Dual paths to continuous online knowledge sharing: a repetitive behavior perspective
| Date | 18 November 2019 |
| Pages | 159-178 |
| DOI | https://doi.org/10.1108/AJIM-05-2019-0127 |
| Published date | 18 November 2019 |
| Author | Minhyung Kang |
| Subject Matter | Library & information science,Information behaviour & retrieval,Information & knowledge management,Information management & governance,Information management |
Dual paths to continuous online
knowledge sharing: a repetitive
behavior perspective
Minhyung Kang
Department of e-Business, School of Business,
Ajou University, Suwon, Republic of Korea
Abstract
Purpose –Continuous knowledge sharing by active users , who are highly active in answeri ng questions, is
crucial to the sustenan ce of social question- and-answer (Q&A) sites . The purpose of this paper is to
examine such knowledge sha ring considering reason-based elaborat e decision and habit-based automated
cognitive processes .
Design/methodology/approach –To verify the research hypotheses, survey data on subjective intentions
and web-crawled data on objective behavior are utilized. The sample size is 337 with the response rate of
27.2 percent. Negative binomial and hierarchical linear regressions are used given the skewed distribution of
the dependent variable (i.e. the number of answers).
Findings –Both elaborate decision (linking satisfaction, intentions and continuance behavior) and
automated cognitive processes (linking past and continuance behavior) are significant and substitutable.
Research limitations/implications –By measuring both subjective intentions and objective behavior, it
verifies a detailed mechanism linking continuance intentions, past behavior and continuous knowledge
sharing. The significant influence of automated cognitive processes implies that online knowledge sharing is
habitual for active users.
Practical implications –Understanding that online knowledge sharing is habitual is imperative to
maintaining continuous knowledge sharing by active users. Knowledge sharing trends should be monitored
to check if the frequency of sharing decreases. Social Q&A sites should intervene to restore knowledge
sharing behavior through personalized incentives.
Originality/value –This is the first study utilizing both subjective intentions and objective behavior data in
the context of online knowledge sharing. It also introduces habit-based automated cognitive processes to this
context. This approach extends the current understanding of continuous online knowledge sharing behavior.
Keywords Knowledge sharing, Intention, Continuous behaviour, Past behaviour, Repetitive behaviour,
Social Q&A sites
Paper type Research paper
1. Introduction
In the era of Web 2.0, many types of content are generated or rated by users (Gazan, 2011;
Paroutis and Al Saleh, 2009). Social question-and-answer (Q&A) sites, such as Yahoo!
Answers (http://answers.yahoo.com/) and Quora (www.quora.com), which allow users to
freely ask and answer questions, are typical examples of this phenomenon (Fang and Zhang,
2019; Guan et al., 2018; Jin et al., 2013, 2015; Kang, 2018; Khansa et al., 2015; Zhou, 2018).
On social Q&A sites, there are users who actively answer questions from other users.
Their main activity is answering, and their asking is rare compared to answering (Kang
et al., 2011). These active answerers are defined as “active users”in this study. Active
users provide a core knowledge base that attracts general knowledge-seeking users to
such sites (Kang, 2018). However, it is not natural to voluntarily provide knowledge to
social Q&A sites. Because knowledge on social Q&A sites is a kind of “public goods”
(Cabrera and Cabrera, 2002), users tend to free-ride –get answers to their own questions
and do not respond to the questions from other users (Guan et al.,2018).Therefore,active
users are a small portion of the entire user group, and most users are askers or readers
(Kang et al.,2011).Theywillstopvisitingiftheyfailtofindtheanswerstheyneed.Even
amonganswerers,manyofthemstopansweringaftertryingoneortwoanswers
Received 21 May 2019
Revised 22 August 2019
Accepted 15 October 2019
The current issue and full text archive of this journal is available on Emerald Insight at:
www.emeraldinsight.com/2050-3806.htm
Online
knowledge
sharing
AslibJournalof Information
Management
Vol.72 No. 2, 2020
pp.159-178
©EmeraldPublishingLimited
2050-3806
DOI10.1108/AJIM-05-2019-0127
159
(Pudipeddi et al., 2014). Thus, active users who repeatedly share knowledge are valuable
assets of social Q&A sites, and maintaining their knowledge sharing behavior is crucial
for the sustained success of such sites (Fang and Zhang, 2019).
As a practical way to maintain active users’contributions, social Q&A sites usually have
special programs to identify and motivate active users. For example, Naver Knowledge-iN
awards top-ranking active answerers with the title “Power Knowledge-iN (KiN).”Similarly,
Quora selects “Top Writers”every year, and Yahoo! Answers has a “Leaderboard”to
identify the most active users. However, these efforts of social Q&A sites identifying active
users and appreciating their contribution officially are not enough to ensure active users’
continuous knowledge sharing. Among many social Q&A sites with similar functions, only
a few are operating successfully (Guan et al., 2018). To effectively maintain continuous
knowledge sharing, a detailed understanding of the mechanisms of active users’continuous
knowledge sharing is necessary.
Continuous knowledge sharing on social Q&A sites is a type of continuous information
system (IS) use. Prior research on continuous IS use focuses mostly on reason-based
elaborate decision processes, where a user requires a continuance intention (based on a
positive evaluation of the previous experience) to continue a certain behavior (Aarts et al.,
1998). This stream of research is based on such theories as the expectation confirmation
theory (ECT; Bhattacherjee, 2001), the theory of planned behavior (TPB) (Ajzen, 1985) and
theory of reasoned action (TRA) (Fishbein and Ajzen, 1975). On the other hand, Kim et al.
(2005) and Limayem et al. (2007) introduced another line of research focusing on habit-based
automated cognitive processes, where a certain behavior becomes habitual through
repetition and is carried out automatically without a rational evaluation (Aarts et al., 1998).
However, the majority of the research is still based on elaborate decision processes (Cheung
et al., 2013; Chiu et al., 2011; Kim, 2011; Zheng et al., 2013).
However, elaborate decision processes are not enough to describe continuous online
knowledge sharing by active users of social Q&A sites. Active users typically share
knowledge several times a day, which indicates that knowledge sharing is a repetitive and
habitual behavior for them. Repetitive behaviors have been proven to have two different
procedural mechanisms: a reason-based elaborate decision process and a habit-based
automated cognitive process (Aarts et al., 1998). Thus, to fully understand a mechanism of
continuous knowledge sharing by active users, both elaborate decision and automated
cognitive processes should be considered.
In addition, many studies report a gap between intention and behavior (Lim et al., 2011;
Szajna, 1996; Wu and Du, 2012). Thus, in studying continuance behavior, it is not enough to
examine only intention; rather, it is desirable to check both intention and behavior. Further,
because of studies reporting insignificant correlations between self-reported and actual
behavior (Hortonet al., 2001), it is recommended thatactual behavior be measured objectively,
rather than self-reported behavior (De Guinea and Markus, 2009).
However, recent studies on continuous online knowledge sharing still focus only on
intention, and studies adopting automated cognitive processes are rare (Guan et al., 2018;
Hashim and Tan, 2015; Jin et al., 2015; Kang, 2018; Zhou, 2018). Moreover, no existing study
examines both intentions and behavior using appropriate measurements (e.g. a subjective
survey for intentions and objective web crawling for behavior).
To overcome these limitations of previous studies, this study suggests a comprehensive
research model that includes reason-based elaborate decision processes and habit-based
automated cognitive processes, in the context of online knowledge sharing. Furthermore,
this study attempts to rigorously validate the research model and hypotheses utilizing both
survey data on subjective intentions and web-crawled data on objective behavior.
In sum, this study focuses on the continuous knowledge sharing behavior of active users,
who are the core assets of social Q&A sites. Considering knowledge sharing by active users
AJIM
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