The role of negative network externalities in SNS fatigue. An empirical study based on impression management concern, privacy concern, and social overload
| Published date | 02 July 2018 |
| DOI | https://doi.org/10.1108/DTA-09-2017-0063 |
| Date | 02 July 2018 |
| Pages | 313-328 |
| Author | Yun Zhu,Zheshi Bao |
| Subject Matter | Library & information science,Librarianship/library management,Library technology,Information behaviour & retrieval,Metadata,Information & knowledge management,Information & communications technology,Internet |
The role of negative network
externalities in SNS fatigue
An empirical study based on impression
management concern, privacy concern,
and social overload
Yun Zhu
School of Journalism, Nanjing University of Finance and Economics,
Nanjing, China, and
Zheshi Bao
Business School, Hohai University, Nanjing, China
Abstract
Purpose –The purpose of this paper is to explore whether negative network externalities would contribute
to social networking site (SNS) fatigue and how this mechanism works.
Design/methodology/approach –A research model was proposed integrating two dimensions of negative
network externalities and three dimensions of mediators (impression management concern, privacy concern,
and social overload) to indicate how negative network externalities affect users’SNS fatigue. Online
questionnaires were adopted to collect data, and 307 valid samples were analyzed by structural equation
modeling approach.
Findings –The findings indicate that negative network externalities have significant indirect effects on SNS
fatigue through impression management concern, privacy concern, and social overload, and among the
three dimensions, privacy concern plays a more important role.
Research limitations/implications –This study offers a solidly grounded and well-demonstrated
conceptual model that not only indicates the effects of negative network externalities in the context of SNS
but also facilitates the understanding of SNS fatigue. Some theoretical and practical implications are
also provided.
Originality/value –This study is novel in exploring users’SNS fatigue a perspective of negative network
externalities. Besides, the mediating roles of impression management concern, privacy concern, and social
overload have been employed to indicate the formation of SNS fatigue.
Keywords Social overload, SNS users, Privacy concern, SNS fatigue, Impression management concern,
Negative network externalities
Paper type Research paper
1. Introduction
Social networking sites (SNSs), such as Facebook, MySpace have become some important
channels for people’s daily communications and interactions. Meanwhile, in recent years, the
popularity of portable devices (smartphones and tablet PCs) and mobile technologies have
further promoted this trend. Nearly, every moment, a great number of people use SNSs to
interact with others, express emotions, read current news, display beautiful pictures or just
share their daily lives. But on the other hand, as users are always encouraged to pay
continuous attention to SNSs and respond to an overwhelming volume of social demands
timely (Lee et al., 2016), physicaland psychological strain ismore likely to occur, which can be
called SNS fatigue. Prior literature has empirically revealed that SNS fatigue would damage
users’satisfaction and further contribute to discontinuous use intention (Zhang et al., 2016).
SNSs are social platforms based on users’participations, and the long-term operation and Data Technologies and
Applications
Vol. 52 No. 3, 2018
pp. 313-328
© Emerald PublishingLimited
2514-9288
DOI 10.1108/DTA-09-2017-0063
Received 13 September 2017
Revised 16 January 2018
Accepted 9 February 2018
The current issue and full text archive of this journal is available on Emerald Insight at:
www.emeraldinsight.com/2514-9288.htm
This work was supported by the Social Science Foundation of Jiangsu Province (17TQA003) and the
Fundamental Research Funds for the Central Universities (2016B46814).
313
Negative
network
externalities in
SNS fatigue
development of them are mainly based on users’continuance intention (Hsu et al., 2014).
Therefore,how to mitigate users’fatiguecan be considered as an approachto retain SNS users
and then enhance competitiveness of SNS providers.
With regard to some products or services, benefits are related to the number of existing
users and complementary goods. As the number of users and related complementary goods
increases, external benefits would emerge. This trend will attract new users and retain
original users. This phenomenon can be called network externalities (Katz and Shapiro,
1985). Lin and Lu (2011) employed network externalities and motivation theory to examine
factors affecting user’s joining SNS. The findings revealed that network externalities can
promote enjoyment and usefulness of SNS usage, which in turn affect users’continuance
intention of SNS. Chiu et al. (2013) found that network externalities can positively influence
SNS identification and satisfaction and then motivate users’subjective well-being and
loyalty. These researchers empirically showed that for users, larger network size in SNS and
more complementary products or services provided by SNS would give them more benefits
and attract more participations. Besides, some empirical results of prior researchers (Lin and
Lu, 2011; Zhang et al., 2017; Zhou and Lu, 2011) have revealed that in many situations,
network externalities cannot directly promote SNS users’intentions or behaviors, and some
mediators, such as enjoyment, usefulness and satisfaction are required. In conclusion, it is
not difficult to find that these studies mainly focused on the positive side of network
externalities, and they seem to have a potential assumption that network externalities will
lead to positive results.
However, prior literature also indicates that for users, the mechanisms of SNS designed
to facilitate connectivity may also create new and unintended problems that can constrain
the growth of personal networks and negatively impact on relationship quality (Binder et al.,
2012). When individuals are in large social networks, there is a higher probability for them
to meet others and suffer more uncontrolled contacts which are likely to be drivers of social
overload (Maier et al., 2014). Besides, the expanding social networks on SNSs usually
accumulate large scale of users’data, especially some personal information, and with the
increasing number of members added to SNS users’buddy lists, their real names, e-mail
addresses, schools, hobbies, and other personal information when they registered for
personal accounts will be disclosed to more audiences (Feng and Xie, 2014). Therefore, some
concerns about privacy protection will be produced. In addition, SNS users are motivated to
use impression management strategies to create desirable self-images (Lin et al., 2014). As
more and more distant relationships are established on SNSs, it is natural for users to
concern about how to manage their impressions especially facing distant friends. From
these studies, it can be found that sometimes negative sides of network externalities also
exist. The increasing number of users and complementary tools may not only generate
benefits but also cause some negative consequences, such as perceived overload and some
concerns. Meanwhile, according to prior literature, the antecedents of fatigue resulting from
SNS usage are exactly related to those consequences (Bright et al., 2015; Lee et al., 2016;
Ravindran et al., 2014). Therefore, negative network externalities are also likely to be
approaches to analyze SNS fatigue. However, to the best of our knowledge, no study on SNS
fatigue is explored from this perspective.
To fill this gap, the aim of this research is to examine whether negative network
externalities would contribute to users’SNS fatigue through social overload, privacy
concern, and impression management concern. The remainder of this paper is structured
as follows. In Section 2, theoretical background of this research is provided, and based
on it, hypotheses and research model are presented. Section 3 indicates the research
methodology of this study, followed by a test mode, data analysis and results in
Section 4. Last, in Section 5, implications, limitations, and future suggestions of this study
are discussed.
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DTA
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