Evasive knowledge hiding in academia: when competitive individuals are asked to collaborate

Abstract

Purpose-Academic knowledge work often presumes collaboration among interdependent individuals. However, this work also involves competitive pressures to perform and even outperform others. While knowledge hiding has not yet been extensively examined in the academic environment, this study aims to deepen the understanding of the personal (individual-level) and situational (job-related) factors that affect evasive knowledge hiding (EKH) within academia.

Design/methodology/approach-A field study was conducted on a nationwide sample of 210 scholars from both public and private business schools in a European Union member state. A series of paired sample t-tests were followed by hierarchical regression analyses to test moderation using the PROCESS macro.

Findings-The results suggest that scholars hide more tacit than explicit knowledge. The findings also indicate a consistent pattern of positive and significant relationships between trait competitiveness and EKH. Furthermore, task interdependence and social support buffer the detrimental relationship between personal competitiveness and evasive hiding of explicit knowledge, but not tacit knowledge.

Originality/value-The research provides insights into several important antecedents of EKH that have not been previously examined. It contributes to research on knowledge transfer in academia by focusing on situations where colleagues respond to explicit requests by hiding knowledge. The moderating role of collaborative job design offers practical solutions on how to improve knowledge transfer between mistrusted and competitive scholars. The collaboration-competition framework is extended by introducing personal competitiveness and relational job design, and suggesting how to manage the cross-level tension of differing collaborative and competitive motivations within academia.

Full text

Journal of Knowledge Management
Evasive knowledge hiding in academia: when competitive individuals are asked to collaborate
Tomislav Hernaus, Matej Cerne, Catherine Connelly, Nina Poloski Vokic, Miha Škerlavaj,
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To cite this document:
Tomislav Hernaus, Matej Cerne, Catherine Connelly, Nina Poloski Vokic, Miha Škerlavaj, (2018) "Evasive knowledge
hiding in academia: when competitive individuals are asked to collaborate", Journal of Knowledge Management, https://
doi.org/10.1108/JKM-11-2017-0531
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Evasive knowledge hiding in academia:
when competitive individuals are asked
to collaborate
Tomislav Hernaus, Matej Cerne, Catherine Connelly, Nina Poloski Vokic and Miha Škerlavaj
Abstract
Purpose –Academic knowledge work often presumes collaboration among interdependent individuals.
However, this work also involves competitive pressures to perform and even outperform others. While
knowledge hidinghas not yet been extensively examined in the academic environment, this study aims to
deepen the understanding of the personal (individual-level) and situational (job-related) factors that
affect evasive knowledge hiding (EKH) within academia.
Design/methodology/approach –A field study was conducted on a nation-wide sample of 210
scholars from both public and private business schools in a European Union member state. A series of
paired sample t-tests were followed by hierarchical regression analyses to test moderation using the
PROCESS macro.
Findings –The results suggest that scholars hide more tacit than explicit knowledge. The findings also
indicate a consistent pattern of positive and significant relationships between trait competitiveness and
EKH. Furthermore, task interdependence and social support buffer the detrimental relationship between
personal competitiveness and evasive hiding of explicit knowledge, but not tacit knowledge.
Originality/value –The research provides insights into several important antecedents of EKH that
have not been previously examined. It contributes to research on knowledge transfer in academia
by focusing on situations where colleagues respond to explicit requests by hiding knowledge. The
moderating role of collaborative job design offers practical solutions on how to improve knowledge
transfer between mistrusted and competitive scholars. The collaboration–competition framework is
extended by introducing personal competitiveness and relational job design, and suggesting how
to manage the cross-level tension of differing collaborative and competitive motivations within
academia.
Keywords Job design, Knowledge hiding, Competition–collaboration framework, Knowledge type,
Trait competitiveness
Paper type Research paper
Introduction
Knowledge hiding, defined as “an intentional attempt by an individual to withhold or conceal
task information, ideas, and know-how that has been requested by another person”
(Connelly et al., 2012, p. 65) can significantly damage relationships at work, create distrust
among co-workers, result in knowledge gaps and lead to lower individual and
organizational performance. A human tendency to look guardedly at the knowledge
possessed (Davenport and Prusak, 1998) is particularly problematic within the academic
setting, where scholars are expected to share knowledge with colleagues and students
alike, to advance the field and contribute to society. This paradoxical behavior is not
expected to occur within a positive organizational knowledge culture (Serenko and Bontis,
2016) or when individuals possess a high level of cultural intelligence (Bogilovic et al.,
2017).
Tomislav Hernaus is an
Associate Professor at the
Faculty of Economics and
Business, University of
Zagreb, Zagreb, Croatia.
Matej Cerne is based at the
Faculty of Economics,
University of Ljubljana,
Ljubljana, Slovenia.
Catherine Connelly is
based at McMaster
University, DeGroote
School of Business,
Hamilton, Canada.
Nina Poloski Vokic is
Professor at the Faculty of
Economics and Business,
University of Zagreb,
Zagreb, Croatia.
Miha S
ˇkerlavaj is Professor
at the Department for
Leadership and
Organizational Behavior, BI
Norwegian Business
School, Oslo, Norway.
Received 20 November 2017
Revised 1 March 2018
14 April 2018
14 June 2018
3 July 2018
Accepted 9 July 2018
Funding information/conflict of
interest declarations: This study
was supported by a project
grant “Knowledge hiding in
academia” received from the
University of Zagreb, Croatia.
The authors confirm that there
is no conflict of interest in the
writing/publishing of this paper.
DOI 10.1108/JKM-11-2017-0531 ©Emerald Publishing Limited, ISSN 1367-3270 jJOURNAL OF KNOWLEDGE MANAGEMENT j
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Nonetheless, while knowledge hiding has not been extensively examined in supposedly
collaborative academic environments, studies of life science scholars (Campbell et al.,
2002;Lee et al.,2010) have clearly indicated that secrecy, an intentional process of hiding
knowledge and information from some while sharing it with others (Costas and Grey, 2016),
is relatively common. The ever-increasing competitive pressure for publications, positions
and funding has been shown to lead to secrecy (Walsh and Hong, 2003), which has
some conceptual similarities to knowledge hiding. This might be especially true for
competitive individuals (Cyr and Choo, 2010). Indeed, personal competitiveness or
competitive personality (i.e. “the enjoyment of interpersonal competition and the desire to
win and be better than others,” cf. Spence and Helmreich, 1983, p. 41) may counter the
general requirement to collaborate in academia, triggering a “co-opetitive” behavior (i.e. a
combination of cooperative and competitive behavior). According to the theory of co-
operation and competition, it is possible for individuals to be competitive with respect to one
goal (e.g. personal goals and preferences) and collaborative with respect to another goal
(e.g. organizational goals and formal job requirements; cf. Deutsch, 1949;Tjosvold et al.,
1983).
Through this overarching framework, the present study will deepen our understanding of
the personal (individual-level) and situational (job-related) factors that affect evasive
knowledge hiding (EKH) within academia. This hiding behavior strategy is particularly
relevant for academia (Demirkasimoglu, 2016), because the knowledge possessed by
scholars is often sufficiently complicated that a partial or evasive answer is believable
(Connelly et al.,2012). We focus our attention on the under-researched context of
mistrusted interpersonal relationships, which are characterized by negative expectations,
potentially unfriendly exchanges and a lack of confidence that another person has your best
interests in mind (Lewicki et al.,1998).
Mistrusted relationships are unfortunately not uncommon in academia (Feist and Gorman,
2013), and are therefore the focus of our research. In a field study among business and
economics scholars in a European Union (EU) member state, we investigated to what extent
scholars hide knowledge from colleagues, and we examined the role of competitive
personality traits in predicting this behavior. We also consider whether collaborative work
(task interdependence; “the breadth of interconnectedness of a particular job with other
jobs”; Kiggundu [1981, p. 501]) and social support (“the perception or experience that one
is loved and cared for by others, esteemed and valued, and part of a social network of
mutual assistance and obligations”; Wills [1991, p. 265]) might discourage EKH. Finally, we
also considered the role of the type of knowledge (i.e. tacit and explicit) that has been
requested, and we controlled for the proximity between the knowledge requestor and the
knowledge hider (i.e. department versus university).
Our research provides insights about several important antecedents of EKH that have not
been previously examined. We contribute to research on knowledge transfer in academia
(Fullwood et al.,2013;Tan, 2016) by focusing on situations where colleagues do not
respond to explicit requests by hiding knowledge. The moderating role of collaborative job
design offers practical solutions on how to improve knowledge transfer between mistrusted
and competitive scholars. We extend the collaboration–competition framework (Deutsch,
1949) by introducing personal competitiveness and relational job design, and by
suggesting how to manage the tension of differing collaborative and competitive
motivations within academia.
In what follows, we first introduce EKH and briefly explain the distinctions between tacit and
explicit EKH. Next, we develop a set of hypotheses on the relationship between EKH and its
personal and job-related antecedents. We then focus on describing the sample, procedure
and research instrument (measures) used for our study and present research results.
Finally, we discuss our findings and draw general conclusions for theory and practice.
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Literature review
Evasive knowledge hiding
Evasive knowledge hiding involves some deception because it represents a situation where
an individual provides incorrect or incomplete information to the knowledge hiding target
(Connelly et al.,2012). EKH has been chosen for this study because of the specific,
complex nature of academic work where knowledge continually advances and new
problems must be solved (Antes and Mumford, 2011). We expect that this type of
knowledge hiding is most likely displayed among academicians (Demirkasimoglu, 2016),
because scholars may feel embarrassed if they were to say that they do not know the
answer to the question (i.e. they would avoid “playing dumb” strategy), or if they cannot
provide a reasonable excuse for not providing the requested information (i.e. they may not
be able to engage in rationalized knowledge hiding). The nature of the knowledge
requested has a key role in determining whether a scholar will be willing to share the
“requested” knowledge, which others desire but obviously do not possess. Thus far,
empirical studies about knowledge hiding have not examined the impact of the differences
between tacit and explicit knowledge. Tacit knowledge is “personal, intangible and
cognitively-embedded,” and explicit knowledge is “formal, systematic and codified”
(Polanyi, 1966).
Existing research (Peng, 2013) has primarily focused either on the complexity of knowledge
(recognized as an important situational factor that shapes employees’ hiding practices) or
psychological ownership feelings over knowledge. For instance, Connelly and Zweig (2015)
argued that employees are more likely to hide knowledge that is complex. Similarly, Peng
(2013) found that individuals tend to hide high-value or personal knowledge when they feel
a strong attachment to the knowledge (e.g. personal insights and creative ideas).
However, Wang et al. (2014) concluded that within the educational context, the decision to
share tacit and explicit knowledge depends on the trade-off between the costs and rewards
incurred by that behavior. Apparently, individuals are generally more inclined to share
explicit and “unimportant” knowledge (Yu et al.,2013), but are more eager to withhold
knowledge that is implicit and vital (Ford and Staples, 2008). Therefore, we believe that
similar motives and behaviors might be present in terms of both knowledge sharing and
knowledge hiding phenomena. This is particularly true for mistrusted relationships; previous
research has found that individuals are often unwilling to share their knowledge and
expertise with co-workers due to a lack of trust (Currie and Kerrin, 2003). The more
employees distrust the person requesting the information, the more likely they are to hide
knowledge from that person (Connelly et al.,2012).
Within the academic context, we distinguish between formal and systematic or explicit
knowledge (e.g. info about call for papers, research grant calls, teaching/fellow openings, the
announcement of scholarly events, published theoretical concepts, research methodology
and statistical methods) and intangible, high-value implicit or tacit knowledge (e.g. new
concepts, innovative/visionary research ideas, project proposals and work-in-progress). As
Niedergassel and Leker (2011) noted, “academic scientists can usually choose rather freely
whether they want to cooperate with a certain external partner or not.” These authors went on
to show that trust is of particular importance when researchers decide whether to
communicate tacit knowledge with someone. We expect that tacit knowledge will be hidden
more often than explicit knowledge within the academic environment because people
rationally pursue their self-interests and carefully calculate the pay-off of sharing knowledge
by considering the resource types that are potentially exchanged (Lee et al., 2010). In other
words, academics might approach knowledge hiding selectively.
While certain types of scholarly knowledge (published theoretical concepts and
methodological procedures) and academic information (scientific opportunities and events)
might be perceived as collaboratively shared public goods, tacit knowledge can still be
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understood as someone’s personal resource that represents a source of competitive
advantage. In addition, if we take into consideration that tacit knowledge is practically
easier to hide than explicit knowledge (Peng, 2013), and that sharing tacit knowledge costs
significantly more time and effort (Reychav and Weisberg, 2010), the following hypothesis is
proposed:
H1. Academics hide more tacit than explicit knowledge.
Personal competitiveness and evasive knowledge hiding
Several personality traits have been shown to be related to knowledge sharing (Wang and
Noe, 2010). Individuals inherently differ in their tendencies to collaborate, share information
and react positively or negatively to others’ requests (Mooradian et al., 2006). We expect a
similar pattern in knowledge-misbehaving situations, and therefore investigate relevant
individual-level predictors of knowledge hiding.
We find personal competitiveness a highly relevant individual-level characteristic for
academic interactions, because it can explain why some individuals respond to the
increasing requirements of academic life in a collaborative or a selfish manner. Cegarra-
Sanchez and Cegarra-Navarro (2017) suggest that student tendencies to engage in rumor-
mongering or spreading partial truths can affect the learning environment significantly.
Some relevant research has also been conducted on competitive work climates. For
instance, Haas and Park (2010) were among the first to measure perceived academic
competition –how a scientist perceived the overall level of competition in his or her scientific
field. While their study addressed the level of competitiveness between academic
individuals (a contextual factor determining broader academic climate), we investigate
competitiveness within individuals (a scholar’s personality trait).
Competitive individuals tend to maximize their own outcomes and interests seeking relative
advantage over others because they seek individual recognition, status and rewards (Van
Lange et al.,1997
). Building on previous research on how competitive individuals engage in
knowledge sharing (Cyr and Choo, 2010), we expect that competitive scholars would be
more prone to hide knowledge than their less competitive counterparts. We base our
argument on the recent work of Connelly et al. (2014), who showed that individual
characteristics such as self-efficacy and trait competitiveness indirectly led to people
feeling “too busy” to share their knowledge when it was requested. Such reasoning is
additionally supported by a competitive part of the theory of co-operation and competition,
which implies that negative attitudes such as “we are against one another” and “we seek to
enhance our own power by reducing the power of the other” are manifested through
impaired communication, obstructiveness and lack of helpfulness (Deutsch, 2006,p.25).In
other words, scholars with competitive personalities might have a desire to perform well and
thus prefer to achieve more than their academic colleagues (Tjosvold et al.,1983), by
keeping their knowledge for themselves. We therefore hypothesize:
H2. Personal competitiveness predicts evasive hiding of (a) explicit knowledge and (b)
tacit knowledge.
The moderating role of collaborative job design
The direct relationship between personal competitiveness and EKH could be further
explained by considering the role of formal job features. Job design, or the content and
organization of one’s work tasks, activities, relationships and responsibilities (Parker, 2014),
represents a collaborative part of the theory of co-operation and competition, which might
help prevent or diminish knowledge hiding. For instance, previous research has suggested
that job design (i.e. work autonomy, time pressure, task interdependence and contact with
beneficiaries) can mitigate the negative effects of delays in information exchange (Grant,
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2007;Guenter et al., 2014) because job characteristics set clear expectations about
required and discretionary behaviors in the workplace. While we can broadly distinguish
among task-, knowledge- and social-job characteristics (Morgeson and Humphrey, 2006),
the latter group is particularly relevant for the knowledge hiding dilemma as a relational
issue.
Social job characteristics (i.e. task interdependence and social support) provide a unique
perspective on job design beyond motivational characteristics (Humphrey et al.,2007).
While researchers increasingly support the relational architecture of jobs (i.e. “the structural
properties of work that shape employees’ opportunities to connect and interact with other
people,” cf. Grant, 2007, p. 396) and introduce relational mechanisms (such as goal and
task interdependence, interactions with others and social support) in their knowledge-
sharing research models, more work is needed to understand the effects that these job-
related factors have on individuals’ intentions to hide knowledge.
Task interdependence and social support are relational aspects of job design that are
particularly relevant for understanding knowledge hiding in academia. Both constructs
represent collaborative job features that have “the potential to interact with competitive
personality traits and counterbalance them” (Barrick and Mount, 1993). A mixed motives
perspective at the individual level follows the logic of co-opetition (Tsai, 2002) that refers to
simultaneously cooperative and competitive behavior such as knowledge sharing among
competitors. The cooperative aspect of knowledge sharing refers to the collective use of
shared knowledge to pursue common interests. Alternatively, the competitive aspect refers
to the use of shared knowledge to make private gains in an attempt to outperform the
business partners (Khanna et al.,1998). This perspective is conceptually supported by the
collaboration–competition framework proposed by Deutsch (1949), who emphasized that
most situations in everyday life involve a complex set of trade-off goals and sub-goals.
However, the original framework did not attempt to make clear how individuals with certain
personality-trait characteristics (e.g. trait competitiveness) would be affected by relational
job mechanisms in situations where they may have opportunities to hide their knowledge.
In contrast to social support, high levels of task interdependence require co-workers to
interact to obtain crucial resources (Fan and Gruenfeld, 1998), such as information.
Following recent findings reported by Cerne et al. (2017), we expect that interdependent
employees will avoid hiding knowledge from colleagues, even if they mistrust them, so that
they can fulfill their own job duties. Task integration and task interdependence do not offer
employees much discretion; instead, the job requirements reduce the opportunities to
behave competitively no matter how much individuals distrust each other.
On the other hand, if scholars work in isolation and are not formally required to exchange
knowledge among themselves (i.e. low-task interdependence), they may become less
collaborative and more likely to hide their knowledge from colleagues. Such individuals
neither would necessarily need others’ input to perform their work nor would they feel
obligated to respond to others’ requests. In addition, if the requested knowledge does not
relate specifically to an assigned task, it might be hidden because of a belief that assisting
colleagues is not their responsibility (Connelly et al.,2012) so they do not need to go
against their competitive nature. In other words, high-task interdependence between
knowledge holders and requestors might neutralize personality-driven knowledge hiding,
which is hypothesized as follows:
H3. The relationship between personal competitiveness and the evasive hiding of (a)
explicit knowledge and (b) tacit knowledge is moderated by task interdependence.
When task interdependence is high, the relationship between personal
competitivenessand evasive knowledge hiding is less negative.
Social support may provide a similar moderating effect on the relationship between trait
competitiveness and EKH. Complementing the general definition of social support, which
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relates to common perceptions of being cared, esteemed and valued, work-related social
support pertains to assistance from supervisors and co-workers (Karasek and Theorell,
1990). Receiving this job resource from social environment might mitigate the effects of a
negative relationship with a mistrusted academic colleague. Supervisory (management)
support is one of the well-recognized social job resources that has already been
demonstrated to influence the ease with which information or knowledge has been shared
(Wang and Noe, 2010). For instance, a supervisor’s presence may require colleagues to
adjust their behavior. A leader could also monitor whether employees follow social norms
and formal rules in the organization. Similarly, if colleagues assist by sharing requested
knowledge and expertise, and provide encouragement and support (Zhou and George,
2001), and thus create a collaborative work climate, then according to the theory of co-
operation and competition, the negative effect of personal competitiveness on evasive
knowledge sharing will be weakened. Vice versa, when co-workers are not interested in
providing social support, the focal relationship between a competitive scholar and his or her
mistrusted colleague will remain negative and lead to EKH.
Although social job-enrichment usually enables collaboration, an individual’s trait
competitiveness will lead him/her to hide knowledge, thus creating a conflict between co-
operative (positive) and competitive (negative) motives. Therefore, the influence of socially
supported jobs on the relationship between competitive personality and evasive hiding
intentions is hypothesized to be as follows:
H4. The relationship between personal competitiveness and the evasive hiding of explicit
knowledge is moderated by social support. When social support is high, the
relationship between personal competitiveness and evasive hiding of (a) explicit
knowledge and (b) tacit knowledge is less negative.
Method
Sample and procedure
The field study was conducted among Croatian scholars at public and private business
schools (Figure 1). Although it is the youngest EU member state (it joined in 2013), Croatia
is a full member of the Bologna Process and has been included in the European higher
education area since 2001. Taking into account the convergence of higher education
systems in Europe, as well as institutional relationships with academic departments across
disciplinary fields (Lee, 2004), we decided to focus on a single academic field: economics
and business. Being exposed to the mounting competitive pressure, and perceived as cash
cows for contemporary universities (Parker, 2018), business schools are a useful example
of knowledge-intensive organizations. In such loosely coupled systems often described as
Figure 1 Research framework
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an “organized anarchy” (Cohen et al., 1972), knowledge management is recognized as a
key enabler of effective governance (Blackman and Kennedy, 2009;Amayah, 2013).
A database of higher education scholars was created by retrieving e-mail addresses from
institutional webpages. Each participant received an e-mail invitation with a link to an online
questionnaire. Participation in the survey was voluntary and participants’ anonymity was
assured. Of the 922 faculty members e-mailed, 210 scholars (31.4 per cent non-tenured,
50.2 per cent tenured and 19.8 per cent of unknown academic rank) from 11 higher
education institutions participated in the study. The response rate was 22.8 per cent, which
is considerably higher than 10 per cent typical for internet surveys (Saunders et al., 2007).
Socio-demographic questions revealed that the sample is somewhat gender-biased (63.9
per cent women) in comparison with the population (51.7 per cent women), and the majority
of respondents were scholars in the 30 to 39 age range (52.1 per cent). Assistant
professors (29.5 per cent) and senior assistants/postdoctoral scholars (23.5 per cent)
represented more than a half of the sample, although other ranks were represented as well
(e.g. associate and full professors). The average academic job tenure of respondents was
12.4 years (SD = 8.3). For more details about respondents, please see Table I.
Measures
Evasive knowledge hiding. Evasive knowledge hiding was assessed by using a four-item
scale measure of EKH (Connelly et al.,2012). Respondents (knowledge holders) were
asked about their hiding intentions separately for not only different types of knowledge but
also in relation to different knowledge requestors (because there are mixed results about
knowledge sharing practices toward distal versus proximal colleagues; e.g. Ford and
Staples, 2008;Cyr and Choo, 2010). Specifically, participants reported how often they
decline requests received from departmental or university colleagues for either explicit
Table I Profiles of respondents
Demographic characteristics No. of responses (%)
Gender
Male 61 29.1
Female 108 51.4
No response 41 19.5
Age
Under 30 17 8.1
30-39 87 41.4
40-49 33 15.7
50-59 22 10.5
60 and up 9 4.3
No response 42 20.0
Academic position
Research assistant 26 12.4
Postdoctoral scholar 39 18.6
Assistant professor 50 23.8
Associate professor 23 11.0
Professor 31 14.7
No response 41 19.5
Job tenure
Less than 10 years 74 35.2
10-19 years 62 29.5
20-29 years 20 9.5
Over 30 years 8 3.8
No response 46 21.9
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(e.g. published work and academic information) or tacit (e.g. work-in-progress and
research ideas) knowledge. The sample item is: “I agreed to help him/her but instead gave
him/her information different from what he/she wanted.” Each item was rated on a five-
response choice frequency scale (ranging from “1” –never to “5” –always). The EKH
measure showed acceptable internal consistency (Cronbach’s alphas varied between 0.85
and 0.91).
Personal competitiveness. Competitive personality as a predictor variable was assessed
using four items from the personal competitiveness scale validated by Lu et al. (2013).
Scholars were asked to report on a five-point Likert-type scale (ranging from 1 –“strongly
disagree” to 5 –“strongly agree”) to what extent they are disturbed and jealous if their
colleagues outperform them in an argument or academic achievement, or get rewarded for
their achievements. An example of the statements used is: “I cannot stand being beaten in
an argument by other colleagues.” One item was deleted because it was specifically
related to sports and not to individual competitiveness in general. The internal reliability was
acceptable (Cronbach’s alpha = 0.77).
Collaborative job design. Task interdependence was measured with five items adopted
from Pearce and Gregersen’s study (1991). The sample item is: “I frequently must
coordinate my efforts with others.” The answers were scored on a five-point Likert-type
scale (ranging from “1” –strongly disagree to “5” –strongly agree). Coefficient alpha of this
scale’s ratings was 0.84. Social support measure consisted of six items, which were taken
from the Work Design Questionnaire developed by Morgeson and Humphrey (2006).The
sample item is: “I have the opportunity to develop close friendships in my job”; and the
scale reliability was above cut-off value (Cronbach’s alpha = 0.88).
Control variables. Several relevant personality (achievement striving and prosocial
motivation) and socio-demographic variables (gender, age, academic tenure and rank)
were examined as controls. Achievement striving (i.e. “the motivation to want to do well in
life,” cf. Hui et al.,2010, p. 1398) has been approached as a higher career ambition and
demanding personal goals that potentially might result in detachment from co-workers,
generate competitive thinking and lead to more extensive knowledge hiding. The construct
was measured by applying a ten-item five-point Likert-type scale developed by Jackson
et al. (2010) comprising both positive (e.g. “I do more than what’s expected of me”) and
negative statements (e.g. “I find it difficult to get down to work”). The construct showed a
good reliability level (Cronbach’s alpha = 0.83). Prosocial motivation (i.e. “the desire to have
a positive impact on other people or social collectives,” cf. Grant, 2007,p.399)leadsto
collaborative behavior (Cardador and Wrzesniewski, 2015) and might reduce the level of
knowledge hiding. A five-item five-point Likert-type scale was obtained from Grant and
Sumanth (2009) and validated in our sample (Cronbach’s alpha = 0.84).
In addition to gender,age and academic/job tenure, we also controlled for academic rank
(full professors and associate professors represented “tenured” positions, while assistant
professors and others were classified as ‘non-tenured’ positions) as an important status
characteristic within the academia. Finally, as previous research provided a mixed evidence
whether the proximity of requestors matters to the decision of whether to engage in less
knowledge sharing (Ford and Staples, 2008), we decided to control for functional proximity/
distance (i.e. not being part of the same unit or department) and examined how it might be
of importance in predicting knowledge hiding among academics.
Data analysis
We adopted confirmatory factor analysis to check the convergent validity and discriminant
validity. Convergent validity was examined by composite reliability and average variance
extracted (AVE). Our composite reliability values ranged from 0.8453 to 0.9012, which are
above the recommended value of 0.7. In addition, AVE scores ranged from 0.5012 to
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0.6955 and all surpass the recommended threshold of 0.5 for each construct (Fornell and
Larcker, 1981). Finally, we measured the square root of AVE to assess discriminant validity
for each construct (within-construct variance) and revealed that they are significantly
greater than the correlation coefficients between constructs (between-construct variance),
thus providing an evidence for discriminant validity among the constructs.
Independent sample t-tests showed no significant differences between academic rank
missing data cases and both “tenured” and “non-tenured” cases (for within-department and
within-university EKH, as well as for tacit and explicit EKH). However, certain significant
differences were found between “tenured” and “non-tenured” respondents (i.e. significant
differences in knowledge hiding were found for tacit knowledge at the departmental and
university level). Therefore, in the further analysis, we controlled for the newly created
“tenured position” dummy variable.
Given the cross-sectional and single-source nature of our research (data were collected
from the same respondents for both independent and dependent variables at a single point
of time), we conducted two additional analyses to identify potential issues related to
common method bias. First, Harman’s single factor test, a principal component analysis on
all items of our constructs extracting only one factor and using no rotation method, was
conducted for each of our four contextually different research models [(tacit vs explicit
knowledge type) (proximal vs distal colleagues)]. No dominant factor emerged. The
overall variance explained by the extracted factor was below the threshold of 50 per cent (it
ranged from 21.39 to 22.02 per cent) thus providing no evidence that common method
variance might be an issue. Due to the potential social desirability of answers regarding
knowledge hiding, the effects of the method variance were additionally modeled at the
construct level, again providing no evidence of measurement error (36.44 per cent of overall
variance explained).
Second, we applied Lindell and Whitney’s (2001) marker variable test, using a theoretically
unrelated variable to adjust the correlations among the principal constructs in the model.
Any high correlation of the marker variable with any other of the study’s principal constructs
would indicate a potential common method bias. For robustness, we separately repeated
the marker variable test with two variables that are not included in the model (work
autonomy and task variety, both also part of the Work Design Questionnaire; Morgeson and
Humphrey, 2006), for which we have little or no theoretical basis to expect the relationship
with the study’s principal constructs. The average correlation between the study’s principal
constructs for work autonomy (r=0.07) and task variety (r=0.01) was low and non-
significant, again providing no evidence of the common method bias.
Results
Table II shows the descriptive statistics, reliability scores and correlations among all the
variables included in the study. More than half of respondents (from 50.2 to 65.7 per cent of
respondents) acknowledged that they engage in EKH when they do not trust their
academic colleagues. However, although widespread, such practice does not occur often,
as mean values for EKH (on a frequency scale 1-5) ranged from 1.68 to 1.88.
We checked for the initially hypothesized dissimilarities in explicit and tacit EKH behavior
across different academic situations (proximal vs distal colleagues) by conducting paired
sample t-tests both for within-department (t-test value = 5.075, p<0.01) and within-
university (t-test value = 5.075, p<0.01) relationships, and found an evidence that EKH
practices differ significantly along the tacit–explicit dimension, thus supporting H1.
Evidently, scholars hide tacit knowledge more than explicit knowledge within mistrusted
academic relationships.
Next, we performed a series of hierarchical linear regression analyses to test H2, with personal
competitiveness as the focal predictor of EKH (both explicit –H2a and tacit –H2b). Four
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Table II Means, standard deviations, reliability scores and correlations
No. Variable M SD 1 2 3 4 5 6 7 8 9 10 11 12 13
1 Gender 1.640 0.482 –
2 Age 2.518 1.021 0.054 –
3 Academic/job tenure 1.700 0.777 0.062 0.560** –
4 Academic rank 3.080 1.512 0.019 0.802** 775** –
5 Task interdependence 3.193 0.731 0.028 0.044 0.049 0.068 (0.838)
6 Social support 3.043 0.869 0.147 0.018 0.096 0.008 0.636** (0.874)
7 Personal competitiveness 1.729 0.744 0.006 0.249** 0.086 0.205** 0.034 0.030 (0.765)
8 Prosocial motivation 3.715 0.686 0.149 0.093 0.075 0.106 0.280** 0.279** 0.170* (0.843)
9 Achievement striving 4.106 0.537 0.148 0.077 0.005 0.059 0.163* 0.016 0.354** 0.417** (0.831)
10 Explicit KH (department) 1.682 0.835 0.022 0.142 0.088 0.125 0.115 0.108 0.404** 0.260** 0.179* (0.851)
11 Tacit KH (department) 1.843 0.973 0.005 0.124 0.105 0.090 0.098 0.088 0.334** 0.249** 0.180* 0.882** (0.853)
12 Explicit KH (university) 1.701 0.842 0.050 0.221** 0.082 0.171* 0.089 0.077 0.430** 0.252** 0.147 0.828** 0.796** (0.879)
13 Tacit KH (university) 1.875 0.962 0.002 0.286** 0.145* 0.246** 0.120 0.111 0.437** 0.306** 0.192* 0.774** 0.864** 0.886** (0.871)
Notes: n= 210; coefficient alphas are given on the diagonal in parentheses; *p<0.05; **p<0.01
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models predicting hiding different types of knowledge in various contextual situations [(tacit vs
explicit knowledge type) (proximal vs distal colleagues)] were constructed. First, we
inserted socio-demographic controls (gender, age, academic/job tenure and academic rank)
in Model 1, followed by additional job-design variables (task interdependence and social
support) and individual traits (personal competitiveness, achievement striving and prosocial
motivation). In addition, we controlled for functional proximity (departmental vs university
colleagues) as distinctive academic situations. Collinearity diagnostics indicated that
multicollinearity was not a significant issue (with Tolerance indicators ranging from 0.257 to
0.897 and VIF scores ranging from 1.114 to 3.887).
The results of Models 2 and 6 summarized in Tables II and III indicate a consistent pattern
of positive and significant relationships between personal competitiveness and EKH toward
departmental colleagues (explicit EKH:
b
= 0.484, p<0.01; tacit EKH:
b
= 0.463, p<
0.01), as well as concerning distal (university-level) relationships (explicit EKH:
b
= 0.534,
p<0.01; tacit EKH:
b
= 0.595, p<0.01), thus confirming H2a and H2b.
We further examined interaction effects of collaborative job design to test H3 and H4 by
using the PROCESS macro for SPSS v2.16.3 (Hayes, 2016). Model 3 examined the
moderating role of task interdependence on the effect of the knowledge holder’s personal
competitiveness on their evasive hiding of explicit knowledge toward close (departmental)
but mistrusted academic colleagues. Initial support has been found for H3a, because the
interaction term’s (personal competitiveness xtask interdependence) coefficient (interaction
term = 0.225, p<0.01) was significant, as shown in Table III. Furthermore, a bootstrapping
procedure (Model 1 in Table V) revealed that this moderating effect is significant both at
lower (point estimate: 0.323, 95 per cent CI from 0.0802 to 0.5665) and higher levels of task
interdependence (point estimate: 0.658, 95 per cent CI from 0.4108 to 0.9050).
Figure 2 portrays the plot of this interaction, indicating that when personal competitiveness is
high, high levels of task interdependence lead to even more knowledge hiding. On the other
hand, when trait competitiveness is low, high levels of task interdependence lead to less
knowledge hiding. To test this interpretation, we conducted a simple slopes analysis. Personal
competitiveness exhibited a positive relationship with EKH when the level of task
interdependence was low (gradient = 0.95, t=5.485,p= 0.00), as well as when it was high
(gradient = 1.87, t=4.383,p= 0.00). On the other hand, task interdependence was not found
to moderate the relationship between personal competitiveness and EKH of tacit knowledge in
within-department mistrusted relationships (Model 7 in Table III), thus rejecting H3b.
A similar procedure was followed to evaluate distal (university-level) relationships. Task
interdependence was once again found to moderate the relationship between trait
competitiveness and evasive hiding of explicit knowledge (Model 3 in Table IV; interaction
term = 0.228, p<0.01) both for lower (point estimate: 0.375, 95 per cent CI from 0.1347 to
0.6161) and higher values of the moderator (point estimate: 0.718, 95 per cent CI from
0.4737 to 0.9629), thus supporting H3a.
This interaction exhibited a similar pattern to the one depicted in Figure 2. Analogous to the
within-department mistrusted relationships, the interaction term was again not significant for
evasive hiding of tacit knowledge (Model 7 in Table IV), rejecting H3b.
Next, Model 4 in Table III considered whether social support moderates the relationship
between personal competitiveness and evasive hiding of explicit knowledge toward close
(within-department) mistrusted relationships. Supporting H4a, the interaction term’s
(personal competitiveness xsocial support) coefficient (interaction term = 0.202, p<0.05)
was significant, which has also been additionally confirmed with the bootstrapping
procedure results (Model 2 in Table V). We depicted this moderation in Figure 3, showing
that when personal competitiveness is high, high levels of social support lead to even more
EKH. On the other hand, when personal competitiveness is low, higher levels of social
support lead to less EKH. To test this interpretation, we conducted a simple slope analysis.
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Table III Hierarchical linear regression analysis results for evasive knowledge hiding as a dependent variable (proximal colleagues)
Measure
Explicit EKH Tacit EKH
Model 1 Model 2 Model 3 Model 4 Model 5 Model 6 Model 7 Model 8
BSEBSEBSEBSEBSEBSEBSEBSE
Intercept 2.130 0.292 1.518 0.759 1.466 0.753 1.462 0.753 2.159 0.314 1.535 0.906 1.498 0.906 1.498 0.907
Gender 0.043 0.136 0.022 0.128 0.003 0.127 0.006 0.127 0.020 0.159 0.063 0.153 0.045 0.153 0.052 0.153
Age 0.066 0.112 0.059 0.098 0.057 0.097 0.050 0.097 0.153 0.131 0.119 0.117 0.118 0.116 0.113 0.117
Academic/job tenure 0.051 0.135 0.111 0.198 0.125 0.197 0.127 0.197 0.103 0.158 0.317 0.237 0.328 0.237 0.328 0.237
Academic rank 0.032 0.086 0.055 0.088 0.056 0.088 0.054 0.088 0.038 0.101 0.154 0.105 0.155 0.105 0.153 0.105
Task interdependence ––0.013 0.108 0.018 0.107 0.017 0.108 ––0.016 0.128 0.012 0.128 0.035 0.130
Social support ––0.085 0.093 0.087 0.092 0.046 0.094 ––0.044 0.110 0.046 0.110 0.019 0.113
Personal competitiveness ––0.484*** 0.093 0.490*** 0.092 0.485*** 0.092 ––0.463*** 0.111 0.467*** 0.111 0.463*** 0.111
Prosocial motivation ––0.182 0.100 0.160 0.100 0.162 0.100 ––0.213 0.119 0.197 0.120 0.200 0.120
Achievement striving ––0.000 0.132 0.006 0.131 0.012 0.131 ––0.061 0.157 0.065 0.157 0.069 0.157
Competitiveness Task interdependence –– – –0.225*** 0.114 – ––– – –0.162 0.138 ––
Competitiveness Social support ––––––0.202** 0.102 ––––– –0.135 0.123
Ftest 1.283 5.244 5.192 5.196 0.905 3.906 3.662 3.639
Adjusted R
2
0.007 0.186*** 0.201*** 0.201*** 0.002 0.135*** 0.137*** 0.136***
Notes: The table presents unstandardized regression coefficients and standard errors for each measure; values in italic are relevant for tests of hypotheses; *p<0.10; **p<0.05;
***p<0.01
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Personal competitiveness exhibited a positive relationship with EKH when the level of social
support was low (gradient = 0.89, t= 5.138, p= 0.00), as well as when it was high
(gradient = 1.69, t= 3.961, p= 0.00). Similar results were also reported by the
bootstrapping procedure (Model 3 in Table V), thus confirming our initial findings. However,
social support was not found to significantly moderate the relationship between personal
competitiveness and evasive hiding of tacit knowledge in within-department mistrusted
relationships (Model 8 in Table III), thus failing to provide support for H4b.
Finally, social support was once again found to moderate the relationship between personal
competitiveness and the evasive hiding of explicit knowledge (Model 4 in Table IV;
interaction term = 0.166, p<0.10). A bootstrapping procedure (Model 4 in Table V)
revealed that this moderating effect is significant both at lower (point estimate: 0.399, 95 per
cent CI from 0.1484 to 0.6494) and higher levels of the moderator (point estimate: 0.690, 95
per cent CI from 0.4385 to 0.9420), thus confirming H4a. This interaction exhibited a similar
pattern to the one depicted in Figure 3. However, the interaction term was not significant for
evasive hiding of tacit knowledge in distal (within-university) mistrusted relationships (Model
8inTable IV), thus not providing support for H4b.
Discussion
Universityscholarsoftenfaceadilemma;theyhavecompetitivepressurestoperformand
even outperform others, yet other academics request their assistance. We therefore examined
the personal (individual-level) and situational (job-related) factors that may lead scholars to
engage in EKH. Our results suggest that academics hide more tacit than explicit knowledge,
and that personal competitiveness predicts evasive hiding of both tacit and explicit
knowledge. However, our results further suggest that the relationship between personal
competitiveness and the evasive hiding of explicit knowledge is moderated by relational job
design. When either task interdependence or social support is high, the relationship between
personal competitiveness and evasive hiding of explicit knowledge is less negative. There are
important theoretical and practical implications that follow from these findings.
Theoretical contributions
The first theoretical contribution to the knowledge hiding literature is related to our evidence
that this phenomenon occurs in academic settings. By narrowing our focus on the practice
of EKH in mistrusted academic relationships, we provided further specificity to the research
on knowledge hiding, following recent calls (Connelly and Zweig, 2015). While the majority
of respondents acknowledged their practice of evasive hiding when they do not trust
academic colleagues, the occurrence was far from frequent confirming that knowledge
Figure 2 Interaction plot –Trait competitiveness Task interdependence for
within-department evasive hiding of explicit knowledge
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Table IV Hierarchical linear regression analysis results for evasive knowledge hiding as a dependent variable (distal colleagues)
Measure
Explicit EKH Tacit EKH
Model 1 Model 2 Model 3 Model 4 Model 5 Model 6 Model 7 Model 8
BSEBSEBSEBSEBSEBSEBSEBSE
Intercept 2.102 0.295 0.835 0.751 0.783 0.745 0.789 0.748 2.654 0.333 1.323 0.826 1.295 0.827 1.301 0.828
Gender 0.026 0.138 0.125 0.127 0.100 0.126 0.112 0.126 0.022 0.155 0.040 0.139 0.027 0.140 0.034 0.140
Age 0.244 0.113 0.165 0.097 0.163 0.096 0.157 0.096 0.279 0.128 0.221** 0.106 0.219** 0.106 0.217* 0.107
Academic/job tenure 0.055 0.137 0.255 0.196 0.270 0.195 0.268 0.195 0.103 0.154 0.485** 0.216 0.493** 0.216 0.491* 0.216
Academic rank 0.036 0.087 0.128 0.087 0.129 0.087 0.127 0.087 0.119 0.098 0.165 0.096 0.166 0.096 0.165 0.096
Task interdependence ––0.036 0.107 0.041 0.106 0.012 0.107 ––0.014 0.117 0.012 0.117 0.025 0.118
Social support ––0.064 0.092 0.066 0.091 0.032 0.093 ––0.050 0.101 0.051 0.101 0.035 0.103
Personal competitiveness ––0.534*** 0.092 0.541*** 0.091 0.535*** 0.091 ––0.595*** 0.101 0.599*** 0.101 0.596*** 0.101
Prosocial motivation ––0.204** 0.099 0.181 0.099 0.187 0.099 ––0.276** 0.109 0.264** 0.109 0.268** 0.109
Achievement striving ––0.130 0.040 0.057 0.129 0.053 0.130 ––0.017 0.143 0.014 0.143 0.012 0.144
Competitiveness Task interdependence –– – –0.228*** 0.113 – ––– – –0.119 0.126 ––
Competitiveness Social support ––––––
0.166* 0.102 ––––––0.077 0.113
Ftest 2.363 6.577 6.440 6.250 4.079 8.704 7.918 7.854
Adjusted R
2
0.032 0.231*** 0.246*** 0.239*** 0.070*** 0.293*** 0.293*** 0.291***
Notes: The table presents unstandardized regression coefficients and standard errors for each measure; values in italic are relevant for tests of hypotheses; *p<0.10; **p<0.05;
***p<0.01
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hiding is a low base-rate yet high-impact behavior (Cerne et al., 2014). Therefore, we may
conclude that EKH exists among scholars, more frequently within specific boundary
conditions, but it needs to be understood as a small-in-size yet large-in-power
phenomenon. Our results are thus in the line with previous research on knowledge hiding as
a more general behavioral category (Connelly et al.,2012).
The second theoretical contribution is aimed at the knowledge management literature and is
related to further delineating between knowledge types, characteristics of knowledge
holders (potential hiders) and their position vis-a
`-vis requestors. We examined and
confirmed differences in terms of evasively hiding tacit versus explicit knowledge. Our
research also showed that characteristics of the knowledge requestors represent an
important determinant of academic knowledge hiding. Their positional characteristics can
define the nature of an academic work relationship, although initial findings about the effect
of the academic status of the inquirer on academicians’ intent to share knowledge were not
found to be significant (Lee et al.,2010). Nonetheless, very few other studies have touched
upon the nature of different relationship dyads in which knowledge hiding may occur. One
could expect that the knowledge hiders’ motivation will vary with the hiding target (Zhang
and Jiang, 2015), and that mistrusted yet proximal colleagues from the same academic
department will collaborate with each other to achieve mutual goals.
Table V Conditional indirect effects at different values of the moderators
Dependent variable
Task
interdependence Social support
Indirect
effect SE
95%
Confidence intervals
Model 1 2.451 –0.323 0.123 (0.0802, 0.5665)
Explicit EKH
(department)
3.185 0.491 0.092 (0.3095, 0.6718)
3.918 0.658 0.125 (0.4108, 0.9050)
Model 2 –2.169 0.314 0.128 (0.0620, 0.5658)
Explicit EKH
(department)
3.041 0.489 0.092 (0.3074, 0.6698)
3.915 0.663 0.128 (0.4101, 0.9165)
Model 3 2.451 –0.375 0.122 (0.1347, 0.6161)
Explicit EKH
(university)
3.185 0.547 0.091 (0.3676, 0.7262)
3.918 0.718 0.124 (0.4737, 0.9629)
Model 4 –2.169 399 0.127 (0.1484, 0.6494)
Explicit EKH
(university)
3.041 545 0.091 (0.3644, 0.7248)
3.915 0.690 0.128 (0.4385, 0.9420)
Notes: N= 168. Besides mean, values for moderator variables represent 1 SD below and above the
mean thus indicating low and high levels of task interdependence and social support. Indirect effects
in italic indicate significance and the significance tests for the indirect effects were based on bias-
corrected confidence intervals derived from 10,000 bootstrapped samples
Figure 3 Interaction plot –Trait competitiveness Social support for within-department
evasive hiding of explicit knowledge
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Our results were robust for the requestors’ position (distance), which complements the finding of
Cyr and Choo (2010) on knowledge sharing. However, dissimilarities were found in terms of
knowledge type: academics seem to hide tacit knowledge more. It may be that knowledge that is
highly valued gets hidden more, especially toward distrusted, disliked or distant colleagues. This
finding is similar to that of Toma and Butera (2009), although we showed more specifically that
tacit EKH is a motivated process more likely to occu ri n competitive mindset.
The third theoretical contribution is related to the personality literature. We examined how
several individual characteristics (i.e. personal competitiveness, achievement striving and
prosocial motivation) affect knowledge hiding. The competitive personality of some academics
was found to be an antecedent of their EKH in mistrusted academic relationships. We
confirmed the importance of this increasingly addressed individual trait for knowledge hiding
behavior as suggested previously by Connelly et al. (2014). Furthermore, personal
competitiveness was found to be a stronger predictor of EKH than both achievement striving
and prosocial motivation –individual characteristics that might avert this misbehavior. In other
words, the mixed motives and personality have an influence on knowledge management
practices, although their effects might differ both in size and direction.
The fourth theoretical contribution relates to the learning and education literature, and deals
with the managerial remedies in terms of the role of job design in the personal
competitiveness–knowledge hiding relationship in academic settings. We built upon the theory
of co-operation and competition to consider the effect of a competitive personality in
conjunction with two collaborative HRM/job-design characteristics (task interdependence and
social support). The findings of our interaction analyses were consistent for social job
characteristics. Both task interdependence and social support were able to buffer the
relationship between personal competitiveness and EKH for explicit knowledge; however, they
only led to reduced levels of EKH when personal competitiveness was low. This is in line with
previous research that recognized job design as an HRM practice to be desirable for
encouraging knowledge-sharing behavior (Cabrera and Cabrera, 2005). However, increased
levels of task interdependence and social support did not do much good for hiding more
valuable and complex tacit knowledge, which, as our study revealed, occurs more frequently
in mistrusted academic relationships. It seems that social job enrichment provokes strategic
knowledge hiding –it creates a cooperative impression (Steinel et al.,2010)whereknowledge
holders decide not to hide “shared” or “less expensive” knowledge, but they are prone to
conceal “unshared” or high-value knowledge that represents the idea of differentiation
required for attaining a higher status. Our findings indicate that scholars’ competitiveness
motives seem to shape academic behaviors more strongly than collaboration-enhancing job-
design initiatives in the case of valuable tacit knowledge, as well as when scholars have a
pronounced competitive personality. Apparently, personality traits do play an important role in
determining the nature of social exchange relationships, and thus require more attention in
future knowledge management research endeavors.
Practical implications
From the perspective of those who manage higher-education institutions or make knowledge
management decisions in general, our research has several practical implications. Above all,
leaders of business schools should acknowledge that EKH, while being incompatible with
academic values, does happen among academic colleagues. Turning a blind eye is
destructive both for individuals and the institutions involved and previous research shows that
it is even damaging to the knowledge hiders themselves (Cerne et al.,2014). An important
question, then, is what can academic leaders do about it? Our study shows that employment
decisions might affect knowledge-exchange in academic settings. The results suggest that
higher-education institutions should be cautious when recruiting job candidates with
competitive personality traits. Instead, academic departments should seek collaborative
individuals whose personal characteristics are more congruent with the open and communal
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components of the scientific ethos (Merton, 1973), rather than with an industrial science
environment that is predominantly competitive and guided by confidentiality and secrecy
(Haeussler, 2011). There are also some benefits in designing academic tasks in
interdependent manner as well as providing social support by department chairs and
teaching/research groups, touching upon the relational aspects of scholars’ job design. The
same holds for designing socially enriched jobs as part of establishing general knowledge
management systems in organizations.
Knowledge hiding is common within contemporary work settings (Peng, 2013). Therefore,
sharing/hiding considerations need to be taken seriously and extended far beyond the context
of academic knowledge, because they permeate almost every aspect of organizational life
(Costas and Grey, 2016). The knowledge hiding phenomenon can lead to particularly
detrimental consequences in academic settings (such as terminations of academic
collaborations reported in the study by Campbell et al.,2002), where individuals are expected
to share knowledge and collaborate to educate, conduct better research and advance
science. Nonetheless, knowledge hiding apparently exists in the academia. In many instances,
scholars paradoxically hide their knowledge even though the nature of the academic
processes requires sharing and dissemination, or when organizational practices are designed
to facilitate knowledge transfer. EKH in mistrusted academic relationships is fostered by
individual traits (personal competitiveness) and knowledge type (tacit), in addition to emerging
achievement- and competition-oriented reward and promotion systems throughout the
academia. Therefore, it is imperative for universities, as well as for other types of knowledge-
intensive organizations, to understand the tools that can help mitigate this occurrence. In such
circumstances, even though knowledge hiding can neither be completely controlled by an
organization nor weakened through the development of knowledge sharing habits (Serenko
and Bontis, 2016), job design might help to reduce the incidence of explicit EKH.
We propose that to discourage knowledge hiding, organizations should develop and
introduce HRM policies and practices based on collaboration-oriented job characteristics,
and by simultaneously taking into account their employees’ individual traits. This has
important implications for knowledge management; in addition to developing organizational
policies and procedures, managers should strive to create work-related policies and
introduce job requirements that encourage frequent interactions among researchers, which
might help to build personal relationships and trust (Nelson, 2016) and thus potentially
result in fewer mistrusted relationships. Our recommendation is in line with
recommendations posited by Foss et al. (2009): for jobs where knowledge relevant to others
is created, organizations should foster either intrinsic or introjected motivation to enhance
the likelihood of knowledge sharing among mistrusted colleagues. This can be done by
formally increasing collaboration during research and teaching processes (e.g. by
increasing task interdependence through co-teaching, stimulating joint collaborative
departmental or even interdisciplinary research), as well as by providing expert services
(e.g. by organizing communities of practice that would consist of faculty members from
different departments, capitalizing on knowledge maps to locate expertise on issues faculty
members are struggling with or appointing specific faculty members to help others to solve
explicit work-related problems during separate office hours).
Research limitations and future research suggestions
Despite the many contributions of this research, some limitations must be acknowledged. The
first limitation of our study is related to the fact that our cross-sectional data prevent us from
making conclusive causal claims about the direction of the hypothesized relationships. This
concern is somewhat mitigated by the fact that the posited associations were grounded in
organizational behavior theory, whereas analytical techniques applied (i.e. ordinary least
squares regression models) are common in the field of knowledge management (for example,
see Cabrilo and Dahms, 2018;Papa et al.,2018). However, future research should involve
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longitudinal or experimental studies that could rule out possible alternative explanations. We
also encourage the usage of complementary analytical techniques such as conditional
process analysis (Jeung et al., 2018) that may offer additional insights.
The second limitation of this work is related to our use of self-report data. Indeed,
underreporting could have led us to underestimate the frequency with which faculty hide
their knowledge from the academic community. The given results likely constitute a lower
bound estimate of the proportion of academics who actually participate in this misbehavior,
because respondents are often reluctant to admit to engaging in behaviors that are
perceived as undesirable or viewed as contrary to accepted norms of practice. However,
because knowledge hiding is a low-base rate event, meta-analytic evidence (Duckworth
and Kern, 2011) suggests that using self-report data gathering strategies actually enable
researchers to capture a broader array of such behaviors.
The third potential limitation of our study is related to the sampling strategy; we only focused
on business/economics scholars from a single country. Specifics related to this disciplinary
field might drive the results. Several studies have already pointed to differences in values-
related behavior between economists and others (Gandal et al.,2005). For example,
Marvell and Ames (1981) found that free-riding was significantly higher among economists
than other highly educated groups. This might be true because economists are trained to
value rational self-interested behavior. It would be interesting to examine whether the results
hold across technical, life sciences or humanities. In addition, when studying knowledge
hiding in academic settings, we should also consider the contextual role of faculty culture.
Specifically, we would benefit from learning more about the influence of (a) the culture of the
academic profession, (b) the culture of the disciplinary field, (c) the culture of the individual
scholar, (d) the culture of the academic institution and (e) the national culture on knowledge
hiding in academia. Equally important would be to test for differences in knowledge hiding
behavioral patterns between scholars from private and public higher-education institutions.
Future research on knowledge hiding in academia should also delve into researchers at different
academic ranks/positions. For instance, a recent study by Demirkasimoglu (2016) found
significant differences in terms of EKH behaviors between research assistants and assistant
professors toward their superiors. Sharing/hiding knowledge with a leader or direct supervisor
could involve considerations different from sharing/hiding with a colleague (Cyr and Choo, 2010).
The competitive pressure is likely to be particularly present in early- and mid-career researchers,
who are working on their reputation and strive for recognition. Therefore, future research should
look into the reasons why and how knowledge is being hidden, i.e. how much of it goes beyond
personality traits and occur because of hig hly competitive settings, and to what extent knowledge
hiding tactics for managing sharing/secrecy tensions (Nelson, 2016) depend upon academics’
involvement and dedication to the university or acad emic work in general.
Conclusion
Knowledge hiding in academic settings is a mixed-motive behavior that contains elements
of both collaboration and competition. This unexpected and undesirable organizational
paradox is still under-investigated. Therefore, we decided to explore how person–situation
interactions might determine the level of this specific type of organizational misbehavior.
Our findings reveal that personal competitiveness is a driving factor of knowledge hiding
within mistrusted academic relationships, whereas relational job-design characteristics (i.e.
task interdependence and social support) successfully diminishes the effects of negative
personality trait when explicit knowledge is requested. However, socially enriched job
design is less efficient if you ask a mistrusted and competitive academic colleague to share
his or her tacit knowledge. Knowledge management issues have to be examined not only
from technological or economic but also from sociological and psychological perspectives.
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Although we covered a relatively large sample of scholars from an EU member state, our
insights might be culturally biased. For that reason, it would be valuable to consider
institutional and cross-national differences related to idiosyncratic academic settings and
specific reward/promotion criteria. Nevertheless, given the potential implications of
mitigating the occurrence of knowledge hiding within academia, it behooves us to further
deepen our understanding of this complex phenomenon.
Acknowledgements
The authors are grateful to Kenneth G. Brown, Marjolein Canie
¨ls and Anders Dysvik for providing
useful comments on the earlier version of the paper, and to Ana Aleksic for her assistance with
data collection. They acknowledge the anonymous re viewer who brought this paper to attention.
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Corresponding author
Tomislav Hernaus can be contacted at: thernaus@efzg.hr
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