Information & Management 58 (2021) 103280
Contents lists available at ScienceDirect
Information & Management
journal homepage: www.elsevier.com/locate/im
The role of perceived integration in WeChat usages for seeking information
and sharing comments: A social capital perspective
T
Xiaofang Chena, Jianqing Mab, June Weic, Shuiqing Yanga,*
a
Zhejiang University of Finance and Economics, China
School of Marxism, Zhejiang University, China
c
Department of Management and MIS, College of Business, University of West Florida, Pensacola, FL, USA
b
A R T I C LE I N FO
A B S T R A C T
Keywords:
Social capital
WeChat usages
Social interaction ties
Trust
Perceived similarity
This paper aims at investigating the role of perceived integration in WeChat usages from a social capital perspective. Drawing on social capital theory, the author(s) proposed a research model of college students’ WeChat
usages for seeking information and sharing comments in youth league campus (YLC) activities. The research
model was empirically tested by using data collected from 518 college students who used the WeChat for YLC
activities in China. The results of structural equation modeling analysis indicate that perceived integration
positively affects 3 dimensions of social capital. Perceived similarity and social interaction ties positively affect
seeking information and sharing comments.
1. Introduction
The recent advancements in wireless technologies and the progress
of social networks have facilitated the exponential growth in the use of
the mobile social media [1]. One of the notable examples in the context
of China is WeChat (“Weixin” in Chinese). According to a recent report
published by Tencent [2], the number of WeChat users exceeded 1
billion by the end of February 2018. As one of the world’s most popular
mobile social media, WeChat has been adopted in various contexts including public libraries [3], restaurant services [4], and organizationpublic relationships [5]. In recent years, WeChat has also been applied
in settings beyond the organizational contexts [6,7]. For instance,
WeChat has been employed to promote civic activities and education,
such as youth league campus (YLC) activities in the context of universities. The YLC is a union of college students, which is responsible
for the student council, and other students’ organization and management works [8]. In general, the purpose of the YLC is to organize student activities and to safeguard their legitimate rights and interests. By
taking part in the YLC activities, college students can improve their
abilities for collaboration, creativity, and self-education. In addition,
encouraging college students to participate in YLC activities can help
hone their civic skills, such as abilities to articulate and express their
ideas [9]. These abilities are important to students, which will benefit
them a lot when they join the workplace [8]. However, various issues
such as time constraints and conflicts may inhibit college students’
⁎
participation in YLC activities, particularly the offline-based YLC activities. For instance, public seminar or lecture sessions (e.g., lectures
on future career orientations) sometimes may conflict with the usual
class schedules of college students, preventing them from participating
in these sessions in person. Therefore, how to reduce such conflicts and
facilitate college students’ YLC activities participation is a question that
many educators are asking.
The introduction of WeChat in YLC activities builds a “bridge” between students’ offline and online social lives, and thus offers a way to
mitigate the issue of time constraints and conflicts faced by students. As
a mobile application platform with functions of communications, social
interactions, and platform architectures, WeChat is widely used by
college students and has constructed a new mobile learning support
environment. Indeed, WeChat nowadays has become an indispensable
part of people’s daily lives, especially the young generation in terms of
civic activities and education [7]. Applying WeChat to YLC activities
may help the managers of YLC to disseminate information easily, so
that students can easily learn about their activities and related information. On the other hand, it also enables the students to share information easily, which may help them to develop social interaction
and communication skills that are very important abilities required in
the workplace. In academics, despite many previous studies devoted to
understanding WeChat usages, most of them focused on the sharing
comments behaviors [10,11]. The underlying mechanisms of how
WeChat helps students to seek information and share their comments in
Corresponding author.
E-mail addresses: chenxf2892@163.com (X. Chen), majq2007@163.com (J. Ma), jwei@uwf.edu (J. Wei), yangshuiqing@zufe.edu.cn (S. Yang).
https://doi.org/10.1016/j.im.2020.103280
Received 12 September 2017; Received in revised form 6 February 2020; Accepted 7 February 2020
Available online 07 February 2020
0378-7206/ © 2020 Elsevier B.V. All rights reserved.
Information & Management 58 (2021) 103280
X. Chen, et al.
previous social capital-related research, we measured the structural,
relational, and cognitive dimensions of social capital by using social
interaction ties [14,15], trust [16], and perceived similarity [17], respectively.
YLC activities are unclear.
By providing ubiquitous, convenient, and location-based social
services, WeChat effectively links offline and online activities by
creating a unified and integrative view of YLC activities to the students.
For instance, when students are unable to participate in the offline YLC
activities, WeChat is the platform whereby students can easily participate in the corresponding online YLC activities by obtaining information and joining discussions instantly. This will enable the students to
be aware of the activities and feel as if they are also part of the activities. Moreover, even after participating in the offline YLC activities,
students can also continue participating in the YLC activities online by
using WeChat. This way, WeChat may provide an integrative experience of the YLC activities to the students. This may facilitate the development of social capital among members of the YLC WeChat group,
and in turn make them likely to seek information and share opinions
within the group. Therefore, it is critical to identify factors that motivate college students to use WeChat for seeking information and
sharing comments in the YLC activities from an online and offline
channel integration perspective.
Based on the social capital theory and the literature related to
perceived integration, the present study intends to explore the factors
that affect college students’ WeChat usages in YLC activities by considering online and offline channel integration perceptions.
Specifically, this study intends to investigate: (1) How do the three
dimensions of social capital (social interaction ties, trust, and perceived
similarity) affect college students’ WeChat usages in YLC activities? (2)
What is the role of perceived integration in forming college students’
social capital perceptions and further shaping their WeChat usages for
seeking information and sharing comments in YLC activities?
The present study makes several contributions. First, unlike many
previous studies that focused on the usage of WeChat in various organization settings [e.g., 3, 5], the present study addressed the benefits of
WeChat use in a relatively underexplored context. Specifically, our
study explored how the usage of WeChat can promote YLC activities
among college students and help in their education and civic skills
formation beyond the usual university curriculum design. Second, apart
from many previous studies that examined users’ participation behaviors focusing on sharing comments or contributors’ behaviors [10,12],
the present study investigates students’ participation intention by
considering both acquiring information and sharing comments behaviors. By doing so, our study thus can offer a more holistic insight to
understand college students’ participation behaviors by using WeChat
in the YLC context. Finally, unlike many studies that have examined
WeChat usage in an online channel setting [e.g., 7,11,13], the present
study investigates the factors that affect WeChat usage in YLC activities
from an online and offline channel integration perspective. As students’
traditionally offline social activities have been increasingly integrated
with their corresponding online social activities with the help of WeChat, explaining students’ WeChat usage in YLC activities should consider the offline and online channel integration.
The remainder of this paper is organized as follows: A review of the
literature on social capital is conducted in Section 2. The research
model and hypotheses are examined in Section 3. Then, the research
methodology is discussed in Section 4 and the data analysis in Section
5. The results are discussed in Section 6. Last, the limitations as well as
theoretical and practical implications are discussed in Section 7.
2.1. Theoretical foundation
2.1.1. Social capital theory
Social capital refers to “the sum of the actual and potential resources
embedded within and derived from the network of relationships possessed by an individual or social unit” [18, P.243]. Unlike the physical,
financial, and human capitals, social capital reflects the resources
rooted in social network structures that enable social interaction among
people [19,20]. In general, social capital consists of three dimensions:
structural, relational, and cognitive [21,22]. The structural dimension
is the base of social capital because of its function of connections between actors [17]. The relational dimension of social capital refers to
assets such as trust and trustworthiness created and leveraged through
relationships [23, p.244]. The cognitive dimension of social capital
refers to the resources providing shared representations, goals, and
visions among parties [17,22].
In academics, social capital has been approved as an important resource in both physical and virtual environments. For instance, Ridings,
Gefen, and Arinze (2002) pointed out that social capital was beneficial
for people to seek information through the virtual community. Zhao,
Lu, Wang, Chau, and Zhang [17] found that social capital becomes an
important motivation for an individual’s knowledge seeking and
sharing in the virtual community. The above-mentioned studies are
beneficial for better understanding the role of social capital in explaining user participation behaviors. However, extant studies mainly
applied the social capital theory in a single online channel context, and
few studies explored this issue from an online plus offline perspective.
As the boundaries of college students’ online and offline social lives are
becoming increasingly blurred by using mobile social media (e.g.,
WeChat in China), it is critical to identify the factors that motivate
people to use WeChat from an online and offline integration perspective.
The structural dimension of social capital is measured by social
interaction ties, which is among the most frequently used factors in the
social capital literature [17,22]. Social interaction ties reflect “the level
of frequency and time investment of online community member interactions” [24]. In the context of our study, WeChat users’ social interaction ties are captured by frequency and time investment of interacting with WeChat friends in YLC activities [25]. When college
students participate in the YLC activities, the main reason that they
choose WeChat moments or WeChat public account is to get to know
each other well based on their social interaction ties.
The relational dimension of social capital is measured by trust,
which is one of the key factors in social capital literature [16]. Trust is
important in virtual communities, and it is essential for the continuity
of taking part in the community [17]. Trust can be classified into three
types: interpersonal trust (trust between people), organizational trust
(trust between organizations), and intraorganizational trust (trust between individuals and organizations) [26,27]. In the present study, we
focused on interpersonal trust, which reflects the trust among WeChat
members. In fact, WeChat’s social circle is mainly composed of relatives, friends, and colleagues, so the trust among them is very high. It
is expected that such high-level trust of college students will have a
positive impact on their intention to participate in YLC activities.
The cognitive dimension of social capital is measured by perceived
similarity, which is one of the important factors in social capital literature [17,28]. In the present study, perceived similarity reflects college students’ shared goals, value, and experiences with other YLC
WeChat members [17]. It is expected that college students with a highlevel of similarity to other YLC WeChat members will tend to be more
likely to participate in YLC activities.
2. Theoretical foundation and hypotheses
Based on the social capital theory and prior research related to
perceived integration, a research model was proposed to capture the
factors that affect college students’ WeChat usages in the YLC activities.
As depicted in Fig. 1, perceived integration by using WeChat will positively affect the factors that represent the three dimensions of social
capital, which in turn will positively affect college students’ intention to
seek information and share comments for YLC activities. Following the
2
Information & Management 58 (2021) 103280
X. Chen, et al.
Fig. 1. The research model.
present study, when college students develop a high level of social interaction ties with other members in the YLC WeChat group, they may
be more likely to see the YLC activity information that is of interest to
them. This interest leads to the members in the YLC WeChat group’s
greater motivation to seek more of such information from the WeChat
group. Therefore, it is reasonable to expect that social interaction ties
will positively influence students’ intention to seek information by
using WeChat in YLC activities. Based on existing studies [14,33], we
can hypothesize that:
2.1.2. Perceived integration
The categorization theory posits that people group ideas and objects
into categories on the basis of similarities and consistency perceptions
[29]. If individuals believe the target and source objects as consistent
and unified ones, they will classify these 2 objects into the same category in memory [30]. Such structured information would result in the
process of category-based evaluation, which influences informationprocessing strategies [29]. In the context of the present study, when
students perceive a high integration level between online and offline
YLC activities by using WeChat, they will be more likely to form similar
evaluations for online or offline social activities. The combined onlineoffline socialscape may make them more involved in YLC activities,
even if they are not able to physically attend the activities. This may in
turn create more opportunities for social capital formation. In our
study, the 3 dimensions of social capital are represented by social interaction ties, trust, and perceived similarity, respectively. Based on the
categorization theory [29], it is reasonable to expect that perceived
integration will positively affect the 3 dimensions of social capital including social interaction ties, trust, and perceived similarity.
In fact, because of its ability of anywhere and anytime access, mobile-based social media has significantly changed the ways in which
people conduct their online and offline social activities [22]. As one of
the most popular new social media, WeChat provides an opportunity for
college students to realize their needs by effectively integrating their
online and offline social activities. Based on previous studies [22,31],
we defined perceived integration as the extent to which college students
perceive their online and offline social activities be combined by using
WeChat. The aim of the present study is therefore to explore how
perceived integration may affect students’ social capital perceptions
and consequently their participation behaviors in YLC activities.
H1a. Social interaction ties will positively affect students’ intention to
seek information.
Social interaction ties will also have positive influences on students’
intention to share comments by using WeChat in YLC activities.
Previous studies also validated positive impacts of social factors on
sharing comments or contributors’ behaviors [12,14,34]. For instance,
Chiu, Hsu, and Wang [14] reported a positive influence of social interaction ties on the quantity of knowledge sharing. Similarly, Cheung,
Liu, and Lee [34] also found that social interactions positively affect
customer information contribution behaviors. In the present study, the
more social interaction ties are formed among students, the more the
likelihood of YLC activities information to be seen and appreciated by
others; thus, the motivation to share information or comments increases. Based on extant studies [14,34], we can hypothesize that:
H1b. Social interaction ties will positively affect students’ intention to
share comments.
2.2.2. Trust
Trust is defined as “the expectancy held by an individual or a group
that the word, promise, verbal or written statement of another individual or group can be relied upon” [35, P. 651]. In the present study,
trust could be understood as the interpersonal trust, which reflects a
general trust toward other WeChat members [17]. Nahapiet and
Ghoshal [18] argued that trust plays an important role in maintaining
cooperative interaction between individuals. Because of its important
role, trust has been applied in various contexts to explain user behaviors, including intellectual capital exchange [18], smart government
adoption [36], restaurant service robots [37], and knowledge sharing
[38]. In the context of the present study, a high trust in other YLC group
members may lead one to feel that the information shared in the WeChat group is of high quality and relevance, which make them highly
motivated to seek information in the group. The positive relationship
between trust and participation behaviors has been validated by existing studies [13,17]. For instance, Che and Cao [13] found that trust
has a positive effect on the intention to use social networking sites such
as WeChat. Zhao, Lu, Wang, Chau, and Zhang [17] also found that trust
has a significant impact on the intention to obtain knowledge through a
sense of belonging. Based on previous studies [13,17], we can hypothesize that:
2.2. Research hypotheses
2.2.1. Social interaction ties
Social interaction ties are channels of information and resource
circulation [14]. Granovetter [32] defined tie strength as “a combination of the amount of time, the emotional intensity, the intimacy, and
the reciprocal services, which characterize the tie.” Based on the previous studies [14,32], the present study defined the extent of social
interaction ties as the strength of the interpersonal relationships, the
amount of time spent, and the frequency of communication among
WeChat members. When students regarded WeChat as mediation to
interact and connect with their social relationships, they will be more
likely to participate in YLC activities by using WeChat.
The positive associations between social interaction ties and participation behaviors have been validated by extant studies [14,33]. For
example, Chen, Wu, Peng, and Yeh [33] found that social interaction
ties as one of social capital dimensions have a positive impact on
consumers’ active participation behaviors for searching products/services information on online group buying sites. In the context of the
3
Information & Management 58 (2021) 103280
X. Chen, et al.
H2a. Trust will positively affect the intention to seek information.
media allows people to overcome the space and time constraints of
social interactions [11,22]. Therefore, the higher college students’ online and offline social activities are integrated by using WeChat, the
greater the social interaction ties among the students will be formed.
Previous studies also found that perceived integration positively affects
social interaction ties in the mobile social community context [22].
Thus, we hypothesize that:
It is expected that trust will also positively affect students’ intention
to share comments in YLC activities by using WeChat [39]. In the
present study, college students with a high trust in other YLC group
members will tend to be more likely to share comments through WeChat to enhance their images or impression among other YLC members.
The positive association between trust and sharing behaviors has also
been validated by extant studies [17,39]. For example, Zhang, Fang,
Wei, and Chen [39] found that trust facilitates the intention of sharing
comments/knowledge and intensifies the psychological safety. Zhao,
Lu, Wang, Chau, and Zhang [17] also reported that trust exerts a positive influence on the intention to share knowledge through a sense of
belonging. Following the extant studies [17,39], we can hypothesize
that:
H4a. Perceived integration by using WeChat will positively affect social
interaction ties.
It is expected that perceived integration will also positively influence trust when students’ use WeChat in YLC activities. In the context of
this study, when online and offline YLC activities are perceived by
students as an integrated entity, the formation of trust in the online
group may benefit from such a perception. For instance, Stewart [41]
developed and examined a trust transfer model, and found that perceived business ties between a trust-inducing physical retail store and
an online shopping site positively affect consumers’ trust beliefs regarding the linked site. This suggests that when online and offline activities are integrated in a holistic view to users as afforded by WeChat,
people no longer see online activities as separated from their offline
counterparts, and feel that they are part of the activities whether they
participated online or offline. This may foster a feeling of closeness with
other members, and in turn enhance the formation of trust with them.
According to the categorization theory [29], when students classify
the members who participate in online and offline YLC activities by
using WeChat as belonging to the same category, they will be more
likely to form trust toward the members of the YLC WeChat group. The
more college students perceived the integration of online and offline
YLC activities by using WeChat, the more confidence they will form
toward the YLC WeChat members. Based on the extant studies [29,41],
we can hypothesize that:
H2b. Trust will positively affect the intention to share comments.
2.2.3. Perceived similarity
As a vital characteristic of the cognitive dimension of social capital,
perceived similarity refers to shared goals, values, or experiences that
one perceives with other members [17]. In virtual communities, WeChat has been increasingly chosen by college students as a social media
platform for seeking information and sharing comments among students with similar goals, value, or experiences. In the present study, the
more similarity between students, the more likely they will see YLC
activities information of interest, thus their motivation to seek such
information will enhance. The association between perceived similarity
and user behaviors has been validated by the extant literature [17,28].
For instance, Zhao, Lu, Wang, Chau, and Zhang [17] found that perceived similarity has an indirect influence on the intention to get
knowledge through a sense of belonging. Based on the extant literature
[17,28], we hypothesize that:
H4b. Perceived integration by using WeChat will positively affect trust.
H3a. Perceived similarity will positively affect the intention to seek
information.
The categorization theory proposed that people rely on similarity to
group objects into categories [29]. It is expected that perceived integration will also have positive influence on perceived similarity. In
the context of our study, when students classify the members who take
part in online or offline YLC activities as belonging to the same category, they will be more likely to form the similarities among the YLC
members. In other words, by using WeChat in YLC activities, students’
online and offline social lives become integrated, which increases the
likelihood that shared perceptions of experiences, values, and common
targets among YLC members can be developed [17]. Indeed, students
who communicate and interact with the YLC WeChat members tend to
share common goals and interests with each other, which will lead to
the similarity perceptions among the YLC WeChat members. Thus, we
hypothesize that:
It is expected that perceived similarity will also have a positive influence on the intention to share comments [40]. Indeed, the relationship between perceived similarity and user behaviors has been
validated by previous research [17,40]. Zhao, Lu, Wang, Chau, and
Zhang [17] revealed that perceived similarity has an indirect impact on
the intention to share knowledge through a sense of belonging. In the
context of the present study, students will be more likely to share
comments through WeChat moments if they perceived more similarities
to WeChat members in YLC activities. For instance, college students can
enhance their impression among members through their WeChat contents, which can provide a platform of sharing their common experiences and interests. The more college students share with each other
their values and goals, the more confidence he or she acquires to share
comments in YLC activities. Following the existing studies [17,40], we
hypothesize that:
H4c. Perceived integration by using WeChat will positively affect
perceived similarity.
H3b. Perceived similarity will positively affect the intention to share
comments.
3. Methodology
3.1. Instrument
2.2.4. Perceived integration by using WeChat
As one of the world’s most popular mobile social media, WeChat
public platform (https://mp.weixin.qq.com) provides users with three
service models: the service account, the subscription account, and the
business account. College students often pay more attention to the
subscription account, which provides useful information and resource
services from other WeChat members. When college students have no
time to participate in offline activities, they can participate in online
activities by seeking information and sharing comments through
WeChat moments or WeChat public accounts, which is beneficial for
college members who need frequent communications. Mobile social
To ensure the validity of the instrument, all the items selected to
measure the constructs were adapted from the scales of well-established
studies. We borrowed items of social interaction ties from Chiu et al.
(2006) and Wang and Wang (2013). The items of trust were adapted
from Chiu et al. (2006) and Zhao et al. (2012). The items of perceived
similarity were adapted from Zhao et al. (2012). The items of intention
to seek information were adapted from Ridings et al. (2002) and Zhao
et al. (2012). The items of intention to share comments were borrowed
from Ridings et al. (2002). The items of perceived integration by using
WeChat were borrowed from Yang et al. (2016). The questionnaire was
4
Information & Management 58 (2021) 103280
X. Chen, et al.
investigated using the 5-point Likert scale ranging from 1 (strongly
disagree) to 5 (strongly agree). A back-to-back translation was conducted to ensure there were no differences between the Chinese and
English versions of the instrument. The final versions of the scales are
presented in Appendix A.
Table 2
Scale Properties.
Factor
Item
Standardized
Loading
Cronbach’s
Alpha
CR
AVE
Social interaction ties
(SIT)
SIT2
SIT3
SIT4
TR1
TR2
TR3
TR4
PS1
PS2
PS3
PS4
SIN1
SIN2
SIN3
SIN4
SHC1
SHC2
SHC3
SHC4
PEI1
PEI2
PEI3
PEI4
0.843
0.903
0.836
0.852
0.866
0.872
0.888
0.897
0.903
0.888
0.887
0.912
0.883
0.880
0.908
0.872
0.888
0.872
0.874
0.867
0.879
0.913
0.909
0.825
0.896
0.741
0.893
0.925
0.756
0.916
0.940
0.799
0.918
0.942
0.803
0.904
0.933
0.777
0.915
0.940
0.796
3.2. Sample
Trust (TR)
Our target population was college students who used WeChat for
YLC activities. We used a convenience sample of students in a university
located in eastern China. The empirical data for the present study were
collected through a web-based survey, which was hosted through a
leading online survey site (www.wjx.cn). As the objective of our study
is to examine college students’ WeChat usages for seeking information
and sharing comments in the YLC activities, the target participants must
have certain experiences of using WeChat for YLC activities. A survey
hyperlink was placed on the WeChat public accounts of the YLC at a
university located in eastern China. Subjects were provided with a small
amount of WeChat Lucky Money to encourage their participation. After
2 weeks’ deployment, 518 valid responses were received after discarding the invalid answers such as same answers for all questions (like
all 3 or all 5), and those who did not have WeChat experiences in YLC
activities. Table 1 shows the detailed descriptive statistics. The sample
was composed of 42.7 percent male and 57.3 percent female subjects.
Perceived similarity
(PS)
Intention to seek
information (SIN)
Intention to share
comments (SHC)
Perceived Integration
by using WeChat
(PEI)
4. Data analysis
Table 3
Interconstruct Correlations and square roots of the AVEa.
4.1. Scale validation
PS
SIN
PEI
SHC
SIT
TR
Following the two-step approach advocated by Anderson and
Gerbing [42], the present study first examines the measurement model
for reliability and validity, and then tests the structural model for establishing the significance of hypotheses.
The confirmative factor analysis was conducted to assess the construct validity of six scales (social interaction ties, trust, perceived similarity, seeking information, sharing comments, and perceived integration by using WeChat). As shown in Table 2, the Cronbach’s alphas
and composite reliabilities were above 0.7, which meant good reliabilities of the scales [43]. The average variance extracted (AVE) values
of each construct were above 0.5, which meant a good convergent
validity of the scales [44].
In Table 3, we tested the discriminant validities with the guidelines
provided by Bagozzi [45]. The square roots of the AVEs had to be
greater than the correlation coefficients with the other constructs in the
model, which meant good discriminant validity. The details are shown
in Table 3, which indicates good discriminant validity. Appendix B
shows the correlation matrix. The internal loadings of every obvious
factor were larger than other cross-loading factors, which show a clear
matrix.
PEI
SHC
SIT
TR
0.894
0.563
0.397
0.511
0.384
0.550
0.896
0.470
0.729
0.338
0.387
0.892
0.498
0.436
0.385
0.881
0.361
0.338
0.861
0.371
0.869
Because self-reported data were used in this study, a common
method bias might have existed. We chose two methods to examine the
bias. First, Harman’s single-factor test was used in our proposed model
[46]. In Appendix B, we knew the largest variance was 14,427 percent,
which meant that there was no single factor that could explain the
majority of the covariance in our model [46]. Second, we compared the
items as indicators on a common method factor in a new developed
model with the original one [47]. The results showed that the loadings
of the common method were all insignificant. From the above, we
concluded that the bias in our research could be ignored.
4.2. Model testing
Measure
Item
Count (N = 518)
Percentage
Gender
Male
Female
Freshman
Sophomore
Junior
Senior
Postgraduate
Others
Less than 1 h
1 to 3 h
3 to 5 h
5 to 10 h
More than 10 h
221
297
201
140
88
72
10
7
10
146
225
110
27
42.7 %
57.3 %
38.8 %
27.0 %
17.0 %
13.9 %
1.9 %
1.4 %
1.9 %
28.2 %
43.4 %
21.2 %
5.2 %
Mobile Internet per day
SIN
*Note: SIT = Social interaction ties; TR = Trust; PS = Perceived similarity;
SIN = Intention to seek information; SHC = Intention to share comments;
PEI = Perceived integration by using WeChat.
a
Diagonal elements are the square root of AVE. These values should surpass
the interconstruct correlations for adequate discriminant validity.
Table 1
Sample Demographics.
Grades
PS
We selected Smart PLS 3.0 to test the research model and the corresponding hypotheses. It has the ability to handle both reflective and
formative constructs [48]. In addition, PLS is the preferred tool for
studies with the aim for theory development and prediction [49].
Considering the predicting nature and the nonnormal distribution data
of our study, PLS is thus more suitable for model estimating in our
study.
As shown in Fig. 2, most of the proposed hypotheses are validated
by data. Specifically, the hypothesized paths from social interaction ties
on seeking information and sharing comments are both significant, thus
hypotheses H1a and H1b are validated. However, impacts of trust on
both seeking information and sharing comments are not significant,
5
Information & Management 58 (2021) 103280
X. Chen, et al.
Fig. 2. The results of the research model.
and sharing comments in YLC activities. This is consistent with the
findings of Che and Cao [13] and Cheung, Liu and Lee [34]. This
suggests that social interaction tie plays an important role in determining college students’ WeChat usage in YLC activities. Specifically,
in terms of path coefficients and significant levels, the social interaction
tie has a stronger influence on sharing comments than that on seeking
information. This implies that the more social interaction ties that
students build, the more chances they will have to share comments with
the WeChat group.
Second, consistent with the findings from Zhao, Lu, Wang, Chau,
and Zhang [17], the present study also found that perceived similarity
positively affects students’ WeChat usage for seeking information and
sharing comments in YLC activities. Specifically, in terms of the path
coefficients and significant levels, perceived similarity exerts a relatively stronger impact on seeking information when compared with
sharing comments. This suggests that the more common goals and interests WeChat members share among themselves, the more likely they
are to obtain information from the WeChat group. However, impacts of
trust on seeking information and sharing comments were found to be
insignificant. The potential explanation is that WeChat users in YLC
activities are all schoolmates, and they are usually familiar with each
other. Indeed, Che and Cao [13] also argued that Chinese users always
have full confidence in the veracity of comments that are posted by the
members in the same group. This suggests that the trust among the YLC
WeChat group is very high. Therefore, trust may not be a vital signal
that affects the information seeking and comments sharing in the YLC
WeChat group.
Third, the present study found that perceived integration by using
WeChat positively affects 3 dimensions of social capital including social
interaction ties, trust, and perceived similarity. This suggests that the
usage of WeChat in YLC activities effectively bridges college students’
online and offline activities, which will further affect their social capital. The findings are in line with the research from Yang, Liu, and Wei
[22]. In terms of the path coefficients and significant levels, perceived
integration by using WeChat exerts the strongest impact on social interaction ties, followed by perceived similarity and trust. This implies
that students will be more likely to build social interaction relationships
with YLC members when they perceive a high-level of integration between online and offline YLC activities. In addition, the frequent interaction between YLC members by using WeChat will result in high
similarity of goals and interests among YLC members. Indeed, the
present study also found that perceived integration exerts an indirect
influence on seeking information and sharing comments through social
interaction ties and perceived similarity. This further emphasized the
important role of perceived integration on shaping college students’
WeChat usages for seeking information and sharing comments in YLC
activities. By using WeChat, students can not only meet new friends
online but can also keep in touch with their offline friends, which will
therefore hypotheses H2a and H2b are not supported. The influences of
perceived similarity on seeking information and sharing comments are
both significant at P < 0.001 level, thus hypotheses H3a and H3b are
validated. The hypothesized paths from perceived integration by using
WeChat on social interaction ties, trust, and perceived similarity are all
significant at P < 0.001 level, therefore hypotheses H4a, H4b, and H4c
are validated. The R-square values for information seeking and comment sharing are 33.8 % and 29 %, respectively.
To further test the mediating effects of social capital on relationships between perceived integration and participation behaviors, we
conducted a multiple mediator analysis to examine the indirect influences by using the SEM method [50]. As displayed in Table 4, the social
interaction ties and perceived similarity partially mediated the impacts
of perceived integration on both seeking information and sharing
comments.
5. Discussion
Drawing on the social capital theory and prior studies related to
perceived integration, the present study investigates how perceived
integration influences 3 social capital factors (e.g., social interaction tie,
trust, and perceived similarity), which may further affect their WeChat
usage for seeking information and sharing comments in the YLC
WeChat group. The main findings are discussed as follows.
First, the present study found that the social interaction tie positively affects college students’ WeChat usage for seeking information
Table 4
Results of Mediating Effects.
PEI - > SIN
PEI - > SIT
SIT - > SIN
PEI - > TR
TR - > SIN
PEI - > PS
PS - > SIN
PEI - > SHC
PEI - > SIT
SIT - > SHC
PEI - > TR
TR - > SHC
PEI - > PS
PS - > SHC
Sample Mean
(M)
Standard Error
(STERR)
T Statistics
0.2778
0.4381
0.1398
0.3852
0.0861
0.3974
0.4668
0.2670
0.4381
0.1868
0.3852
0.0413
0.3974
0.4191
0.0505
0.0631
0.0610
0.0627
0.0613
0.0638
0.0643
0.0500
0.0671
0.0595
0.0627
0.0690
0.0638
0.0804
6.2238
7.0715
2.1020
6.1286
1.3390
6.2238
7.2836
5.2463
7.0715
3.1238
6.1286
0.5699
6.2238
5.2017
Sobel Z
2.1171
1.3415
4.7214
2.6039
0.6542
3.9496
* Note: SIT = Social interaction ties; TR = Trust; PS = Perceived similarity;
SIN = Intention to seek information; SHC = Intention to share comments;
PEI = Perceived integration by using WeChat. The sample mean, standard
error, and T-value were determined using the bootstrapping procedure.
6
Information & Management 58 (2021) 103280
X. Chen, et al.
on the determinants in an online channel environment. The present
study investigated the factors that affect college students’ WeChat usage
behaviors in YLC activities from an online and offline integration perspective. Results demonstrated that perceived integration using WeChat
positively affects the college students’ social capital and their participation behaviors in YLC activities. This emphasized the important roles
of perceived integration by using WeChat in shaping college students’
participation behaviors in YLC activities. Our study thus provides a
better theoretical understanding of students’ WeChat usage behaviors in
the multichannel perspective.
From the practical perspective, results of this study provide useful
implications for managing YLC activities. First, the present study found
that social interaction ties positively influence students’ WeChat usage
for seeking information and sharing comments in YLC activities. The
implication for managers of YLC activities is clear: they should exert
substantial effort to enhance students’ social interaction ties. For instance, they can provide social interaction components such as like,
forward, comments, and barrage through the WeChat platform, which
will help to increase YLC WeChat members’ social interaction ties.
Second, we found that perceived similarity has a positive effect on
students’ WeChat usage for YLC activities. The implication for managers
of YLC activities is straightforward: they should take measures to increase students’ similarity perceptions. For example, they can make
topics in WeChat moments or WeChat public accounts more focused, so
that students with similar goals and interests can easily find each other.
Finally, managers of YLC activities should emphasize the integration
perceptions between offline and online YLC activities by using WeChat
because we found that perception integration positively affects all 3
social capital factors. For instance, they can provide live broadcast of
offline YLC activities through WeChat platforms. In this way, they can
encourage students using WeChat to interact with other YLC members
when students are taking part in offline YLC activities. On the other
hand, when students cannot take part in offline YLC activities, they can
participate in the activities online by using WeChat.
further strengthen the trust among students.
5.1. Limitations
The present study has a few limitations. First, as the test bed of our
study is WeChat usages for YLC activities in education settings, social
interaction ties, trust, and perceived similarity were operationalized as
the structural, relational, and cognitive dimensions of social capital,
respectively. However, other social factors such as the norm of reciprocity may also have potential impacts on students’ WeChat usage
for YLC activities. Thus, future studies are encouraged to include the
norm of reciprocity to further examine WeChat usage behaviors.
Second, to faithfully capture impacts of social capital on WeChat usage
behaviors (seeking information and sharing comments), an ideal research design is a longitudinal analysis over different periods. However,
the data collected in our study restrict this analysis. Future studies thus
could examine WeChat usage behaviors using a longitudinal analysis.
Third, it is also worth noting that data of this study were collected from
students of a university in China. While focusing on students of a particular university can minimize the unexplained variance in the data
set, such a narrow focus may lead to the generalizability issues of our
results. Future studies can therefore further examine and validate our
findings at different universities in different country contexts.
5.2. Implications
This study has both theoretical and practical implications. From the
theoretical perspective, the present study developed and validated a
research model of WeChat usage in YLC activities by addressing the
benefits of WeChat uses beyond the traditional organization contexts.
The results of our study indicated that the usage of WeChat can promote
college students’ YLC participation behaviors by stimulating their integration perceptions and enhancing their social capital. The present
study thus provided a valuable insight in understanding college students’ WeChat uses in YLC activities.
Second, previous studies tend to explore users’ participation behaviors by focusing on contributors’ behaviors [12]. The present study
investigated college students’ participation behaviors in YLC activities
by considering both seeking information and sharing comments behaviors. The results indicated that both seeking information and sharing
comments behaviors should be taken into consideration to explain
college students’ YLC participation behaviors. This suggests that a
narrow focus on one of the two behaviors would not fully explain
college students’ YLC participation behaviors. The present study thus
offers a more holistic insight to understand students’ participation behaviors in the education environment than prior research.
Finally, extant studies examined WeChat usage that mainly focused
Funding
This research was funded by the National Natural Science
Foundation of China, grant number71472163, 71704153.
CRediT authorship contribution statement
Xiaofang Chen: Data curation, Writing - original draft,
Investigation. Jianqing Ma: Investigation, Supervision. June Wei:
Writing - review & editing. Shuiqing Yang: Conceptualization,
Methodology, Validation.
Appendix A. The scales
Structural dimension：Social interaction ties (Chiu, Hsu and Wang, 2006, Wang and Wang, 2013)
SIT1. WeChat provides different ways to communicate with others in YLC activities. Dropped.
SIT 2. I maintain close social relationships with some members in WeChat when taking part in some YLC activities, in both online and offline
contexts.
SIT 3. I spend a lot of time interacting with some members in WeChat when taking part in some YLC activities, in both online and offline contexts.
SIT 4. I have frequent communication with some members in WeChat when taking part in some YLC activities in both online and offline contexts.
Relational dimension: Trust (Chiu, Hsu and Wang, 2006, Zhao, Lu, Wang, Chau and Zhang, 2012)
TR1. I feel members of the YLC WeChat group are trustworthy.
TR2. The participants in the YLC WeChat group will do everything within their capacity to help others.
TR3. The participants in the YLC WeChat group behave in a consistent manner.
TR4. The participants in the YLC WeChat group will always keep promises they make to one another.
Cognitive dimension: perceived similarity (Zhao, Lu, Wang, Chau and Zhang, 2012)
PS1: I feel members in the YLC WeChat group have common goals.
PS2: I feel members in the YLC WeChat group have interests similar to mine.
PS3: I feel members in the YLC WeChat group have values similar to mine.
PS4: I feel members in the YLC WeChat group have experiences similar to mine.
7
Information & Management 58 (2021) 103280
X. Chen, et al.
Intention to seek information (Ridings, Gefen and Arinze, 2002, Zhao, Lu, Wang, Chau and Zhang, 2012)
SIN1: I intend to come to the YLC WeChat group to seek related information, when I need to know other people’s views about our university
services.
SIN2: I will consider coming to the YLC WeChat group to seek related information when I need to know news and activities of our university.
SIN3: I come to the YLC WeChat group when I need facts about a particular subject in our university.
SIN4: I come to the YLC WeChat group to get information on a particular topic in our university.
Intention to share comments (Ridings, Gefen and Arinze, 2002)
SHC1: I’d like to share my commentary with other members of the YLC WeChat group.
SHC2: I intend to share my views with other members of the YLC WeChat group.
SHC3: I will try to share my perspectives with other members of the YLC WeChat group.
SHC4: I’d like to give advising information to other members of the YLC WeChat group.
Perceived integration by using WeChat (Yang, Liu and Wei, 2016)
PEI1. WeChat allows me to keep in touch with my online community members, while I participate in offline YLC activities.
PEI2: WeChat allows me to instantly respond to my online community members, when I participate in the offline YLC activities.
PEI3: WeChat effectively mitigated the conflicts between my online and offline YLC activities.
PEI4: WeChat effectively integrated my online and offline YLC activities.
Appendix B. Loadings and cross loading for reflective measures
Factor
PEI1
PEI2
PEI3
PEI4
PS1
PS2
PS3
PS4
SHC1
SHC2
SHC3
SHC4
TR1
TR2
TR3
TR4
SIN1
SIN2
SIN3
SIN4
SIT2
SIT3
SIT4
Eigen-values
Variance %
Cumulative
PEI
0.779
0.829
0.861
0.840
0.144
0.102
0.164
0.118
0.181
0.262
0.044
0.231
0.134
0.216
0.188
0.256
0.202
0.147
0.057
0.132
0.114
0.165
0.246
3.318
14.427
14.427
PS
0.150
0.081
0.130
0.124
0.761
0.839
0.810
0.789
0.252
0.145
0.290
0.186
0.230
0.151
0.210
0.126
0.195
0.262
0.188
0.184
0.117
0.198
0.062
3.197
13.898
28.325
TR
0.207
0.163
0.133
0.191
0.209
0.158
0.160
0.175
0.279
0.303
0.372
0.369
0.777
0.784
0.748
0.783
0.017
0.113
0.084
0.138
0.150
0.095
0.080
3.161
13.741
42.066
SIN
0.150
0.118
0.144
0.136
0.237
0.244
0.239
0.231
0.162
0.107
0.133
0.132
0.054
0.106
0.136
0.102
0.790
0.795
0.846
0.824
0.076
0.181
0.157
3.131
13.612
55.678
SHC
0.133
0.175
0.109
0.167
0.260
0.150
0.152
0.210
0.787
0.784
0.723
0.765
0.300
0.306
0.264
0.287
0.075
0.064
0.134
0.147
0.091
0.066
0.109
2.995
13.023
68.701
SIT
0.155
0.144
0.169
0.147
0.146
0.110
0.111
0.130
0.112
0.090
0.109
0.087
0.154
0.099
0.149
0.054
0.167
0.094
0.092
0.120
0.828
0.843
0.755
2.282
9.923
78.624
Note: SIT = Social interaction ties; TR = Trust; PS = Perceived similarity; SIN = Intention to seek information; SHC = Intention to share
comments; PEI = Perceived integration by using WeChat.
Appendix C. Supplementary data
Supplementary material related to this article can be found, in the online version, at doi:https://doi.org/10.1016/j.im.2020.103280.
[8] B.D. Christens, T. Dolan, Interweaving youth development, community development, and social change through youth organizing, Youth Soc. 43 (2011) 528–548.
[9] S. Verba, K.L. Schlozman, H.E. Brady, Voice and Equality: Civic Voluntarism in
American Politics, Harvard University Press, 1995.
[10] S. Mousavi, S. Roper, K.A. Keeling, Interpreting social identity in online brand
communities: considering posters and lurkers, Psychol. Mark. 34 (2017) 376–393.
[11] C. Gan, Understanding WeChat users’ liking behavior: an empirical study in China,
Comput. Human Behav. 68 (2017) 30–39.
[12] Chin Lung Hsu, J. Lin, Chuanchuan, Acceptance of blog usage: The roles of technology acceptance, social influence and knowledge sharing motivation, Inf. Manag.
45 (2008) 65–74.
[13] H.L. Che, Y. Cao, Examining WeChat users’ motivations, trust, attitudes, and positive word-of-mouth: evidence from China, Comput. Human Behav. 41 (2014)
104–111.
[14] C.-M. Chiu, M.-H. Hsu, E.T. Wang, Understanding knowledge sharing in virtual
communities: an integration of social capital and social cognitive theories, Decis.
Support Syst. 42 (2006) 1872–1888.
[15] E.S.-T. Wang, M.C.-H. Wang, Social support and social interaction ties on internet
References
[1] CNNIC, 43th Statistical Survey Report on Internet Development in China. [R/OL].
(2019-02-28) [2019-5-02], (2019) http://www.cnnic.net.cn/.
[2] Tencent, WeChat Data Report, [R/OL], (2018-03-05), [2018-11-6], (2018) https://
www.sohu.com/a/224849404_519996.
[3] C. Gan, A survey of WeChat application in Chinese public libraries, Libr. Hi Tech 34
(2016) 625–638.
[4] R. Ghiselli, J. Ma, Restaurant social media usage in China: a study of industry
practices and consumer preferences, Worldw. Hosp. Tour. Themes 7 (2015)
251–265.
[5] W.H.S. Tsai, R.L. Men, Social messengers as the new frontier of organization-public
engagement: a WeChat study, Public Relat. Rev. 44 (2018) 419–429.
[6] Z. Sun, R. Liu, L. Luo, M. Wu, C. Shi, Exploring collaborative learning effect in
blended learning environments, J. Comput. Assist. Learn. 33 (2017) 575–587.
[7] J. Chen, Can online social networks foster young adults’ civic engagement?
Telemat. Inform. 34 (2017) 487–497.
8
Information & Management 58 (2021) 103280
X. Chen, et al.
[16]
[17]
[18]
[19]
[20]
[21]
[22]
[23]
[24]
[25]
[26]
[27]
[28]
[29]
[30]
[31]
[32]
[33]
[34]
[35]
[36]
[37]
[38] M.H. Hsu, T.L. Ju, C.H. Yen, C.M. Chang, Knowledge sharing behavior in virtual
communities: the relationship between trust, self-efficacy, and outcome expectations, Int. J. Hum. Stud. 65 (2007) 153–169.
[39] Y. Zhang, Y. Fang, K.K. Wei, H. Chen, Exploring the role of psychological safety in
promoting the intention to continue sharing knowledge in virtual communities, Int.
J. Inf. Manage. 30 (2010) 425–436.
[40] C. Ziegler, J. Golbeck, Investigating interactions of trust and interest similarity,
Decis. Support Syst. 43 (2007) 460–475.
[41] K.J. Stewart, Trust transfer on the world wide web, Organ. Sci. 14 (2003) 5–17.
[42] J. Anderson, D. Gerbing, Structural equation modeling in practice: a review and
recommended two-step approach, Psychol. Bull. 103 (1988) 411–423.
[43] J.C. Nunally, Psychometric Theory, 2nd ed., McGraw-Hill, New York, 1978.
[44] R.P. Bagozzi, Y. Yi, On the evaluation of structural equation models, J. Acad. Mark.
Sci. 16 (1988) 74–94.
[45] R.P. Bagozzi, Evaluating structural equation models with unobservable variables
and measurement error: a comment, J. Mark. Res. 18 (1981) 375–381.
[46] P.M. Podsakoff, D.W. Organ, Self-reports in organizational research: problems and
prospects, J. Manage. 12 (1986) 531–544.
[47] H.G. Liang, N. Saraf, Q. Hu, Y.J. Xue, Assimilation of enterprise systems: the effect
of institutional pressures and the mediating role of top management, Mis Q. 31
(2007) 59–87.
[48] W.W. Chin, The Partial Least Squares Approach for Structural Equation Modeling,
295, (1998), pp. 295–336.
[49] J.F. Hair, Multivariate data analysis: pearson new international edition, Pearson
Schweiz Ag 3 (2013) 128–134.
[50] K.J. Preacher, A.F. Hayes, Asymptotic and resampling strategies for assessing and
comparing indirect effects in multiple mediator models, Behav. Res. Methods 40
(2008) 879–891.
addiction: integrating online and offline contexts, cyberpsychology, behavior, Soc.
Netw. 16 (2013) 843–849.
C.M. Ridings, D. Gefen, B. Arinze, Some antecedents and effects of trust in virtual
communities, J. Strateg. Inf. Syst. 11 (2002) 271–295.
L. Zhao, Y. Lu, B. Wang, P.Y.K. Chau, L. Zhang, Cultivating the sense of belonging
and motivating user participation in virtual communities: a social capital perspective, Int. J. Inf. Manage. 32 (2012) 574–588.
J. Nahapiet, S. Ghoshal, Social capital, intellectual capital and the creation of value
in firms, Academy of Management Annual Meeting Proceedings 1997 (1997)
35–39.
R.D. Putnam, Tuning In, Tuning Out, The strange disappearance of social capital in
America, PS Polit. Sci. Polit. 28 (1995) 664–683.
T. Zhou, Y. Lu, B. Wang, K.-K. Wei, Explaining mobile community user participation
from a social capital perspective, Int. J. Mob. Commun. 8 (2010) 278–296.
J. Nahapiet, S. Ghoshal, Social capital, intellectual capital, and the organizational
advantage, Knowledge & Social Capital 23 (2000) 119–157.
S. Yang, Y. Liu, J. Wei, Social capital on mobile SNS addiction: a perspective from
online and offline channel integrations, Internet Res. 26 (2016) 982–1000.
J. Nahapiet, S. Ghoshal, Social capital, intellectual capital, and the organizational
advantage, Acad. Manag. Rev. 23 (1998) 242–266.
S.T. Wang, S.L. Chen, Forming relationship commitments to online communities:
the role of social motivations, Elsevier Science Publishers B. V. (2012).
C.B. Zhang, Y.N. Li, B. Wu, D.J. Li, How WeChat can retain users: roles of network
externalities, social interaction ties, and perceived values in building continuance
intention, Comput. Human Behav. 69 (2017) 284–293.
D.D. Gremler, K.P. Gwinner, S.W. Brown, Generating positive word-of-mouth
communication through customer-employee relationships, Int. J. Serv. Ind. Manag.
12 (2001) 44–59.
K. Rong, D. Secchi, Y.Y. Shou, Culture, trust and business ecosystems: the mediating
role of online chat in China, Int. J. Mob. Commun. 16 (2018) 247–265.
S. Fu, Q. Yan, G.C. Feng, Who will attract you? Similarity effect among users on
online purchase intention of movie tickets in the social shopping context, Int. J. Inf.
Manage. 40 (2018) 88–102.
J. Ozanne, M. Brucks, D. Grewal, A study of information search behavior during the
categorization of new products, J. Consum. Res. 18 (1992) 452–463.
J.E. Escalas, J.R. Bettman, Self-construal, reference groups, and brand meaning, J.
Consum. Res. 32 (2005) 378–389.
L.-B. Oh, H.-H. Teo, V. Sambamurthy, The effects of retail channel integration
through the use of information technologies on firm performance, J. Oper. Manag.
30 (2012) 368–381.
M.S. Granovetter, The strength of weak ties, Am. J. Sociol. (1973) 1360–1380.
Y.-C. Chen, J.-H. Wu, L. Peng, R.C. Yeh, Consumer benefit creation in online group
buying: the social capital and platform synergy effect and the mediating role of
participation, Electron. Commer. Res. Appl. 14 (2015) 499–513.
C.M.K. Cheung, I.L.B. Liu, M.K.O. Lee, How online social interactions influence
customer information contribution behavior in online social shopping communities:
a social learning theory perspective, J. Assoc. Inf. Sci. Technol. 66 (2015)
2511–2521.
J.B. Rotter, A new scale for the measurement of interpersonal trust, J. Pers. 35
(1967) 651–665.
M. Jaradat, A.A. Moustafa, A.M. Al-Mashaqba, Exploring perceived risk, perceived
trust, perceived quality and the innovative characteristics in the adoption of smart
government services in Jordan, Int. J. Mob. Commun. 16 (2018) 399–439.
L.W. Hwa, L.C. Wen, S.K. Heng, A technology acceptance model for the perception
of restaurant service robots for trust, interactivity, and output quality, Int. J. Mob.
Commun. 16 (2018) 361–376.
Xiaofeng Chen is an assistant professor in the School of Information at Zhejiang
University of Finance and Economics. She is a pH.D. candidate of the School of Marxism,
Zhejiang University, China. Her research interests include mobile learning adoption, high
education, and related topics.
Jianqing Ma is a professor in the School of Marxism at Zhejiang University, China. His
research interests include psychology, high education, network psychological education,
and related topics.
Dr. June Wei is a professor in the Department of Management and Management
Information Systems at the University of West Florida. She earned a pH.D. from Purdue
University and a Master’s degree from Georgia Institute of Technology and another
Master’s degree from Zhejiang University. She has over 180 publications including papers
in referral journals such as Computers in Human Behavior, Electronic Commerce Research,
Behavior and Information Technology, and among others. She has many years of industry
working experiences and is currently serving as the Editor-in-Chief for 2 referral international journals.
Shuiqing Yang is an associate professor in the School of Information at Zhejiang
University of Finance and Economics. He received his pH.D. from the Huazhong
University of Science and technology in 2012. His research focuses on electronic and
mobile business and technology adoption. His research has been published in Decision
Support Systems, Information & management, Computers in Human Behavior, International
Journal of Mobile Communications, Internet Research, International Journal of HumanComputer Interaction, Journal of Business and Industrial Marketing, among others.
9