Academics’ Intention to Adopt SNS for Engagement Within Academia
Eleni Dermentzi, Savvas Papagiannidis, Carlos Osorio and Natalia Yannopoulou
Newcastle University Business School, Newcastle University, 5 Barrack Road, Newcastle Upon Tyne, U.K.
Keywords: Academics, Social Media, Academic Engagement, Social Networking Sites, Theory of Planned Behaviour,
Gratifications Theory.
Abstract: Although Social Networking Sites (SNS) have become popular among scholars as tools for engagement
within academia, there is still a need to examine the motives behind academics’ intentions to adopt SNS. This
study proposes and tests a research model based on the Decomposed Theory of Planned Behaviour and
Gratifications Theory with a sample of 370 academics around the world in order to address the objective set.
Our findings suggest that while attitude and perceived behavioural control are the main drivers of academics’
intentions to adopt SNS for engagement, the effect of social norms on intentions is not significant. In addition,
networking needs, perceived usefulness, image, and perceived reciprocity affect attitude, while self-efficacy
affects perceived behavioural control. Implications for SNS providers and universities that want to promote
and encourage online engagement within their faculties are discussed.
Online or internet technologies have long been
established as communication and collaboration tools
in academia (Veletsianos and Kimmons, 2012). More
specifically, when it comes to networking and
information sharing, a specific type of online
technology has prevailed over the past few years:
Social Networking Sites (SNS). SNS have been
defined as “web-based services that allow individuals
to (1) construct a public or semi-public profile within
a bounded system, (2) articulate a list of other users
with whom they share a connection, and (3) view and
traverse their list of connections and those made by
others within the system” (Boyd and Ellison, 2007).
Although many of them have not been created for
professional purposes, research has shown that
scholars employ them as professional tools that can
be used beyond instructional purposes (Veletsianos,
2012). SNS can facilitate the creation of social capital
in academia (Madhusudhan, 2012; Richter, 2011) and
make Networked Participatory Scholarship feasible,
which is “the practice of scholars’ use of
participatory technologies and online social
networks to share, reflect upon, critique, improve,
validate, and further their scholarship” (Veletsianos
and Kimmons, 2012). Most importantly, SNS can
help both academics and institutions increase
community outreach, and facilitate their efforts to
create impact on society and their effectiveness in
accomplishing their goals (Forkosh-Baruch and
Hershkovitz, 2012; Veletsianos and Kimmons, 2013).
Due to the significant benefits that SNS can
potentially offer in an academic context, scholars
have begun to examine the use of SNS for academic
purposes more systematically (e.g. Gruzd, Staves, &
Wilk, 2012; Veletsianos and Kimmons, 2012).
However, so far research has focused exclusively on
answering “how” SNS can change academic practice
and “what” the academics’ usage patterns are
(Forkosh-Baruch and Hershkovitz, 2012;
Madhusudhan, 2012; Van Noorden, 2014;
Veletsianos, 2012; Veletsianos and Kimmons, 2012;
Veletsianos and Kimmons, 2013). Our work builds on
this emerging body of research, extending it by
focusing on “why” scholars participate in SNS. To the
best of our knowledge this is the first scholarly article
that attempts to understand the motivating factors that
drive academics to adopt SNS by following a
quantitative approach. Related literature has been of
an exploratory nature so far, using qualitative
approaches (Gruzd, Staves, & Wilk, 2012; Lupton,
2014). In addition, current research is based entirely
upon the views of the actual users of SNS, ignoring
the attitudes of a great number of academics that do
not use SNS. Based on the above, the overall
objective of this paper is to study the academic use of
SNS for engagement, taking into consideration both
Dermentzi, E., Papagiannidis, S., Osorio, C. and Yannopoulou, N.
Academics’ Intention to Adopt SNS for Engagement Within Academia.
In Proceedings of the 12th International Conference on Web Information Systems and Technologies (WEBIST 2016) - Volume 1, pages 219-228
ISBN: 978-989-758-186-1
2016 by SCITEPRESS Science and Technology Publications, Lda. All rights reserved
users and non-users of SNS. In order to address our
objective, we synthesise and apply the Decomposed
Theory of Planned Behaviour (Decomposed TPB)
and Uses and Gratifications Theory, proposing a
conceptual model that aims to determine the factors
that affect academics’ intention to use SNS in order
to disseminate their research and engage with their
This paper is organised in the following way:
Firstly, we review the related literature and build our
research model. Then, we present our methodology
and the results of our data analysis. Discussion of the
results follows and the paper concludes with a
summary of our results and their implications, the
limitations of our study and directions for future
2.1 Theoretical Framework
The Decomposed TPB is an alternative version of the
TPB model proposed by Ajzen (1991). According to
the TPB model, human behaviour is affected by three
factors: a) attitude towards behaviour, b) subjective
or social norm, which is the perceived social pressure,
and c) perceived behavioural control, which is “the
perceived ease or difficulty of performing the
behaviour”. These three factors lead to the
development of behavioural intention (Ajzen,
2002b). In the Decomposed TPB, the three factors are
analysed further by taking apart the various
dimensions that comprise them. Consequently, the
Decomposed TPB provides a more holistic
understanding of behavioural intentions, since the
analysis of the factors renders the relationships
among them clearer and easier to understand and
interpret (Taylor and Todd, 1995).
While the Decomposed TPB is a suitable model
for examining Information Technology (IT) usage
(Taylor and Todd, 1995), it is not specialised on new
media, such as SNS. Hence, the Uses and
Gratifications Theory, which is considered more
appropriate for understanding the uses of new media
by individuals (Foregger, 2008), is also adopted. The
theory sheds light on how individuals use
communications among other resources in order to
meet their needs and accomplish their goals. It is
based on five basic assumptions: a) the audience is
conceived of as active, b) the audience takes a great
deal of initiative in linking “need gratification” and
media choice, c) media compete with other sources of
need satisfaction, d) as far as methodology is
concerned, many of the goals related to mass media
use can be derived from data provided by the
audience itself, and e) judging the cultural
significance of mass communication should be
avoided while audience orientations are separately
explored (Katz et al., 1973).
Based on the Decomposed TPB (Taylor and Todd,
1995) and Uses and Gratifications Theory (Katz et al.,
1973), we propose a research model that investigates
how academics’ intention to use SNS in order to
engage with their peers and create impact within
academia is formed. The section that follows
examines the various factors that may affect attitude
towards behaviour, social norms, perceived
behaviour control and lastly intention.
2.2 Research Model and Development
of Hypotheses
Self- Promotion and Image: One of the needs
related to the use of media, as proposed by the Uses
and Gratifications Theory, is the need to gain insights
into one’s personal identity (Flanagin and Metzger,
2001). Web sites are regularly used for implementing
impression management strategies (i.e. strategies that
aim to control information about a person, an object,
an entity or idea) (Connolly-Ahern and Broadway,
2007). Participation in online communities has also
been connected with self- interest motives, like
seeking to enhance one’s reputation (Faraj and
Johnson, 2010). In the academic context, blogs are
often used as tools for sharing thoughts about
academic work conditions and policies and even
promoting one’s expertise by providing advice
(Mewburn and Thomson, 2013), activities that
eventually result in the creation of a virtual academic
identity. Likewise, SNS have been found to be used
by academics as tools for forming digital identity and
engaging in impression management (Veletsianos,
2012). Many academics seem to use social media in
order to increase the visibility of their research and
discuss their ideas with their colleagues (Lupton,
2014; Menendez, Angeli, & Menestrina, 2012). We
suggest that academics’ need for self-promotion,
which is the manifestation of one’s abilities or
accomplishments in order to be seen as competent by
others (Bolino and Turnley, 1999), and enhancement
of professional identity affect their attitude towards
using online technologies for engagement in a
positive way.
H1. The motive of self- promotion positively
affects academics’ attitude towards using SNS for
academic engagement.
H2. The motive of maintaining a positive image
WEBIST 2016 - 12th International Conference on Web Information Systems and Technologies
positively affects academics’ attitude towards using
SNS for academic engagement.
Information Sharing and Seeking: Knowledge
management, including information seeking and
sharing is a common motive for using online services.
According to Papacharissi and Rubin (2000),
information seeking is the most salient use of the
Internet. This is especially true for virtual
communities, with online users stating that the main
reason they visit them is the opportunity to exchange
information (Ridings and Gefen, 2004). A more
recent study has found that information seeking is a
motive for using SNS too, as users regard social
relationships as useful sources for information (Kim
et al., 2011). This is in agreement with previous
findings suggesting that information seeking is one of
the four gratifications derived from using SNS (Ku,
Chu, & Tseng, 2013). Interpersonal utility, which
takes the form of information sharing among peers, is
also considered as a motive for Internet use
(Papacharissi and Rubin, 2000). The use of SNS for
information dissemination seems to be the case in
academia, too (Lupton, 2014; Menendez et al., 2012).
More specifically, many academics use SNS in order
to keep in touch with new developments and events
and provide access to new or unpublished articles in
their research field (Lupton, 2014). Therefore, we
H3. The motive of information sharing positively
affects academics’ attitude towards using SNS for
academic engagement.
H4. The motive of information seeking positively
affects academics’ attitude towards using SNS for
academic engagement.
Networking: Studies about the use of online
communities have shown that many of the ways that
people use to communicate during face-to-face
interactions are replicated in online environments,
with online members seeking social support or
friendships by joining an online community
(Maloney-Krichmar & Preece, 2005; Ridings and
Gefen, 2004). Not surprisingly, one of the main uses
of SNS is networking in the form of maintaining old
ties and creating new ones with peers that share the
same interests (Foregger, 2008; Kim et al., 2011; Ku
et al., 2013). Academics also use SNS for connecting
and establishing networks and sometimes they even
use SNS as platforms for multi-disciplinary
collaborations (Gruzd et al., 2012; Jung and Wei,
2011; Lupton, 2014). We expect that:
H5. The motive of maintaining old contacts
positively affects academics’ attitude towards using
SNS for academic engagement.
H6. The motive of creating new contacts positively
affects academics’ attitude towards using SNS for
academic engagement.
Perceived Usefulness: Perceived usefulness has
been defined as “the degree to which a person
believes that using a particular system would enhance
his or her job performance” (Davis, 1989). According
to Taylor and Todd (1995), who tested the predictive
power of the Decomposed TPB, perceived usefulness
is significantly related to attitude. Research that
examines participation in virtual communities (Lin,
2006) has also found that the path from perceived
usefulness to attitude is significant. Online tools are
often considered useful by scholars for organising
their work and increasing their efficiency (Lupton,
2014). The above lead us to the following hypothesis:
H7. Perceived usefulness of SNS positively affects
academics’ attitude towards using SNS for academic
Perceived Trust: In this study, perceived trust
refers to the trust an individual has in the benevolence
and integrity of other online users (Lin, 2006). Trust
has been considered as a factor influencing
participation in virtual communities and social
interactions that take place in them (Chiu et al., 2006).
Lin (2006) found that perceived trust is one of the
determinants of member intentions to participate in
virtual communities. In fact, the prosperity of an
online community is based on members’ sense of
trust that the other members will treat them with
respect and care (Maloney-Krichmar and Preece,
2005). Moreover, trust has been found to play an
important role in using SNS for online political
participation. In the study of Himelboim et al. (2012),
people who reported trusting others were more likely
to use SNS for political interaction and search of
political information. Absence of trust could
discourage participation in SNS, especially when
academics are concerned about being vulnerable to
various types of attack online, including outright
aggression, hate speech or harassment (Lupton,
2014). For these reasons we propose that:
H8. Perceived trust among SNS members
positively affects academics’ attitude towards using
SNS for academic engagement.
Perceived Reciprocity: Reciprocity is a “give
and take” exchange relationship that can appear in
online environments, with the users helping each
other and rewarding kind actions. Chiu et al. (2006)
have found that there is a positive and significant
relationship between reciprocity and the quantity of
knowledge sharing in virtual communities. Likewise,
Jeon et al. (2011) have found that reciprocity has a
positive effect on members’ attitudes toward
knowledge sharing in communities of practice. Long-
Academics’ Intention to Adopt SNS for Engagement Within Academia
lasting sustainable online communities are
characterised by strong group norms of support and
reciprocity that make even externally driven
governance unnecessary (Faraj and Johnson, 2010;
Maloney-Krichmar and Preece, 2005). Giving and
receiving support is one of the perceived benefits
academics may gain by joining SNS (Lupton, 2014).
We postulate that:
H9. Perceived reciprocity in SNS positively
affects academics’ attitude towards using SNS for
academic engagement.
Peer and External Influence: As the
Decomposed TPB suggests, social norms are affected
by peer influence, which takes the form of
encouragement or opposition towards using the IT in
question (Taylor and Todd, 1995). Hsu and Chiu
(2004) have added an additional factor, namely
“external influence”, which is the influence by mass
media, experts and any other non-personal
information that could affect individuals’
considerations about performing the behaviour. The
research of Bhattacherjee (2000) confirms that
external influence is an important determinant of
social norms in IT related contexts. Academics seem
to take into consideration their colleagues’ opinion
about SNS, even if these opinions come from
academics outside their home organisation or from a
different discipline (Gruzd et al., 2012). Based on the
above, the following hypotheses are put forward:
H10. Peer influence positively affects the social
norms of academics.
H11. External influence positively affects the
social norms of academics.
Privacy Control: Privacy control involves the
ability of academics to control information about
themselves and their research in online environments.
For example, as far as SNS are concerned, privacy
control could be influenced by the privacy policy of
SNS, the awareness that information is being
collected, the voluntary character of the information
submission, and the openness of information usage by
the SNS (Xu et al., 2013). So far, privacy control has
been associated with the alleviation of privacy
concerns in SNS (Xu et al., 2013) and Internet use
(Dinev and Hart, 2003). In the case of academics,
these concerns are about privacy in general, inability
to control the content posted on social media and
copyright issues (Gruzd et al., 2012; Lupton, 2014).
Ajzen (2002b) has introduced the general notion of
controllability as the second factor that, along with
self-efficacy, comprises the perceived behavioural
control in the TPB model. We hypothesise that:
H12. Privacy control in SNS positively affects
theperceived behavioural control of academics.
Self-efficacy: In the context of online
technologies, self-efficacy refers to users’ beliefs in
their capabilities to use online technologies. Lack of
technological proficiency can be an important barrier
to knowledge sharing in online communities
(Ardichvili, 2008). The Decomposed TPB suggests
that self-efficacy is one of the determinants of
perceived behavioural control (Taylor and Todd,
1995). This notion is also supported by research in the
e-commerce field that found that self-efficacy
influences perceived behavioural control
significantly (Hung et al., 2003). Although academics
are sufficiently technologically competent since they
have to use the Internet in their academic practice
(e.g. getting access to academic journals, submitting
manuscripts through journals’ online systems etc.),
they still may feel that they have difficulties in
managing personal and professional information
when they use new online tools like SNS (Gruzd et
al., 2012). We therefore expect that:
H13. Self-efficacy related to the use of SNS
positively affects the perceived behavioural control of
Attitude, Social Norms and Perceived
Behaviour Control: According to the Decomposed
TPB (Taylor and Todd, 1995) and the original TPB
(Ajzen, 1991), behaviour is a direct function of
behavioural intention. One of the main factors that
affects behavioural intention according to Ajzen
(1991) is the attitude towards behaviour, or in other
words, whether a person is in favour of or against the
behaviour in question. Research on social networking
has shown that attitude toward social networking is
positively associated with intention to use social
networking (Peslak et al., 2011). Similarly, social (or
subjective) norms, which is the second factor that
affects behavioural intention in TPB, is found to be
positively correlated to intention in an SNS context
(Peslak et al., 2011). Finally, perceived behavioural
control has also been found to have a positive
relationship with intention in a similar context, that of
participating in virtual communities (Lin, 2006). Based
on the above, the following hypotheses are formulated:
H14. Attitude of academics towards using SNS for
academic engagement positively affects intention to
use SNS for this purpose.
H15. Social norms of academics related to using
SNS for academic engagement positively affect
intention to use SNS for this purpose.
H16. Perceived behavioural control of academics
related to using SNS for academic engagement
positively affects intention to use SNS for this
WEBIST 2016 - 12th International Conference on Web Information Systems and Technologies
For the purposes of the study a purposeful sample that
covers academics (including doctoral students) from
different disciplines, career stages and countries was
employed. In order to achieve this we used different
sampling techniques: a) we distributed the survey’s
link via social networking sites, by posting it on
groups with an academic focus and using our personal
profiles on Twitter, etc. b) we created
a random sample of 3000 academics and we sent the
survey’s link through email invitations. Since there is
no list of academics around the world, we chose
universities at random from the list of universities
around the world provided by Webometrics
( and we retrieved contact
information about random academics from
universities’ webpages. A total of 711 respondents
started the survey. After discarding the incomplete
responses and outliers, the remaining 370 valid
responses were used for our analysis. Table 1 shows
the profiles of the participants.
The online questionnaire that was used in the
study was constructed by following the main
premises of the two main theories suggested (Ajzen,
2002a; Francis et al., 2004; Katz et al., 1973). Table 2
presents the sources from which items were adapted.
4.1 Reliability and Validity
We ran both Exploratory Factor Analysis (EFA) and
Confirmatory Factor Analysis (CFA) in order to
assess the construct reliability and validity. The
Kaiser–Meyer–Olkin (KMO) and principal
component factor analysis were conducted to
examine the adequacy of the study sample and the
validity of the study instrument, respectively. After
removing some items due to poor loadings or failure
to load with the expected factor, we found that the
value of KMO was 0.943 and all the items loaded on
each distinct factor and explained 83.49% of the total
variance. The reliability of the scales was also tested
and the Cronbach’s alphas of all scales ranged between
0.741 and 0.965 (Table 2), indicating very good
Table 1: Sample Demographics (N=370).
Percent Percent
18 - 24 0.8 Europe 76.1
25 - 34 28.6 America 10.3
35 - 44 33.8 Asia 6.5
45 - 54 19.5 Australia/Oceania 6.8
55 - 64 14.6 Africa 0.3
Current Post
Discipline Group
PhD student 17.5 STEM 24.6
Post Doc/Research Associate 8.1 Humanities 9.7
Lecturer 21.9 Social Sciences 58.1
Senior Lecturer/Assistant Prof. 27.6 Multidisciplinary 7.6
Reader/Associate Prof./Prof. 24.9
Male 54.6
1 – 5 15.5 Female 45.4
6 – 10 30.5
SNS User
11 – 20 35.1 Yes 82.2
21 – 30 12.1 No 17.8
31 and over 6.8
Engage via SNS
Not engaging via SNS
Table 2: Cronbach's a.
Variable Cronbach’s a Variable Cronbach’s a
Intention (Ajzen 2002b; Lin 2006) 0.965 Perc. Usefulness (Lin 2006) 0.939
Attitude (Peslak et al. 2011) 0.942 Image (Moore and Benbasat 1991) 0.937
Subj. Norms (Lin 2006; Taylor and Todd 1995) 0.943 Trust (Chiu et al. 2006) 0.917
PBC (Lin 2006; Taylor and Todd 1995) 0.741 Peer Influence(Taylor and Todd 1995) 0.945
Privacy Control (Xu et al. 2013) 0.930 External Influence(Hsu and Chiu 2004) 0.902
Old Ties (Foregger 2008) 0.896 Reciprocity (Chiu et al. 2006) 0.886
New Contacts (Kim et al. 2011) 0.911 Self-Efficacy (Lin 2006) 0.910
Info Seek (Kim et al. 2011) 0.918 Self-Promotion(Bolino and Turnley 1999) 0.925
Info Share (Papacharissi and Rubin 2000) 0.804
Academics’ Intention to Adopt SNS for Engagement Within Academia
reliability according to Fornell and Larcker (1981).
We further tested construct reliability and validity
by conducting CFA using the AMOS software
package. As can be seen in Figure 1, all the constructs
have Composite Reliabilities (CR) above the
recommended value of 0.70 and the Average
Variance Extracted exceeds the threshold of 0.50
(Hair et al. 2014) and therefore reliability and
convergent validity have been established. In
addition, the square root of AVE is greater than inter-
construct correlations for every construct; thus, there
is discriminant validity among them.
According to Hair et al. (2014), when the number
of observations is above 250 and the model contains
more than 30 observed variables, significant p-values
are expected for χ
and a good model fit has been
established when CFI is above 0.90, SRMR is 0.08 or
less and RMSEA is less than 0.07. Our measurement
model meets all the above thresholds (χ
/df = 1.683,
CFI = 0.95, SRMR = 0.0517, RMSEA = 0.043),
demonstrating a good model fit.
4.2 Structural Model
After testing our full hybrid model (χ2/df =1.794, CFI
= 0.94, SRMR = 0.0714, RMSEA = 0.046), we
obtained the results that are presented in Figure 2.
According to the results, maintaining old contacts
(β = 0.180, p<0.01), creating new contacts (β= 0.137,
p<0.1), perceived usefulness (β= 0.518, p<0.01),
image (β= 0.117, p<0.05), and reciprocity (β=0.142,
p<0.01) had a positive effect on attitude towards
using SNS for academic engagement and therefore
H5, H6, H7, H2 and H9 were supported. Self-
promotion, on the other hand, had a slightly negative
effect (β= -0.073, p<0.1) on attitude and thus H1 was
rejected. Information seeking, information sharing
and perceived trust had non- significant effects on
attitude and therefore H4, H3 and H8 were rejected as
well. Peer influence (β=0.485, p<0.01) and external
influence (β=0.144, p<0.05) had positive effects on
social norms, and thereby H10 and H11 were
supported. While self-efficacy (β= 0.747, p<0.01) had
a significant positive effect on perceived behaviour
control, the effect of privacy control (β=-0.078,
p<0.1) was slightly negative and therefore only H13
was supported, whereas H12 was rejected. Finally,
H14 and H16 were supported as attitude (β=0.553,
p<0.01) and perceived behaviour control (β= 0.338,
p<0.01) affected intention to use SNS for academic
engagement positively. H15, however, was rejected
as the effect of social norms on intention was not
The aim of this study is to understand the factors that
motivate academics to use SNS in order to engage
with their peers and augment the impact of their
research. Ten out of the sixteen hypotheses were
supported based on the data analysis. Not
surprisingly, attitude towards SNS use for
engagement was found to have a strong and
significant effect on the intention of academics to use
such platforms for professional purposes. Similarly,
perceived behaviour control of SNS use affects the
intention to use them positively, a finding that is in
line with the expectations of TPB. In addition, there
were high levels of explained variance in these three
constructs (R
= 0.610, R
=0.667 and R
0.533). Social norms, on the other hand, do not have
any significant effect on intention. This is not
completely unexpected. Lin (2006), who looked into
the intention to participate in virtual communities,
found that social norms do not influence behavioural
intention. In addition, according to Taylor and Todd
(1995), it is not uncommon for studies using TAM
and TPB theories to find no significant influence of
social norms on behavioural intention. In fact, social
norms have been found to be more influential in
organisational settings and when respondents have
little experience with the technology under
examination. According to the demographics of our
sample the vast majority of the respondents already
use SNS for various reasons (82.2%), so they cannot
be considered as inexperienced users.
Another interesting finding is that the effects of
information sharing and information seeking on
attitude are not significant. A possible explanation is
that academics, being used to seeking and sharing
information through more formal and reliable
sources, such as journals and books, do not consider
SNS as potential channels for information exchange,
and therefore such motives do not affect their
attitudes towards using SNS for engagement.
Concerns about lack of credibility, the quality of
posted content and copyright issues, which have been
expressed in the study of Lupton (2014) regarding
SNS use by scholars, could explain the reluctance of
academics to consider SNS as important sources of
academic information. This could also explain the
non-significant effect of perceived trust on attitude. If
academics believe that SNS are not appropriate
environments for exchanging academic information,
trust should not be of such importance since the risks
associated with the concerns discussed above are not
present. Another potential explanation could be that
academics already know many of their peers in their
WEBIST 2016 - 12th International Conference on Web Information Systems and Technologies
Figure 1: Construct Correlation Matrix (Square root of AVE on the diagonal).
Figure 2: Results of SEM analysis (Note: * p< 0.1, **p<0.05, ***p<0.01, ns= not significant).
subject area prior to connecting to them online, thus
trust is taken for granted and does not affect their
attitudes towards SNS use for engagement within
A limited information exchange among
academics on SNS could also justify the fact that
CR AVE 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17
InfoSeek 0.920 0.744 0.862
Attitude 0.943 0.768 0.628 0.876
SocialNorm 0.944 0.893 0.521 0.498 0.945
PBC 0.772 0.638 0.577 0.733 0.466 0.799
OldTies 0.898 0.640 0.567 0.582 0.411 0.556 0.800
NewContac 0.912 0.776 0.781 0.646 0.460 0.551 0.617 0.881
Usefulness 0.941 0.842 0.748 0.771 0.499 0.684 0.582 0.711 0.917
Image 0.932 0.735 0.520 0.521 0.530 0.417 0.365 0.492 0.547 0.857
SelfPromo 0.923 0.708 0.418 0.350 0.331 0.366 0.416 0.492 0.443 0.403 0.842
Reciprocity 0.886 0.796 0.483 0.537 0.430 0.497 0.357 0.499 0.560 0.473 0.316 0.892
Trust 0.914 0.682 0.343 0.320 0.310 0.261 0.316 0.368 0.343 0.484 0.272 0.544 0.826
0.945 0.896 0.380 0.281 0.563 0.368 0.289 0.329 0.408 0.515 0.288 0.440 0.309 0.947
ExternalInfl 0.905 0.706 0.396 0.282 0.412 0.357 0.303 0.362 0.370 0.500 0.232 0.489 0.427 0.584 0.840
PrivacyCntr 0.927 0.761 0.180 0.208 0.216 0.126 0.230 0.243 0.193 0.199 0.156 0.207 0.440 0.145 0.279 0.873
SelfEfficacy 0.896 0.684 0.588 0.677 0.393 0.676 0.494 0.576 0.695 0.473 0.394 0.721 0.461 0.411 0.400 0.266 0.827
Intention 0.967 0.908 0.534 0.764 0.439 0.709 0.527 0.609 0.686 0.437 0.379 0.498 0.295 0.304 0.284 0.132 0.608 0.953
InfoShare 0.810 0.682 0.820 0.636 0.421 0.513 0.568 0.751 0.740 0.488 0.382 0.509 0.391 0.350 0.362 0.158 0.620 0.518 0.826
Academics’ Intention to Adopt SNS for Engagement Within Academia
privacy control has a slight negative effect on
perceived behaviour control. Indeed, it has been
found that privacy concerns and information sharing
on SNS are related, with privacy concerns having a
negative effect on self-disclosure of personal
information (Xu et al., 2013). It would be normal for
academics to consider privacy control as a relatively
unimportant factor of the overall control they believe
they have over their SNS use, if they do not disclose
any sensitive or significant information.
Finally, the self-promotion motive has a small but
negative effect on attitude towards SNS use for
academic engagement. This could be attributed to the
different attitudes that male and female academics
hold about self-promotion. Female academics have
been found to be reluctant to engage in self-
promotion activities, in contrast to their male
counterparts (Bagilhole and Goode, 2001; Coate and
Howson, 2014). If this is true, female respondents are
expected to hold an indifferent or even negative
stance towards using SNS for self-promotion.
Further research could also investigate whether there
are differences in academics' attitudes towards self-
promotion based on the discipline.
The present study contributes to the body of
knowledge about engagement and impact in
academia by examining the factors that affect
academics’ intentions to use SNS as a part of their
academic practice. We found that academics’ attitude
and perceived behavioural control regarding SNS use
for academic engagement are the main drivers of
academics’ intentions to adopt SNS for this purpose.
Attitude is mainly influenced by the perceived
usefulness of SNS and secondarily, by a sense of
reciprocity that characterises connections on SNS and
needs for networking and enhancing one’s
professional image. Self-efficacy regarding the use of
SNS for professional reasons is the main driver of
perceived behavioural control. Contrary to what was
expected based on the Decomposed Theory of
Planned Behaviour, social norms do not have
significant effects on academics’ intention to adopt
One of the main implications of our study is that
our findings can help academic SNS providers, such
as and ResearchGate understand the
needs of their members and design more efficient
services. As networking and collaboration among
members are the main factors that influence
academics’ attitude towards SNS, they could focus on
the creation of new innovative online services that
enhance the networking experience on their
platforms. In addition, marketing approaches that
stress the actual benefits that an academic can gain by
using SNS could prove to be more efficient in the
recruitment of new members than approaches that
encourage academics to join a social network because
their peers are already members.
An equally important implication is that
universities can use the results of the study to design
more successful online engagement campaigns. As
academics are the ones that undertake research and
create impact it is important that they get involved in
the general process of their institution’s engagement
attempts with other researchers and the public.
Providing training and support on SNS use could be
really helpful since self-efficacy has been found to
play a crucial role in academics’ perceived behaviour
control. In addition, associating the use of SNS for
academic engagement with a professional image that
is desirable in academia and recognising online
engagement activities as a part of the formal
academic practice would probably result in more
academics adopting social media for professional
The study has presented our early findings based
on our preliminary analysis Further analysis could
explore whether there are differences among personal
and professional attributes (for instance gender or the
stage at which one is, e.g. comparing early academics
vs. established academics). It will be also of interest
to explore whether there are any significant
differences between those users already engaged on
social media and how satisfied they are overall and
those who are not. With regard to this study’s
limitations, due to the specific context on which our
research focuses, asking questions that capture actual
use was deemed unfeasible. Although we were able
to capture the general actual use of SNS by asking
respondents to self-report the time they spend on
them, specific questions about the time spent on SNS
solely for engaging with other academics were
considered too complicated. This is due to the fact
that most academics do not consciously separate the
time they spend on SNS for engagement purposes
from the time they spend on SNS for other reasons.
Consequently, our model accounts only for intentions
and not for actual use.
Finally, the generalisability of our findings may
be limited due to the demographics of our sample.
Although special attention has been paid to including
academics from different countries, levels of
experience and disciplines, the majority of our
respondents work in universities in Europe and
WEBIST 2016 - 12th International Conference on Web Information Systems and Technologies
almost half our sample comes from the social
sciences. Using the results of this study to understand
academics’ motives from other disciplines and/or
geographical areas should be done with caution.
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