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Social identity, electronic
word-of-mouth and referrals
in social network services
Jorge Arenas-Gaitan and Francisco Javier Rondan-Cataluña
University of Seville, Seville, Spain, and
Patricio Esteban Ramı́rez-Correa
Catholic University of the North, Coquimbo, Chile
Social identity
in SNS
1149
Received 23 April 2013
Revised 23 April 2013
Accepted 15 October 2013
Abstract
Purpose – The main aim of this work is to explore the mechanisms that promote the transmission and
reception of online opinions (electronic word-of-mouth (eWOM) and referrals) by travel services buyers
in the context of social networks services (SNS).
Design/methodology/approach – The research examines two areas of study: social identification
theory and word-of-mouth communication in the virtual environment (eWOM). Based on these
theories an explicative model has been proposed applying structural equation modeling (SEM)
analysis to a sample of SNS users buying travel services. Partial least squares was chosen as a method
to conduct an SEM analysis.
Findings – First, the results support the central role of social identification in SNS communication.
Second, the results show that SNS users give greater importance to the transmission of communication
than to its reception. This fact supports the idea that SNS is used more as a tool for highlighting and
maintaining social status than as a channel for information.
Originality/value – The study highlights the role of social identification as the core element which
drives SNS. It then analyses the development of eWOM communication in the new context provided
by SNS. In addition eWOM communication is studied from two perspectives: from the standpoint of
the communicator, but also the receiver. Finally, it seems appropriate to differentiate between virtual
communities discussing tourism (e.g. www.TripAdvisor.com) and the SNS (e.g. www.facebook.com,
www.twitter.com). While the former seems to be a growing source of information, the latter acts rather
more in a social context.
Keywords Online social networks, Tourism, Information technology, Communications technologies,
Management information systems, Social identification, e-WOM, Referrals
Paper type Research paper
Introduction
If during the last decade, the internet has been the cornerstone of marketing
relationships, Web 2.0 and social networks services (SNS) now also form an essential
part of the picture. In 2012, more than 1,035 million international tourists were
recorded, according to statistics gathered from the United Nations World Tourism
Organization, 2013, with 2013 figures having been predicted to be even better. On the
other hand, in 2012, the number of internet users worldwide was in excess of 2.7 billion
people, according to the United Nations agency for information and communication
technologies (ITU, 2013). If we focus purely on the SNS Facebook, the world’s leading
social network had more than a billion monthly active users by the end of December
2012 (Facebook, 2013). These figures indicate that both of these worldwide trends are
quite significant in our society.
Kybernetes
Vol. 42 No. 8, 2013
pp. 1149-1165
q Emerald Group Publishing Limited
0368-492X
DOI 10.1108/K-04-2013-0081
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In their own way, new technologies have revived an old marketing subject:,
i.e. word-of-mouth (WOM) communication. The development of the internet and SNS
means that users can share tips, reviews and recommendations in a new virtual
environment, leading to an emerging type of communication called electronic
word-of-mouth (eWOM; Hsueh and Chen, 2010). Previously tourism and marketing
literature had proven WOM to be one of the most effective ways of advertising, being
more successful than either radio or television. Moreover, “eWOM” could overcome the
traditional limitations of WOM, such as the fact that WOM often involves private
conversations which can be difficult to track (Hsueh and Chen, 2010). Therefore, it is
interesting to analyse the relationship between SNS use with eWOM communication
sent or received by tourist service buyers.
We believe that given the social component that defines SNS, an explanation based
on individual aspects provides a partial view of the phenomenon. In particular, the
decision to use online social networking technologies represents a social phenomenon
that depends to a great extent on interactions among users and the use of social
technologies. In addition, this is only possible when a group of individuals are willing
to use the technology repeatedly together (Cheung and Lee, 2010). The inclusion of
social identification theory provides an explanation: people develop a sense of
themselves from the groups to which they belong (Hogg and Terry, 2000; Li, 2011)
along with a collective identity which contrasts with other conditions in which the
individual is unique and separate.
In this study, several research lines converge in the context of the purchase of travel
services. The first includes the study of Web 2.0, as a developing and essential marketing
channel in the tourism industry, which remains an area less studied due to its novelty. This
subject is approached using the theory of social identification, and is supported by others
such as Casaló et al. (2010), Kwon and Wen (2010), Li (2011), Zhou (2011), or Nusair et al.
(2011). The second line of research, addressed in this paper is WOW communication in the
online context provided by SNS. The topic of eWOM among travel service buyers is also
discussed. The majority of work on this subject focuses on post-purchase behaviour
(Hui et al., 2007; Chi and Qu, 2008; Hutchinson et al., 2009; Huang et al., 2010; Chang and
Wang, 2011). The academic literature so far has tended to focus more on the outcomes and
potential of marketing strategies, and in this regard, a systematic empirical investigation
into the motivations behind customer decisions to engage in WOW communication, has
been highly recommended in some recent studies (Shen et al., 2013). This work addresses
the phenomenon of eWOM communication more from the perspective of technology and
individual social behaviour. Some authors (Hennig-Thurau et al., 2010; Libai et al., 2010;
Jalilvand and Samiei, 2012) have highlighted the necessity of undertaking research about
eWOM and SNS in a service marketing context.
There are strong relationships between the service industry and new information
technologies. Service is doubtless one of the economic sectors where the repercussion of
advances in information and communications technology – especially the development
and increasing penetration and use of the internet – has been extensive. The internet and
its most recent evolution in terms of interactivity or the Web 2.0, has had an innovative
impact on all aspects of services. Such a change in the overall operating environment has
resulted in a complete transformation of the conventional customer acquisition model.
The traditional attention, interest, desire and action (AIDA) marketing model according
to which consumers’ acquisition went through the phases of AIDA (prior to purchase)
has been substituted by a new model which recognizes the role of the internet in all the
phases of the acquisition process: attention, interest, search, action and sharing (AISAS).
When applied to the service sector, especially tourism, the last step has become
particularly important (Carvão, 2010). Sharing holiday comments, diaries, tips or photos
has become a frequent practice for a growing number of travellers. Though the
percentage of people that share their experiences at a global level may be relatively small
(many will do the same online but with their circle of friends only in social networks such
as Facebook or Twitter), a much higher percentage of users do read such comments and
take them into account when making purchase decisions ( Johnson et al., 2012).
The main objective of this work is to explain the influence of eWOM on referred
purchases in an SNS context based on social identification theory. This general aim can be
divided into two more specific objectives or sub-goals. For the first sub-goal, we analysed
the social component involved in participation in SNS, so we have adopted the theory of
social identification in this context. Second, we addressed eWOM communication. For
this task, we distinguished between two separate points of view. On the one hand, we
studied the willingness of users to transmit eWOM communication and on the other hand
we analysed the relative importance of eWOM as received communication.
To achieve the above objectives, this paper has been structured as follows: the study
begins with a review of the literature underpinning the main theoretical contributions
related to these topics. This review then provides a basis for developing a set of
hypotheses that result in the research model proposed. To test the proposed model,
partial least squares (PLS) technique is used, this is a methodology for estimating
structural equation modeling (SEM). The results section shows the appropriateness of
the scales of measurement used and the support given to each hypothesis. The work
concludes by addressing the main findings, followed by a discussion of the implications
of the results; outlining the main limitations of the study and proposing future research.
Literature review
In this section, we present the theoretical bases that support the research undertaken.
First, this work is based on a thorough review of the literature about WOM, and its
application to the electronic environment and more recently to SNS. We will complete
this theoretical framework with contributions extracted from social identity (SI) theory.
Word-of-mouth and referrals
Social network sites (SNSs) have become one of the most popular social communication
channels, contacting millions of consumers around the world, and the effect of eWOM
communication using Web 2.0 is an increasing phenomenon. SNS have transformed
the way users interact with each other, obtain products and service information and
make purchasing decisions (Chu and Choi, 2011). The social network setting offers an
appealing context in which to study eWOM. The sites provide easy-to-use tools for
current users to invite others to join the network. The electronic recording of these
outbound referrals (REF) opens a new window into the effects of eWOM (Trusov et al.,
2009). As a result, SNS provide users with an unbiased tool for searching product and
service information which also allows them to offer their own consumer-related advice.
In marketing literature, WOM communication is a widely studied topic, but these
days it has become particularly important because of its Web 2.0 and online social
network application (Trusov et al., 2009). “eWOM” can overcome the traditional
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limitations of WOM, such as the fact that WOM often involves private conversations
which can be difficult to track (Hsueh and Chen, 2010).
WOM has a significant influence on consumers’ decision to change the attitudes and
behaviours of friends and relatives (Opermann, 2000). Therefore, WOM has been
described as one of the important post-purchase behaviours (Harrison-Walker, 2001). It
is even more important and influential in the services context because of their
intangibility and, therefore, greater perceived risk (Casaló et al., 2008). Furthermore,
Garnefeld et al. (2011) argues that recommending a service provider improves the
current customers’ loyalty to the provider and that positive WOM is not only effective
for gaining but also for keeping customers. WOM recommendations are especially
critical in tourism marketing because they are considered to be the most reliable, and
thus they are one of the most sought-after information sources for potential tourists
(Nusair et al., 2011; Leung et al., 2011).
In relation to WOM, communication is addressed from the communicator’s
perspective. A referral or a recommendation represents one form of favourable WOM
that is passed on by a customer about a certain product or service (Wheiler, 1987). In
other words, the point of view of the receiver is adopted. The “desirability” of REF is
related to the benefits to the referrer (the party that takes the initiative) and the receiver
of the referral (Rigopoulou et al., 2008). With regard to this, Chatterjee (2011) examines
the credibility of recommendations received through this new virtual environment.
Another question is the importance given by the receiver to the message received. In
this sense, Arsal et al. (2010) analysed its relevance using content analysis on some
virtual communities focused on tourism.
The social network setting offers an appealing context in which to study eWOM and
REF. The sites provide easy-to-use tools for current users to invite others to join the
network. The electronic recording of these outbound REF opens a new window into the
effects of eWOM (Trusov et al., 2009). Though still a relatively new phenomenon, online
social networking sites have begun to attract the attention of marketing scholars. For
example, Ansari et al. (2008) have developed an approach for modelling multiple
relationships of different types among users of a social networking site. Dholakia et al.
(2004) studied two key group-level determinants of virtual community participation:
group norms and SI. Trusov et al. (2010) proposed a model that enables managers to
determine which users are likely to be influential and therefore, important to the
business in their role of attracting others to the site. There is an article by Bronner and
de Hoog (2011) which is especially relevant, although it does not focus purely on SNS.
They focused on tourists and studied their eWOM in various ways. In addition, they
analysed how tourists decide to make recommendations about their holidays, what
motivates them, and what recommendations they were making. This study seeks to
complement the vision provided by these authors.
Very few studies, so far, have included eWOM and REF among their constructs or latent
variables (Chatterjee, 2011; Huang et al., 2011). This however, is one of the main
contributions of this research. SNS therefore provides a particularly appropriate context for
study given its strong dynamic features (De Bruyn and Lilien, 2008). Consumer behaviour
within SNS, such as Facebook, represents a complex, multi-layered, iterative process which
includes learning, alternative evaluation, and feedback posting, all of which focus on
sharing diverse sets of information (Jane et al., 2007). These virtual communities have very
easy access to direct communication allowing consumers to post their experiences of
products and services (Park and Feinberg, 2010). Therefore, it is easy to argue that SNS use
is an antecedent to providing information about products and services, eWOM, and to
receiving recommendations (REF) about products and services. Furthermore, although
there are many types of user, we understand that those who are more involved and
participatory and who make important contributions in the form of eWOM, are also more
attentive to the recommendations and comments that others post. Comments and support
from other users to their eWOM communication may act as a social reward. Based on the
arguments outlined above, the following hypothesis is developed:
H1. Use of SNS (USE) is positively related to transmitted eWOM.
H2. USE is positively related to received REF.
H3. Transmitted eWOM by SNS is positively related to received REF.
SI theory
SI theory has been used in studies in the fields of tourism and technology (Casaló et al.,
2010; Ku, 2012). Prior research has used SI theory to explain how a person identifies with
others (Akkinen, 2005). Broadly speaking, this theory proposes that people develop a
sense of the self from the groups to which they belong (Hogg and Terry, 2000) and a
collective identity which contrasts with other identities in which the individual is unique
and separate (Bhattacharya et al., 1995). A SI thus implies that the person believes that he
or she belongs to a certain social group and that this membership has a significant value
(Hogg and Terry, 2000; Tajfel et al., 1971). As a result, a sense of unity among group
members is developed. Different from personal identity, SI relates to the individual’s
perceived position in a social group (Viktor et al., 1973). Strong SI is known as an
important variable in self-goal setting. SI helps those with low self-esteem to establish a
self-concept and also helps to avoid low goal-setting (Baumeister, 1993; Brockner et al.,
1998; Festinger, 1954). This implies that SI may influence the actual use of social
network services (Kwon and Wen, 2010). For example, a friend plans to use an instant
messenger for group projects. However, the use of an instant messenger for group
projects depends on whether other friends are willing to use it also. In addition, their
experiences in using it will create a norm for them to continuously use it for other group
projects. Thus, it would be more appropriate to examine the decision to use online social
networks from an intentional social action perspective (Cheung and Lee, 2010).
The main assumption of SI theory is that people are motivated to maintain and
improve self-image as a member of the group (Ely, 1994). Clément et al. (2001) found
that communication support is necessary for those with a SI who collaborate with each
other. This implies that a SNS would be perceived as a useful tool for them, if the tool is
usable. Previous research has found that SI has a significant impact on attitude
(Terry et al., 1997), and that it affects organizational behaviour in knowledge sharing
(Ho et al., 2012). Boyd and Ellison (2007) indicated that SNS provide an opportunity for
users to articulate and make their social connections visible. Moreover, Song and Kim
(2006) proposed SI as a crucial determinant affecting the intention to use SNS. Recently,
Zhou (2011) found a strong relationship between SI and SNS participation. Hence, we
suggest that SI in a social network service will positively influence the USE. According
to these theories, the following hypothesis is developed:
H4. SI is positively related to USE in SNS.
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SI brings about individual behaviours for the benefit of the group members with the
expectation of self-enhancement through a boost in self-esteem that is both personal
and collective (Bagozzi and Lee, 2002). SI is an important indirect determinant of group
behaviour (Bagozzi and Dholakia, 2006). It has been proven that customer communities
organized in small groups around a brand, engender greater social identification, when
compared to similar customer communities organized more generally around the
product category. In the case of virtual communities, WOM has two main functions
related to SI. First, consumers may use WOM as a way to manage other users’
impressions of them. Second, WOM can be a means of expressing concern about others
and helping virtual community members to make better choices (Ryu and Feick, 2007).
Okazaki (2009) showed that, among other elements, SI is an important antecedent
affecting desire (individual-level driver) and social intention (group-level driver) to
engage in eWOM. According to these ideas, we propose the following hypothesis:
H5. SI is positively related to transmitted eWOM in SNS.
H6. SI is positively related to received REF in SNS.
Figure 1 shows our conceptual model and graphically presents our research hypotheses.
Research methodology
Sample and data collection
The empirical research is based on a non-probabilistic and self-selection sampling
method, therefore it is a convenience sample. A questionnaire was published on the
internet and links to this questionnaire were sent by e-mail and SNS to the researchers’
group of contacts, asking these contacts to complete the survey and redirect it to
other contacts. Specifically, the data was collected in Chile and Spain from a sample
of on-line questionnaires between January 14 and March 15, 2011. The exclusion of
invalid questionnaires due to duplications or empty fields provided a final sample
size of 603 respondents, who had bought tourist services in the previous year and
used SNS. The fact that 81.1 per cent of this sample bought tourist services through the
SNS Use
H2
H4
Social
Identity
H1
H5
H3
Figure 1.
Proposed model
Word of
Mouth
H6
Referrals
internet is notable. In addition, 61.9 per cent of the sample were women. The majority
of respondents were Spanish and Chilean and marginally from other countries, such
as Germany, Brazil, Argentina, USA, etc. Statistically, significant differences in
responses by nationality were not found. The age of the participants in the sample was
close to the SNS user-average, ranging from 18 to 62 years old, but was made up
predominantly of young people under 30. In relation to SNS, 82 per cent of respondents
used Facebook, 54.7 per cent Tuenti (a Spanish SNS), and 20.1 per cent Twitter.
Measurement scales
The measurement scales applied have been widely tested in other investigations.
Specifically, to measure the USE, the scales proposed by Kwon and Wen (2010) were
adapted. Measurements for SI were adopted from Song and Kim’s (2006) study. To
measure WOM the scales proposed by Walsh and Beatty (2007) were adapted. Referrals
(REF) were quantified by asking the respondents whether: “Recommendations I received
from my social network contacts were important when I bought the trip”. All items were
measured using a seven-point Likert-type scale with anchors from “strongly disagree” to
“strongly agree”. Table II shows the measurement scales used.
A pilot study of a sample size of 50 was conducted to ensure the reliability and
user-friendliness of the questionnaire design. All travel buyers and SNS users responding
to the questionnaire commented on its clarity, readability and ease of understanding. As
a result, no amendments were made in terms of the rewording of items.
Statistical tools
PLS was chosen to conduct data analyses in this study. Unlike LISREL-type SEM, which
is based on the covariance structure of the latent variables, PLS is a component-based
approach. PLS aims to examine the significance of the relationships between research
constructs and the predictive power of the dependent variable (Chin, 1998). Thus, PLS is
suitable for predictive applications and theory building. Referral is measured via a
single objective indicator, therefore, the validity and reliability of this measurement
scale is guaranteed. PLS has three major advantages over other SEM techniques that
make it well suited to this study. First, in PLS, constructs may be measured by a single
item whereas in covariance-based approaches, at least four questions per construct are
required. Second, in most social studies, data tend to be distributed non-normally, and
PLS does not require any normality assumptions and handles non-normal distributions
relatively well. Third, PLS accounts for measurement error and should provide more
accurate estimates of interaction effects such as mediation (Chin, 1998; Gefen and
Straub, 2000) and has the ability to handle a relatively small sample size (Barclay et al.,
1995; Chin, 1998). Because PLS considers all path coefficients simultaneously, it allows
analysis of direct, indirect, and spurious relationships. PLS estimates multiple
individual item loadings in the context of a theoretically specified model rather than in
isolation, so it also enables researchers to avoid biased and inconsistent parameter
estimates for equations (White et al., 2003). Therefore, PLS is an appropriate choice for
testing a research model. SmartPLS 2.0 M3 was specifically used in this study.
Results
The SEM analysis was conducted by constructing a measurement model and a
structural model. The measurement model analysed relationships among a set of
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Table I.
Demographic profile
observed variables and a predetermined number of latent variables. Reliability was
tested using construct reliability and item reliability. Having ensured that the scale
was reliable, the next step was to check the construct validity. Then the measurement
model was evaluated and finalized before the structural model was evaluated.
Measurement model
To assess the constructs, we conducted a confirmatory factor analysis (CFA) using
PLS. Based on the CFA results, we analysed convergent validity, discriminant validity,
and the reliability of all the multiple-item scales, following the guidelines from previous
literature (Fornell and Larcker, 1981; Gefen and Straub, 2000). The measurement
properties are reported in Table I.
Reliability was assessed in terms of composite reliability and Cronbach’s a, which
measures the degree to which items are free from random error and therefore yield
consistent results. Composite reliabilities in our measurement model ranged from
0.897 to 0.926 (Table I), Cronbach’s a ranged from 0.830 to 0.880, in both cases the
scores are above the recommended cut-off of 0.70 (Fornell and Larcker, 1981; Nunnally
and Bernstein, 1994).
Convergent validity was assessed in terms of factor loadings and average variance
extracted (AVE). Convergent validity requires a factor loading greater than 0.70 and an
AVE of no less than 0.50 (Fornell and Larcker, 1981). As shown in Table I, all items had
factor loadings over 0.70 ( p , 0.01). AVE ranged from 0.745 to 0.807, suggesting
adequate convergent validity.
Discriminant validity was assessed by comparing the AVE of each individual
construct with shared variances between this individual construct and all the other
constructs. Higher AVE of the individual construct than shared variances suggests
discriminant validity (Fornell and Larcker, 1981). Table II shows the inter-construct
correlations off the diagonal of the matrix. Comparing all the correlations and square
roots of AVE shown on the diagonal, the results indicated adequate discriminant
validity (Table III).
SNS
Facebook
Tuenti
Twitter
Gender
Men
Women
Age
Mean
, 20
20-30
30-40
. 40
Nationality
Spain
Chile
USA
German
Others
82%
54.7%
20.1%
38.1%
61.9%
24.56 years
21.4%
63.5%
11.5%
4.6%
67.7%
15%
6.8%
3.5%
7%
Reliability and
Construct validity
SI
USE
WOM
Referrals
(REF)
SI
Referrals
USE
WOW
Items
AVE: 0.807
Composite
reliability: 0.926
Cronbach’s a: 0.880
AVE: 0.745
Composite
reliability: 0.897
Cronbach’s a: 0.830
AVE: 0.804
Composite
reliability: 0.925
Cronbach’s a: 0.878
AVE: n.a.
Composite
reliability: n.a.
Cronbach’s a: n.a.
Loading
SI1: as a member of the community, my position is very
important to me
SI2: as a member of the community, I am the type
of person who likes to engage in my community
SI3: activities in my community are the important
part in my life
USE1: I tend to use the SNS frequently
USE2: I spend a lot of time on SNS
USE3: I exerted myself to SNS
WOM1: I’m likely to say good things about this company
WOM2: I would recommend this company to my friends
and relatives
WOM3: If my friends were looking for a new company
of this type, I would tell them to try this place
REF: I buy trips taking into account recommendations
of my friends in social network sites
Social identity
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0.881
0.920
0.894
1157
0.808
0.898
0.883
0.888
0.919
0.884
n.a.
Table II.
Reliability and validity
SI
Referrals
USE
WOW
0.807
0.176205
0.490470
0.372599
n.a.
0.222636
0.367508
0.863
0.355938
0.897
The structural model
Assessment of the structural model involved estimating the path loadings and the R 2
values. Path loadings indicate the strengths of the relationships between the
independent variables and dependent variable, while R 2 values measure the
predictive power of the structural models. Interpreted as multiple regression results,
the R 2 indicates the amount of variance explained by the exogenous variables. Using a
bootstrapping technique, we calculated path loadings and t-statistics for hypothesized
relationships. The results are shown in Figure 2.
As indicated by path loadings and the associated significance levels, the influence of
SI on REF (0.002) is not significant, but the influence of SNS use on REF (0.104) is
significant at 90 per cent of confidence level. These results point out the rejection of H6,
and the partial support of H2.
On the other hand, SI significantly affects both WOW and SNS use. These results
confirm H5 and H4. In addition, a significant relationship between SNS use and eWOM
communication is found, this fact supports H1. Finally, eWOM communication shows a
strong relationship to the importance of Referrals obtained via SNS, this result confirms H3.
Table III.
Discriminant validity
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0.240
0.104
*
0.
49
0*
***
1158
0.002 n.s.
Social
Identity
0.228****
Referrals
0.144
*
**
2
*
60
0.
***
30*
0.3
Word Of
Mouth
0.178
Figure 2.
Result
Notes: Statistically significant at: *p < 0.1, **p < 0.05,
***p < 0.01, ****p < 0.001 and n.s. – no significant
As shown in Figure 2, the model has a relatively appropriate goodness of fit.
SI explained 24 per cent of variance in USE. For communication variables, the model
explained 17.8 per cent of variance in WOW and 14.4 per cent of variance in referrals.
Discussion
This work endeavors to explain eWOM communication in the context of the SNS users
who are travel service buyers. This aim is achieved through two more specific
objectives, which we call sub-goals.
In the first sub-goal, the social component implicit in SNS based on the theory of
social identification is examined. SI explains SNS use adequately, and there is a strong
relationship between both constructs. This relationship is incorporated in H4. The
same occurs with H5, which reflects the relationship between social identification and
eWOM communication. However, H6 has not been accepted, therefore, SI is not related
to the importance given to REF in SNS users who buy tourist services. This finding is
unexpected and the explanation could be the following. It is likely that SNS users
showing a high SI were not very interested in the recommendations posted by their
friends in SNS, because the formers may think that the opinions of the latters are not
well-founded. In addition, SNS users presenting a low SI may not pay much attention
to SNS, and therefore, their friends and family recommendations are ignored.
In general, these results indicate the key role played by social identification in the
context of SNS. This idea is consistent with Cheung and Lee (2010), Li (2011) and Zhou
(2011). Cheung and Lee (2010) noted that the USE is basically a social phenomenon that
largely depends on the interaction among users. In addition the use of social
technologies only makes sense when a group of individuals are willing to use and
continue to use the technology together. Li (2011) found that status has an important
role in the intention to use SNS, from the point of view of social influence. Zhou (2011)
found a strong relationship between SI and SNS participation. Concretely, this author
highlighted the relevance of the cognitive and the evaluative elements. In the same
way, these results are supported by those obtained by Hsu et al. (2006). They affirm
that reference groups have a big influence on the behaviour of individual tourists.
Furthermore, tourist service buyers confirm eWOM as a type of social activity: it is a
way of offering advice and getting noticed among their group of contacts.
The second and last sub-goal relates to eWOM communication. We have identified two
separate views in this area. On the one hand, we have collected data on users’ willingness to
publish eWOM communication. On the other hand, we have analysed the relative
importance of received REF. H1 deals with the relationship between the USE by travel
service buyers and the eWOM communication transmitted by them. H2 brings together
the relationship between USE and the importance given to REF received by respondents.
The results support both hypotheses, but H2 is only partially confirmed. In addition, H3
proposes that transmitting eWOM communication is an antecedent of REF, and in this
case the hypothesis is sustained. If we add these results to the above sub-goal, we find that
SI indirectly affects REF in two ways, significantly via eWOM communication, and less so
in SNS use. This means that respondents are more interested in publishing messages for
their group of contacts about services bought and experiences lived than in taking into
account information from others that helps them to decide about future purchases.
However, these individuals are interested in comments made by their social network group
on their previous posts, which is consistent with the social vision of using SNS. SI makes
people use SNS, but this fact does not always mean that the recommendations offered by
their acquaintances are adopted, if they have not asked for them. These results are
consistent with the motivations found by Bronner and de Hoog (2011) in the section on
tourists. Furthermore, these results are consistent with those obtained by Muñoz-Leiva et al.
(2012) who found behaviour differences between virtual communities specializing in
tourism (www.tripadvisor.com) and SNS (www.facebook.com).
In short, respondents use SNS as a means of displaying their social position to their
group of contacts, and especially as a way of providing advice and information to their
contacts, about tourism services bought and experiences lived. Our results do not
support SNS as a means of gathering information, people seem less interested in
collecting recommendations on tourist services, than in communicating about
activities that reinforce the position individuals occupy in their social network. It is
possible that REF have more relevance in virtual communities specializing in tourism
(Arsal et al., 2010), but their influence is limited in SNS.
Theoretical contribution
From a theoretical viewpoint, this work makes several significant contributions. First,
we highlight the role of social identification as the soul, the heart, which drives SNS.
SI is a strong antecedent of eWOM and USE, presenting a positive and significant
relationship with both variables. Previous studies found a direct relationship between
SI and USE (Zhou, 2011), but the link between SI and eWOM is novel and original.
Second, the study analyses the development of eWOM communication in the new
context provided by SNS. The contribution is that SNS promote a greater use of
eWOM. In spite of the fact that WOM is a traditional marketing tool, the new context of
SNS provides a markedly social development of eWOM as a way of communication.
Third, eWOM communication is studied from two perspectives, i.e. from the
standpoint of the communicator, but also from that of the receiver. To include eWOM
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and REF as two different communication tools is the major contribution of this study.
The positive relationships between USE and REF, and eWOM and REF have not been
simultaneously studied in previous studies. Fourth, a distinguishing feature of this
work is that the sample is composed essentially of SNS users and travel buyers from
Spain and Chile. Two Latin countries that share important similarities and also some
differences (Arenas et al., 2011), but differ from other typical studies in these topics that
analyse Asian and Anglo-Saxon cultures.
Managerial implications
With regard to its practical implications, this work provides several elements that must
be considered. It seems appropriate to differentiate between virtual communities based
on tourism (e.g. www.TripAdvisor.com) and the SNS (e.g. www.facebook.com, www.
twitter.com). While the former seem to be a growing source of information, the latter acts
more in a social capacity. Focusing on the latter, the results of this study explained the
central role that social position plays in individual behaviour on social networks. The
USE and generated eWOM communication are closely related to the importance that
social position plays for individuals. From the point of view of management, travel
industry leaders should promote actions that reaffirm the social position of individuals.
This is vital to provide travel buyers with the opportunity to share their participation in
tourist activities and other services with their social networks. For example,
a holiday-oriented hotel can take pictures of parties and celebrations (such as sports
tournaments), and invite their customers to be tagged in these photos, which in turn
allows its customers to show their participation in the events to their contacts. Holiday
adventure companies can do something similar (diving, rafting, cannoning, etc.), showing
pictures of their customers at key moments, and inviting them to be tagged. In this way,
companies will achieve positive eWOM communication from their clients, who can show
their experiences to their net contacts, reaffirming their status. In addition, those who
have had good service experiences, and who engage in publishing their opinions and
feelings in SNS, are very likely to lead positive eWOM communication. Consequently,
this important group of influencers can be identified and supported by companies.
Moreover, companies should develop mechanisms for obtaining this valuable
information on what social network users say about them. The development of
“community managers” is essential in building a communication strategy which taps
into the huge amount of information users publish on social networks about the company,
in order to reaffirm positive feedback and to promote the overall image of the company.
Conclusions and limitations
In conclusion, we have studied WOW communication in the context of SNS. Given the
novelty and dynamism of this environment this is quite an attractive and relevant
subject area to explore. To do this we have relied on the idea that user behaviour in SNS
is strongly influenced by their social environment. On the other hand, WOW
communication in SNS is more dynamic than in other environments. We considered both
types of eWOM communication, i.e. as transmitted and as received REF. In summary,
our work indicates that tourism service consumers use eWOM communication as a tool
to assert their social group, rather than as a tool for gathering information.
Finally, this work has some limitations. For example, we have used a non-random
sampling method and it would be necessary to validate and generalize the results using
random sampling methods in future investigations. Furthermore, we must point out
that the majority of individuals who participated in the study were living in a Latin
culture. The sample size did not enable us to make generalizations, and the results may
not apply to different nationalities. Developing cross-cultural studies in this area would
be an important line for future research.
Social identity
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References
Akkinen, M. (2005), “Conceptual foundations of online communities”, Working Papers w-387,
Helsinki School of Economics, Helsinki.
Ansari, A., Konigsberg, O. and Stahl, F. (2008), “Modeling multiple relationships in online social
networks”, working paper, Columbia Business School, Columbia University,
Manhattan, NY.
Arenas, J., Rondán, F.J. and Ramirez, P.E. (2011), “Cross cultural analysis of the use and
perceptions of web based learning systems”, Computers and Education, Vol. 57,
pp. 1762-1774.
Arsal, I., Woosnam, K.M., Baldwin, E.D. and Backman, S. (2010), “Residents as travel destination
information providers: an online community perspective”, Journal of Travel Research,
Vol. 49 No. 4, pp. 400-413.
Bagozzi, R.P. and Dholakia, U.M. (2006), “Antecedents and purchase consequences of customer
participation in small group brand communities”, International Journal of Research in
Marketing, Vol. 23, pp. 45-61.
Bagozzi, R.P. and Lee, K.-H. (2002), “Multiple routes for social influence: the role of
compliance, internalization, and social identity”, Social Psychology Quarterly, Vol. 65 No. 3,
pp. 226-247.
Barclay, D., Thompson, R. and Higgins, C. (1995), “The partial least squares approach to causal
modelling: personal computer adoption and use as an illustration”, Technology Studies:
Special Issue on Research Methodology, Vol. 2 No. 2, pp. 285-324.
Baumeister, R.F. (1993), Self-esteem: The Puzzle of Low Self-regard, Lawrence, Hillsdale, NJ.
Bhattacharya, C.B., Hayagreeva, R. and Glynn, M.A. (1995), “Understanding the bond of
identification: an investigation of its correlates among art museum members”, Journal of
Marketing, Vol. 59 No. 4, pp. 46-57.
Boyd, D.M. and Ellison, N.B. (2007), “Social network sites: definition, history, and scholarship”,
Journal of Computer-mediated Communication, Vol. 13 No. 1, pp. 210-230.
Brockner, J., Heuer, L., Siegel, P.A., Wiesenfeld, B., Martin, C. and Grover, S. (1998), “The
moderating effect of self-esteem in reaction to voice: converging evidence from five
studies”, Journal of Personality and Social Psychology, Vol. 75, pp. 394-407.
Bronner, F. and de Hoog, R. (2011), “Vacationers and eWOM: who posts, and why, where, and
what?”, Journal of Travel Research, Vol. 50 No. 1, pp. 15-26.
Carvão, S. (2010), “Embracing user generated content within destination management
organizations to gain a competitive insight into visitors’ profiles”, Worldwide Hospitality
and Tourism Themes, Vol. 2 No. 4, pp. 376-382.
Casaló, L.V., Flavián, C. and Guinalı́u, M. (2008), “The role of satisfaction and website usability in
developing customer loyalty and positive word-of-mouth in the e-banking services”,
International Journal of Bank Marketing, Vol. 26 No. 6, pp. 399-417.
Casaló, L.V., Flavián, C. and Guinalı́u, M. (2010), “Determinants of the intention to participate in
firm-hosted online travel communities and effects on consumer behavioral intentions”,
Tourism Management, Vol. 31, pp. 898-911.
1161
K
42,8
1162
Chang, H.H. and Wang, H.-W. (2011), “The moderating effect of customer perceived value on
online shopping behaviour”, Online Information Review, Vol. 35 No. 3, pp. 333-359.
Chatterjee, P. (2011), “Drivers of new product recommending and referral behaviour on social
network sites”, International Journal of Advertising, Vol. 30 No. 1, pp. 77-101.
Cheung, C.M.K. and Lee, M.K.O. (2010), “A theoretical model of intentional social action in online
social networks”, Decision Support Systems, Vol. 49, pp. 24-30.
Chi, C.G.-Q. and Qu, H. (2008), “Examining the structural relationships of destination image,
tourist satisfaction and destination loyalty: an integrated approach”, Tourism
Management, Vol. 29, pp. 624-636.
Chin, W.W. (1998), “Issues and opinions on structural equation modelling”, MIS Quarterly,
Vol. 22 No. 1, pp. 7-26.
Chu, S. and Choi, S.M. (2011), “Electronic word-of-mouth in social networking sites:
a cross-cultural study of the United States and China”, Journal of Global Marketing,
Vol. 24 No. 3, pp. 236-281.
Clément, R., Noels, K. and Doeneault, B. (2001), “Interethnic contact, identity, and psychological
adjustments in the mediating and moderating roles of communication”, Journal of Social
Issues, Vol. 57, pp. 559-578.
De Bruyn, A. and Lilien, G.L. (2008), “A multi-stage model of word of mouth through viral
marketing”, International Journal of Research in Marketing, Vol. 25 No. 3, pp. 143-225.
Dholakia, U.M., Bagozzi, R.P. and Pearo, L.R.K. (2004), “A social influence model of consumer
participation in network- and small-group-based virtual communities”, International
Journal of Research in Marketing, Vol. 21 No. 3, pp. 241-263.
Ely, R.J. (1994), “The effects of organizational demographics and social identity on relationships
among professional women”, Administrative Science Quarterly, Vol. 39 No. 2, pp. 203-238.
Facebook (2013), “Statistical data”, available at: https://newsroom.fb.com/Key-Facts (accessed
March 22, 2013).
Festinger, L. (1954), “A theory of social comparison processes”, Human Relations, Vol. 7,
pp. 117-140.
Fornell, C. and Larcker, D. (1981), “Evaluating structural equation models with unobservable
variables and measurement error”, Journal of Marketing Research, Vol. 18 No. 1, pp. 39-50.
Garnefeld, I., Helm, S. and Eggert, A. (2011), “Walk your talk: an experimental investigation of
the relationship between word of mouth and communicators’ loyalty”, Journal of Service
Research, Vol. 14, pp. 93-107.
Gefen, D. and Straub, D. (2000), “The relative importance of perceived ease of use in IS adoption:
a study of ecommerce adoption”, Journal of the Association for Information Systems, Vol. 1,
Article 8, available at: http://jais.aisnet.org//articles/1-8/article.htm
Harrison-Walker, J. (2001), “The measurement of word-of-mouth communication and an
investigation of service quality and customer commitment as potential antecedents”,
Journal of Service Research, Vol. 4 No. 1, pp. 60-75.
Hennig-Thurau, T., Malthouse, E.C., Friege, Ch., Gensler, S., Lobschat, L., Rangaswamy, A. and
Skiera, B. (2010), “The impact of new media on customer relationships”, Journal of Service
Research, Vol. 13, pp. 311-330.
Ho, L.A., Kuo, T.H. and Lin, B. (2012), “How social identification and trust influence
organizational online knowledge sharing”, Internet Research, Vol. 22 No. 1, pp. 4-28.
Hogg, M.A. and Terry, D.J. (2000), “Social identity and self-categorization processes in
organizational contexts”, Academy of Management Review, Vol. 25 No. 1, pp. 121-140.
Hsu, C.H.C., Kang, S.K. and Lam, T. (2006), “Reference group influences among Chinese
travellers”, Journal of Travel Research, Vol. 44, pp. 474-484.
Hsueh, S.C. and Chen, J.M. (2010), “Sharing secure m-coupons for peer-generated targeting via
eWOM communications”, Electronic Commerce Research and Applications, Vol. 9 No. 4,
pp. 283-293.
Huang, C.Y., Chou, Ch.J. and Lin, P.Ch. (2010), “Involvement theory in constructing bloggers’
intention to purchase travel products”, Tourism Management, Vol. 31, pp. 513-526.
Huang, M., Cai, F., Tsang, A.S.L. and Zhou, N. (2011), “Making your online voice loud: the critical
role of WOM information”, European Journal of Marketing, Vol. 45 No. 7, pp. 1277-1297.
Hui, T.K.H., Wan, D. and Ho, A. (2007), “Tourists’ satisfaction, recommendation and revisiting
Singapore”, Tourism Management, Vol. 28, pp. 965-975.
Hutchinson, J., Lai, F. and Wang, Y. (2009), “Understanding the relationships of quality, value,
equity, satisfaction, and behavioral intentions among golf travellers”, Tourism
Management, Vol. 30, pp. 298-308.
ITU (2013), “The world in 2013: ICT facts and figures”, available at: www.itu.int/ITU-D/ict/
index.html (accessed March 22, 2013).
Jalilvand, M.R. and Samiei, N. (2012), “The impact of electronic word of mouth on a tourism
destination choice: testing the theory of planned behavior (TPB)”, Internet Research,
Vol. 22 No. 5, pp. 591-612.
Jane, B.T., Cara, O.P. and Tolson, H. (2007), “An exploratory investigation of the virtual
community MySpace.com”, Journal of Fashion Marketing & Management, Vol. 11 No. 4,
pp. 587-603.
Johnson, P.A., Sieber, R.E., Magnien, N. and Ariwi, J. (2012), “Automated web harvesting to
collect and analyse user-generated content for tourism”, Current Issues in Tourism, Vol. 15
No. 3, pp. 293-299.
Ku, E.C.S. (2012), “Distributed fascinating knowledge over an online travel community”,
International Journal of Tourism Research, June.
Kwon, O. and Wen, Y. (2010), “An empirical study of the factors affecting social network service
use”, Computers in Human Behavior, Vol. 26, pp. 254-263.
Leung, D., Law, R. and Lee, H.A. (2011), “The perceived destination image of Hong Kong on
Ctrip.com”, International Journal of Tourism Research, Vol. 13, pp. 124-140.
Li, D.C. (2011), “Online social network acceptance: a social perspective”, Internet Research, Vol. 21
No. 5, pp. 562-580.
Libai, B., Bolton, R., Bügel, M.S., de Ruyter, K., Götz, O., Risselada, H. and Stephen, A.T. (2010),
“Customer-to-customer interactions: broadening the scope of word of mouth research”,
Journal of Service Research, Vol. 13, pp. 267-282.
Muñoz-Leiva, F., Hernández-Méndez, J. and Sánchez-Fernández, J. (2012), “Generalising user
behaviour in online travel sites through the travel 2.0 website acceptance model”, Online
Information Review, Vol. 36 No. 6, pp. 879-902.
Nunnally, J.C. and Bernstein, I. (1994), Psychometric Theory, McGraw-Hill, New York, NY.
Nusair, K., Parsa, H.G. and Cobanoglu, C. (2011), “Building a model of commitment for
Generation Y: an empirical study on e-travel retailers”, Tourism Management, Vol. 32,
pp. 833-843.
Okazaki, S. (2009), “Social influence model and electronic word of mouth: PC versus mobile
internet”, International Journal of Advertising, Vol. 28 No. 3, pp. 439-472.
Social identity
in SNS
1163
K
42,8
1164
Opermann, M. (2000), “Tourism destination loyalty”, Journal of Travel Research, Vol. 39 No. 1,
pp. 78-84.
Park, J. and Feinberg, R. (2010), “E-formity: consumer conformity behaviour in virtual
communities”, Journal of Research in Interactive Marketing, Vol. 4 No. 3, pp. 197-213.
Rigopoulou, I.D., Chaniotakis, I.E., Lymperopoulos, C. and Siomkos, G.I. (2008), “After-sales
service quality as an antecedent of customer satisfaction”, Managing Service Quality,
Vol. 18 No. 5, pp. 512-527.
Ryu, G. and Feick, L. (2007), “A penny for your thoughts: referral reward programs and referral
likelihood”, Journal of Marketing, Vol. 71 No. 1, pp. 84-94.
Shen, X.-L., Wang, N., Sun, Y. and Xiang, L. (2013), “Unleash the power of mobile word-of-mouth:
an empirical study of system and information characteristics in ubiquitous decision
making”, Online Information Review, Vol. 37 No. 1 (accessed January 15, 2013).
Song, J. and Kim, Y.J. (2006), “Social influence process in the acceptance of a virtual community
service”, Information Systems Frontiers, Vol. 8, pp. 241-252.
Tajfel, H., Billig, M., Bundy, R.P. and Flament, C. (1971), “Social categorization and intergroup
behaviour”, European Journal of Social Psychology, Vol. 2, pp. 149-178.
Terry, D., Carey, C. and Callan, V. (1997), “Employee responses to an organizational merger:
group status, group permeability and identification”, Australian Journal of Psychology,
Vol. 49, p. 48, ss.
Trusov, M., Bodapati, A.V. and Bucklin, R.E. (2010), “Determining influential users in internet
social networks”, Journal of Marketing Research, Vol. 47 No. 4, pp. 643-658.
Trusov, M., Bucklin, R.E. and Pauwels, K. (2009), “Effects of word-of-mouth versus traditional
marketing: findings from an internet social networking site”, Journal of Marketing, Vol. 73,
September, pp. 90-102.
UNWTO (2013), “News release – international tourism to continue robust growth in 2013”,
January, Interim update, World Tourism Organization, available at: http://mkt.unwto.org/
en/barometer (accessed March 15, 2013).
Viktor, G., Thomas, D.L. and Weigert, A.J. (1973), “Social identities in Anglo and Latin
adolescents”, Social Forces, Vol. 51, pp. 477-484.
Walsh, G. and Beatty, S.E. (2007), “Measuring customer-based corporate reputation: scale
development, validation, and application”, Journal of the Academy of Marketing Science,
Vol. 35 No. 1, pp. 127-143.
Wheiler, K. (1987), “Referrals between professional service providers”, Industrial Marketing
Management, Vol. 16, pp. 191-200.
White, J.C., Varadarajan, P.R. and Dacin, P.A. (2003), “Market situation interpretation and
response: the role of cognitive style, organizational culture, and information use”, Journal
of Marketing, Vol. 67 No. 3, pp. 63-79.
Zhou, T. (2011), “Understanding online community user participation: a social influence
perspective”, Internet Research, Vol. 21 No. 1, pp. 67-81.
About the authors
Jorge Arenas-Gaitan is an Assistant Professor in the Department of Business Management and
Marketing at the Seville University, Spain. He received his BA and PhD degrees in business
administration from Seville University in Spain. His research interests include behavior of firms
in global markets, cross-cultural studies and information technology acceptance. His work has
been published in journals, books, and refereed conference proceedings, including Computers
& Education, Social Science Computer Review, Journal of Technology Management & Innovation,
Americas Conference on Information Systems Proceeding (AMCIS), International Marketing
Trends Conference Proceeding, and Advances in Data Networks Communications, Computers.
Jorge Arenas-Gaitán is the corresponding author and can be contacted at: [email protected]
Francisco Javier Rondan-Cataluña is an Associated Professor in the Department of
Business Management and Marketing at the Seville University, Spain. He received his BA and
PhD degrees in business administration from Seville University in Spain. His research interests
include franchise, price management and consumer behavior. His work has been published
in journals, books, and refereed conference proceedings, including Computers & Education,
Behaviour & Information Technology, Management Decision and Electronic Commerce Research
and Applications, The Service Industries Journal, International Journal of Service Industry
Management, Americas Conference on Information Systems Proceeding (AMCIS), International
Marketing Trends Conference Proceeding, and Advances in Data Networks Communications,
Computers Proceeding.
Patricio Esteban Ramı́rez-Correa is an Associated Professor in the School of Commercial
Engineering at the University Catholic of the North, Chile. He received his BS degree in computer
engineering and his MA degree in management from Pontifical University Catholic of Valparaiso
in Chile and his MS degree (DEA) in marketing and PhD degree in business administration from
Seville University in Spain. His research interests include enterprise systems and information
technology acceptance. His work has been published in journals, books, and refereed conference
proceedings, including Computers & Education, Journal of Information Systems and Technology
Management, Journal of Technology Management & Innovation, Americas Conference on
Information Systems Proceeding (AMCIS), European and Mediterranean Conference on
Information Systems Proceeding (EMCIS), International Marketing Trends Conference
Proceeding, and Advances in Data Networks Communications, Computers Proceeding.
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