect tourist accommodation companies due to the impact they have. In the framework of an exploratory study, the qualitative research that has been conducted will provide inputs to answer these questions.
This paper is organized as follows: it begins with a review of the literature on online social influence, with specific reference to the field of tourist accommodation contracting, followed by qualitative research with four group meetings held by users, non-experts, of different generational groups, on the contracting of tourist accommodation through hotel reservation pages. After the presentation of the results, a discussion of the conclusions, contributions and future lines of research of this paper is made.

4. METHODOLOGY

The methodological approach chosen to study the informational social influence exercised through evaluations and comments in the decision-making processes on tourist accommodation is qualitative, since it was desired to know attitudes, feelings and habits up close. This information is full of nuances and it would not be possible to cover it with a quantitative approach. In addition, this perspective allows the researcher to get familiar with the phenomenon he or she wishes to research, more structured knowledge is acquired, concepts are clarified and priorities are established, among other advantages (Selltiz, Wrightsman, and Cook, 1980).
Among the different qualitative techniques for collecting information that allow us to obtain relevant information regarding a specific area of interest, in this study, the focus group method is used. It is an intensive technique that is oriented to knowledge of the structures of perception, obtaining self-confessions from the participants and the objective of which is to carry out a confrontation of opinions and ideas of the participants, with a view to reaching conclusions, an agreement or decisions (Mucchielli, 1978).
 Focus groups have been developed following a semi-directed methodology with a guided approach for which a semi-structured interview guide was developed. It is about provoking a conversation among the participants in a relaxed and comfortable way so that they can present their ideas and opinions and develop a discussion about the raised issues (Krueger, 1991). In order to deepen the information obtained, different projective techniques were used, such as the presentation of images, to encourage participants to express emotions and private feelings by reducing the response barrier (Oppenheim, 1992). The questions have been raised following the funnel technique that involves addressing more generic issues to end up in more specific aspects. For this, the meeting was structured into three blocks of questions: block I, related to the Internet and the tourism sector; block II, questions about the type of content they demand when faced with an online purchase decision regarding a tourist accommodation and block III, about the scores or numerical ratings of the tourist accommodation sites.

5. SAMPLE

In accordance with the characteristics of this piece of research and the objectives that were set, four group meetings have been held on decision-making in the online contracting of tourist accommodation. The sessions lasted about an hour and a half and were held in the Community of Madrid in April 2017. The size of the focus groups recommended by Morgan (1998) and Krueger (1991) is five to ten people, it can be up to twelve; In the case of this study, four focus groups of nine individuals each with ages from 20 to 50 years have been carried out.
Taking into account that the recommendation to select participants in the groups is homogeneity, with the idea of winning in diversity, two discussion groups have been held with millennials (18-30 years) and two others with individuals belonging to Generation- X (30-50 years). In both cases, internal homogeneity has been preserved, since both are generations born under the prism of the digital era that have aroused the interest of many academics and professionals in recent years (Furlong, 2007). The chosen groups represent the generations of the millennium change that confront the paradox of technology that encourages individualism (interaction only with the machine), while promoting communication and collaboration with other Internet users, which is of interest to our study. Despite the differences between groups, the objective of this study is not to obtain information about each group in a specific way but to analyze the results jointly since both groups constitute the main clientele of the analyzed websites. In table 1, the technical data of this piece of research are summarized.

Table 1. Technical data of qualitative research.

Source: Made by the author.

6. RESULTS

Below are the main results obtained after the analysis of the horizontal discourse of the discussion groups based on the blocks indicated in the guided interview and that seek to answer the research questions.

6.1. Results about the Internet and the tourism sector

Regarding the results about the Internet and the tourism sector (block I), it should be noted that all interviewees state that they are accustomed to using the Internet and consider it an essential tool in their purchasing decision process. The Internet is their first choice when faced with the decision to purchase products such as technology, clothing or travel: “if the Internet did not exist, the truth is that I would not even know where to start looking for.”
 When it comes to searching for information to make a possible online reservation, they say that they tend to use preferably generic search engines -Booking or Tripadvisor- rather than the websites of the brands, they refer to reasons such as speed, comfort and the possibility of obtaining all the information they need jointly: «Internet travel search engines have everything. It is fast, comfortable and, above all, you can see prices, offers, comparisons and opinions. Everything at once».

6.2. Content demanded by users

Regarding block II, on the type of content they demand when faced with a decision to purchase a tourist accommodation online, they state that they need information to be clear and easy to read, accurate, not too abundant and with numbers that help them to get a global and quick idea: “information should be little and clear. It is essential that you get numbers, it helps you a lot since you get a quick idea.” “At a first glance you look at the number that appears, it gives you a global idea. It’s clear and easy.”
 There is a broad consensus regarding the priorities of informational content of each hotel. First of all, the information presented must contain a photograph (preferably inside the accommodation) and they are completely unanimous in agreeing that, if there is no photograph, the option is discarded, secondly the attention is directed to the price, then they pay attention to the numerical score of the establishment, and then go to see the number of people who endorse the score. Lastly, they look at complementary information such as offers, information about the location of the hotel, the distance to downtown or the proximity to the subway or bus stations: «Having a photograph is essential, if not, I do not continue reading. The price cannot be missing.
The score, that is, the number is vital, if it does not convince you because it is very low, most of the time you keep looking for other possible options”; “the photo is the first thing you notice, it is important because it gives you confidence, then the score it has been given and it is also important to know how many people have valued it, if there are many people who think so, that gives you more guarantees” ; “I need a large number evaluating the option, that gives me the clue to follow, then it encourages me a lot, when considering the option, to know how many people have said that, if there are many people who think the same makes me eager to explore more about that hotel.” If these aspects are satisfactory to them, then they are encouraged to read the comments.

6.3. Results on numerical evaluations

Regarding block III regarding numerical evaluations, the exploratory analysis leads to the following results:

– First of all, they emphasize that the numerical valuation is very relevant. On a scale of 1 to 10, this piece of information acquires an importance of 8.5: “I would say it is very, very important, from 8 to 9 out of 10”; “It’s vital, on a scale of 1 to 10, I think it’s at least 9 concerning importance.”
– Regarding the presentation of the numerical information, they indicate that it must have a large size and be in bold type to stand out, it must be a number with a decimal (the decimal provides more accurate information and it is more reliable) and finally, it must go in the upper right part. Although it makes no difference whether it is inside a box or not: “it should look good because it’s the first thing you look for, so it should be big and clear, if it takes a decimal it’s better because it’s more accurate and I would say that you trust even more”; “I think it should go on the top right because it’s where it looks best, big and standing out from the other information, for example, go in another color or in bold type.”
– In relation to the evaluation scale, first, they consider that the numerical score should be on a scale of 1 to 10 (for example, 7/10, 8.5 / 10 ...) because it is more intuitive and easier to understand: “We’re used to assessing over 10 points, it’s more precise than over 5, it’s clear and easy to “transform” on one’s mind”; “The score of 5 is insufficient and the one of 100 is cumbersome”. On the other hand, they state that sometimes it is not necessary to put the scale on which the numerical evaluation is obtained because it is understood and with the decimal number would be sufficient. For example, if the score is 8.5 or 6.5, it is understood that it is created over 10 points maximum. In addition, they explain that when the score is less than 5, for example, 4.5 or 4, it is necessary to put on what scale it is based because, otherwise, it can be confusing: “it is necessary to know the scale on which it has been valued when we speak of scores that are less than 5, because if it is a 4.5, it is not the same if it is on a scale of 5 than on a scale of 10.” Finally, they do not consider it necessary to include icons such as faces, circles or stars in the evaluation. They prefer the decimal evaluation: “symbols don’t provide information. Sometimes they confuse and are more difficult to interpret”; “sometimes the stars are confused with the stars of the hotel and it is a mess”; “circles or smiley faces seem scarcely serious to me”.
– Regarding the meaning that the interviewees give to the numerical evaluation, five relevant conclusions have been obtained: (1) On a scale of 1 to 10, they need the evaluation to be at least a 7 to consider an option to be good: “if we speak of a scale of 10 points, there should be at least a remarkable one, no?”; “at least a 7, a five is very little and a six is ??very mediocre.” (2) When the evaluation is less than 7, the purchasing decision process continues as follows: first they look if there is other information of interest that may be relevant such as the location of the hotel or possible offers: “if the rating is under 7, I don’t consider it a good option, although I keep looking for something that could make me opt for that alternative, for example, that it was very close to the beach or downtown, or that the price was a bargain.” Then, if that information does not appear or if it is not relevant enough for the decision maker, it is automatically discarded because it is less than 7 out of 10. (3) When the evaluation of an option is lower than 7 out of 10, the number of evaluators is indifferent and comments are not consulted, except for out of curiosity: “if the rating is not good, I don’t look either at the people who said it or at the opinions. Although I recognize that many times I do it out of curiosity. Because I wonder, why is it so bad?” (4) The numerical evaluation is sufficient, it does not need to be accompanied by words like “very good” or “excellent”. They consider that they do not provide any type of additional information: “with the number, it’s enough, you don’t have to tell me if it’s excellent or rather good, that’s what I do depending on the rating they give”. (5) If there is a symbol, the preference, in order, would be as follows: first stars, although they confuse them with the number of stars of the hotel, in the second place circles, although it is difficult for them to see how many are marked and, finally, faces, since they are not very serious.
– On the importance of the number of comments for their decision, eight main conclusions have been obtained: (1) This information is essential: “it is important to know how many people are giving their opinion, that gives us a lot of confidence”; “The number of evaluators is fundamental, if it doesn’t appear it doesn’t give us confidence, we need that information”; “The more people are evaluating the product, the greater the credibility.” (2) If the number of comments does not appear, the option is discarded: “if the number of people who have commented doesn’t appear, we don’t continue to value”. (3) First, they look at the numerical evaluation and then go on to see the number of comments: “First, it’s always to see the score and then how many people have commented”. (4) The minimum number of comments they need to be sure of their choice depends on aspects such as the type of establishment. In a hotel, they need to have a minimum of 500 opinions, although if we pass to a number of four-digit evaluators, confidence is total: “if there are at least 500 evaluations that is already a good number, although the ideal thing is that the figure has four digits, in that case, the decision is almost immediate.” (5) A high numerical evaluation with few evaluators or comments is ruled out in all cases: “even if the hotel score is high, if not many people say it, I don’t trust completely”; “What gives me confidence that this hotel can be an option is, above all, the fact that many people think the same thing”. (6) A lower evaluation but made by more people gives more confidence than a higher value with fewer comments: “I prefer a rating of 6.5 said by 300 people than one of 6.8 said by only 200 people”. (6) Although they first pay attention to the numerical evaluation, the decision is not adopted until the comments are read: “if there is a rating but there are no opinions, it doesn’t give us any confidence, no matter how good the rating”. (viii) They consider that a somewhat lower numerical evaluation but supported by more comments is preferable than a larger number but said by fewer people: “I prefer a rating of 6.5 said by 300 people than one of 6.8 said by only 200 people”.

Table 2 presents, as a summary, the main conclusions obtained after the discourse analysis with some of the most significant verbatims.

Table 2. Contents and remarkable verbatims

Source: Made by the author

The analysis of the discourse given by the discussion groups leads to the following flow chart in which the decision process followed by the users in the creation of the initial set of alternatives for the contracting of tourist accommodations is represented (Figure 1).

Source: Made by the author.

Figure 1. Sequential process followed by the consumer in the first decision stage. Results of qualitative research.

7. CONCLUSIONS

In this paper, based on the consideration that numerical evaluations and the volume of comments are a form of informational social influence, the variables that influence during the first stage of the decision process, in which the set of alternatives is constructed, as well as the interactions between evaluations and the number of comments, have been analyzed qualitatively.
 Regarding the first research question asked: What contents are relevant to guide the decision process in the first stage? The results follow that the abundance of options to choose from encourages the development of efficient strategies that facilitate the selection process among the alternatives. For an option to be considered, it is necessary that it has a photo, an adequate price and that the numerical evaluation has been made by enough users.
 Regarding the second research question: How do users integrate the information inputs that come from other users -evaluations and volume of comments- to make a first selection and what kinds of interactions occur between these evaluations and comments? The information obtained from the numerical evaluation qualifies the alternative, but it is the number of evaluators that gives credibility or is subtracted from the evaluation. Users try to ratify continuously that the information they receive is reliable. This verification search is solved quickly and little exhaustively with additional data provided in the accommodation offer, as is the volume of evaluators. These results therefore point to a moderating role for the number of evaluators. However, the influence of the number of evaluators when the numerical assessment is low does not affect credibility. This indicates that the moderating role played by the number of evaluators could be asymmetric. If the evaluation is high, it gives it credibility, but if the evaluation is low, however small the number of evaluators, the information is credible because underlying the participation of the users is the idea that they are non-incentivized contributions. Comments are especially reliable if what they say is negative.
The confidence of the user in the evaluations is a crucial aspect for the management of the information that the companies emit due to the weight that they seem to have in the preselection of alternatives. In this regard, companies have understood that the added value of these evaluations transcends the information they provide in their catalogs, since the evaluation is the result of the experience of another user, motivated by reporting what they have lived without hiding negative aspects. For this reason, more and more websites are promoting the numerical evaluation as valuable information available to the user.
 From the business point of view, the participation of the user could arouse some misgivings among operators since it exposes them to client-judges whose evaluation is based mainly on their preferences. Opening the door to user participation is a kind of loss of control over the information that will appear about an organization. However, far from the risk, what research shows is that, when a user is faced with the evaluation of a product or service that has been previously evaluated by others, positive evaluations exercise a positive bias and promote compliance. This effect makes the first evaluations transcendent because they will mark the trend of future evaluations. In short, the promoters of the evaluation of their products or services should not forget that, as popular wisdom says, what starts well, ends well.
 Despite the results that have been obtained, it is not entirely clear if the role played by the number of comments, in the case of contracting accommodations, is exclusively to moderate the credibility of the evaluations or if this data has additional meanings. For example, the number of comments may be able per se to give notoriety to the evaluation, whatever it may be. Particularly in the case of cinema, other studies show that the mere fact of having numerous comments, regardless of the positive or negative sign, exerts a favorable influence on the consideration of a film. The number of comments also implies a social proof that the channel chosen to be informed is adequate because it is chosen by many other users beforehand; in short, it ratifies the election of the channel. Looking ahead, it would be desirable to deepen the influence of the number of comments when considering only the number, and when taking into account their valence.
 The information gathered raises new research questions related to the suitability of the evaluation scales used in websites -numeric, percentage or iconic-, the appropriate form of representation of these evaluations -size of values, colors, typographies-, together with other concrete aspects of the influence exercised by the evaluation on the user, such as the difference between evaluations made with whole numbers versus evaluations made with precise numbers.
 We conclude with a final observation regarding the users of the analyzed information. In this study on informational social influence, we have focused on the management of the information provided to the user, rejecting variables related to the user, such as susceptibility to interpersonal influence and susceptibility to comparative information. This fact has been deliberated in the design of research, which does not mean that in future research it is not desirable to incorporate variables of this nature or even research from them. In particular, susceptibility to interpersonal influence reflects the permeability of information from other people. By recognizing the role of this type of variables, we implicitly record that the processes of informational social influence can be moderated by factors external to the subject that emerge in the context, but also by the nature of the subject itself. In fact, susceptibility to interpersonal influence recognizes the degree of vulnerability of the subject to the influence exercised by others in their decisions, a matter of increasing importance at present.

REFERENCES

1. Amblee N, Bui T (2011). Harnessing the influence of social proof in online shopping: The effect of electronic word of mouth on sales of digital microproducts. International Journal of Electronic Commerce, 16(2), 91-114. doi: 10.2753/JEC1086-4415160205
2. Birkinshaw J, Brannen MY, Tung RL (2011). From a distance and generalizable to up close and grounded: reclaiming a place for qualitative methods in international business research. Journal of International Business Studies, 42, 573-581. doi: 10.1057/jibs.2011.19
3. BrightLocal (2014). Local Consumer Reviewer. Recuperado de www.brightlocal.com/wp-content/uploads/2014/07/Local-Consumer-Review-Survey-20141.pdf
4. Burnkrant RE, Cousineau A (1975). Informational and normative social influence in buyer behavior. Journal of Consumer research, 2(3), 206-215. doi: 10.1086/208633
5. Chen L, Gillenson ML, Sherrell DL (2002). Enticing online consumers: an extended technology acceptance perspective. Information & Management, 39(8):705-719.
6. Cialdini R (2009). Influence: Science and Practice. Boston, MA: Pearson Education.
7. Cialdini R, Goldstein N (2004). Social influence: Compliance and Conformity. Annual Review of Psychology, 55, 591-621. doi: 10.1146/annurev.psych.55.090902.142015
8. ComScore. (2007). Online Consumer-Generated Reviews Have Significant Impact on Offline Purchase Behavior. Recuperado de http://www.comscore.com/Insights/Press-Releases/2007/11/Online-Consumer-Reviews-Impact-Offline-Purchasing-Behavior.
9. Dichter E (1966). How word-of-mouth advertising works. Harvard Business Review, 131-44.
10. Furlong M (2007). Turning Silver into Gold: How to Profit from the New Baby Boomer Market Place. Upper Saddle River, NJ: FT Press.
11. Informe Cisco System. (2013). Informe Anual de Seguridad de Cisco. Recuperado de http://www.cisco.com/web/ES/pdf/Cisco_ASR_2012_v2_020813.pdf.
12. Kelman HC (1961). Processes of opinion change. Public opinion quarterly, 25(1), 57-78.
13. Krueger R (1991). El grupo de discusión. Guía práctica para la investigación aplicada. Madrid: Pirámide.
14. Lee M, Shi N, Cheung C, Lim K, Sia C (2011). Consumer’s Decision to Shop Online: The Moderating Role of Positive Informational Social Influence. Information & Management, 48(6):185-191. doi: 10.1016/j.im.2010.08.005
15. Litvin SW, Goldsmith R, Pan B (2008). Electronic word-of-mouth in hospitality and tourism management. Tourism Management, 29, 458–468. doi: 10.1016/j.procs.2010.12.008
16. Maxwell JA (1998). Designing a qualitative study. En Bickman L, Rog DJ, Handbook of applied social research methods (pp. 69-100). Thousand Oaks, CA: Sage Publications.
17. Moe W, Schweidel D (2011). Online Product Opinions: Incidence, Evaluation and Evolution. Marketing Science, 31(3):372-386. doi: 10.1287/mksc.1110.0662
18. Morgan DL (1998). The focus group guidebook. Thousand Oaks, CA: Sage.
19. Mucchielli R (1978). La entrevista de grupo. Conocimiento del problema y aplicaciones prácticas. Bilbao: Ed. Mensajero.
20. Mudambi SM, Schuff D (2010). What makes a helpful review? A study of customer reviews on Amazon.com. MIS quarterly, 34(1):185-200. Retrieved from http://pdfs.semanticscholar.org/eddb/53ec2f7723fe205d56bed1f284f8174ba7e2.pdf.
21. Nielsen (2012). State of the Media: The Social Media Report. Recuperado de http://www.nielsen.com/us/en/insights/reports/2012/state-of-the-media-the-social-media-report-2012.html.
22. Olabarri ME, Monge S, Usín S (2015). Cómo evalúan los jóvenes las opiniones de otros consumidores en Internet. El caso de la UPV/EHU. Revista Latina de Comunicación Social, 70, 703-725. doi: 10.4185/RLCS-2015-1067
23. ONTSI (2016). Estudio sobre Comercio Electrónico B2C 2015. Recuperado de www.informeticplus.com/estudio-sobre-comercio-electronico-b2c-2015-edicion-2016-ontsi.
24. Oppenheim AN (1992). Questionnaire Design and Attitude Measurement. London: Pinter Publishers.
25. Park DH, Kim S (2009). The effects of consumer knowledge on message processing of electronic word-of-mouth via online consumer reviews. Electronic Commerce Research and Applications, 7(4), 399-410. doi: 10.1016/j.elerap.2007.12.001
26. PhoCusWright. (2013). Travel Tech Trends. Recuperado de http://www.phocuswright.com/Free-Travel-Research/Travel-Tech-Trends-2013.
27. Rao H, Greve HR, Davis GF (2001). Fool’s gold: Social proof in the initiation and abandonment of coverage by Wall Street analysts. Administrative Science Quarterly, 46(3):502-526. doi: 10.2307/3094873
28. Reinstein DA, Snyder CM (2005). The influence of expert reviews on consumer demand for experience goods: A case study of movie critics. The Journal of Industrial Economics, 53(1):27-51. doi: 10.1111/j.0022-1821.2005.00244.x
29. Roberts JH, Lattin JM (1991). Development and Testing of a Model of Consideration Set Composition. Journal of Marketing Research, 28, 429-440.
30. Salmon SJ, De-Vet E, Adriaanse MA, Fennis BM, Veltkamp M, De-Ridder DT (2015). Social proof in the supermarket: Promoting healthy choices under low self-control conditions. Food Quality and Preference, 45, 113-120. doi: 10.1016/j.foodqual.2015.06.004
31. Selltiz C, Wrightsman L, Cook S (1980). Métodos de investigación en las relaciones sociales (9a ed.). Madrid: Rialp.
32. The World Economic Forum (2015). The Travel & Tourism Competitiveness Report 2015. Geneva. Recuperado de http://reports.weforum.org/travel-and-tourism-competitiveness-report 2015/?doing_wp_cron=1497361405.4453260898590087890625
33. Zhu F, Zhang X (2010). Impact of online consumer reviews on sales: The moderating role of product and consumer characteristics. Journal of Marketing, 74(2):133-148. doi: 10.1509/jmkg.74.2.133

AUTHORS
Diana Gavilán Bouzas

She has a degree in Advertising and Public Relations from the Complutense University of Madrid (UCM), a Master’s Degree in Marketing from ESEM and a PhD in Economic and Business Sciences from the UCM where she teaches as a Prof. Contratado Doctor. His line of research is communication and behavior in technological spaces. Author of books and academic articles. He has developed research projects for different companies (IKEA, Tatum). Speaker in academic and professional forums, national (AEMARK, Future of Advertising,) and international (IAMB, EMAC).
http://orcid.org/0000-0002-5293-779X
https://scholar.google.com/citations?user=Ibk0keEAAAAJ&hl=en
https://www.researchgate.net/profile/Diana_Gavilan

Gema Martinez-Navarro
She holds a PhD in Economic and Business Sciences, specializing in Communication, from the Complutense University of Madrid. She is currently an assistant professor in the Department of Marketing and Market Research of the university. She has worked as a consultant and market researcher for different brands. His research facet is linked to the area of communication and new technologies. He has published different articles and participated in national and international congresses. She is the author of the book “Fashion Marketing and Communication”.
http://orcid.org/0000-0002-9047-8010
http://scholar.google.com/citations?user=WN5v8MEAAAAJ&hl=en
https://www.researchgate.net/profile/Gema_Martinez7

Susana Fernández-Lores
Degree in Information Sciences from the Complutense University of Madrid (UCM), Master in Marketing Management from IE Business School and PhD in Economics and Business Administration from the UCM. With extensive professional experience in the field of communication, currently working as a consultant, researcher and university professor. Author of books and academic articles, speaker at academic and professional conferences and co-author of the Work Experiential Engagement model. His line of research is brand and new technologies.
http://orcid.org/0000-0002-1164-0703
https://scholar.google.com/citations?user=dY9ovcwAAAAJ&hl=en
https://www.researchgate.net/profile/Susana_Fernandez_Lores