JAIST Repository
https://dspace.jaist.ac.jp/

Title

Counterproductive knowledge behavior involunteer work: perspectives from the theory ofplanned behavior and well-being theory

Author(s)Shirahada, Kunio; Zhang, Yixin

Citation

Journal of Knowledge Management

Issue Date

2021-11-17

Type

Journal Article

Text version

author

URL

http://hdl.handle.net/10119/17609

Rights(c)Kunio Shirahada and Yixin Zhang. Published by
Emerald Publishing Limited. This article ispublished under the Creative Commons Attribution(CC BY 4.0) licence. Anyonemay reproduce,
distribute, translate and create derivative works ofthis article (for both commercial and noncommercial purposes), subject to full attribution tothe original publication and authors. The full termsof this licence maybe seen at
http://creativecommons.org/licences/by/4.0/legalc
odeDescription

This work was supported by JSPS KAKENHI Grant
Number
20H01529 and JAIST Open Access Paper Support
Project.

Japan Advanced Institute of Science and Technology

Counterproductive Knowledge Behavior in Volunteer Work:
Perspectives from the Theory of Planned Behavior and Well-Being Theory
By

Kunio Shirahada and Zhang Yixin
Japan Advanced Institute of Science and Technology
Mail: kunios@jaist.ac.jp
DOI: 10.1108/JKM-08-2021-0612

Abstract
Purpose: This study identifies the counterproductive knowledge behavior (CKB) of volunteers in
nonprofit organizations and its influencing factors, based on the theories of planned behavior and wellbeing.
Design/methodology/approach: An online survey was used to collect 496 valid responses. A
structural equation model was constructed, and the relationships among the constructs were estimated
via the maximum likelihood method. To analyze the direct and indirect effects, 2,000 bootstrapping
runs were conducted. A Kruskal-Wallis test was also conducted to analyze the relationship between
the variables.
Findings: A combination of organizational factors and individual attitudes and perceptions can beused to explain CKB. Insecurity about knowledge sharing had the greatest impact on CKB. A
competitive organizational norm induced CKB, while a knowledge-sharing organizational norm did
not have a significant impact. Further, the more self-determined the volunteer activity was, the more
the CKB was suppressed. However, well-being did not have a significant direct effect. Volunteers withhigh levels of well-being and self-determination had significantly lower levels of insecurity aboutknowledge sharing compared to those who did not.
Originality: There is a lack of empirical research on CKB in volunteer organizations; therefore, we
propose a new approach to knowledge management in volunteer activities.
Practical implications: Well-being arising from volunteering did not directly suppress CKB. To
improve organizational efficiency by reducing CKB, non-profit organization managers should provide
intrinsically motivating tasks and interact with the volunteers.
Keywords: counterproductive knowledge behavior; volunteering; nonprofit organizations; wellbeing; theory of planned behavior
Classification: Research paper

Acknowledgement: This study is supported by JSPS KAKENHI Grant Number 20H01529

Introduction
The nonprofit sector plays an important role to resolve social problems. Nonprofit organizations(NPOs) require volunteers with diverse skills and backgrounds, who come together and shareknowledge (Grant, 1996), thereby creating social value (Lettieri et al., 2004). However, knowledge
sharing in organizations does not happen automatically (Davenport and Prusak, 1998), andcounterproductive knowledge behaviors (CKB), such as knowledge hiding (i.e., intentionally avoiding
the sharing of knowledge) are frequent (Connelly et al., 2012). It undermines organizational efficiency
and NPOs’ ability to ameliorate social issues.
The consequences of deliberate knowledge hiding behavior in organizations can not only undermine
their efficiency and but also reduce opportunities for volunteers to obtain non-monetary rewards fortheir activities (Wilson and Musick, 1997). Volunteering can help improve physical and mental health(Dury et al., 2014; Morrow-Howell et al., 2003). It can also increase hedonic well-being (Diener,
1984), such as positive emotions (O’Shea, 2006; Pavlova and Silbereisen, 2012; Rebok et al., 2004),
and eudaimonic well-being (Keyes, 1998), such as fulfillment through role awareness (Greenfield andMarks, 2004) and personal growth (Macleod et al., 2016). If organizational members realize that theygain well-being from their activities, they may be motivated to display more productive knowledge
behaviors and avoid CKBs.
This study identifies the CKB of volunteers at NPOs and its influencing factors. We employed thetheory of planned behavior (TPB) framework (Ajzen, 1991), which explains intentional behavior fromthe perspective of organizational pressure and individual attitudes and perceptions. The selfdetermination theory (Ryan and Deci, 2000) that posits self-determination as a leading factor
responsible for well-being creation and the concept of trustworthy relationships within an organization(Martín-Alcázar et al., 2019) were also used. Research on CKB as the dark side of knowledge
management has progressed in the last decade, especially in the context of corporate settings (Serenko,
2019). Meanwhile, knowledge management research on NPOs has demonstrated the effectiveness ofknowledge sharing among members (Mohd Noor et al., 2015) and between organizations (Rathi et al.,2014) on organizational effectiveness. Knowledge management systems (Huck et al., 2011) that
promote knowledge sharing among volunteers have also been developed. These studies take thestandpoint of promoting productive knowledge behavior. However, few studies have analyzed CKB
in NPOs by integrating empirical data on organizational behavior and participants’ well-being.

Theoretical Background and Hypothesis Development
Counterproductive Knowledge Behavior

Knowledge management is responsible for promoting knowledge sharing to increase organizational
efficiency and effectiveness (Davenport and Prusak, 1998). In the past, the SECI (SocializationExternalization-Combination-Internalization) model (Nonaka and Takeuchi, 1995) that uses the
dynamics of organizational knowledge creation to effectively share individual knowledge and turn it
into organizational knowledge, and the theory of “Ba” (Nonaka and Konno, 1998) that puts the SECI
model into practice were developed. Knowledge sharing and creation are now very important
processes for organizational capacity building. However, the transfer of best practices into
organizations is not easy. Szulanski (1996) argued that this is due to the lack of absorptive capabilityof the recipient, uncertainty about the effect of the knowledge being transferred (causal ambiguity), an
arduous relationship between the source and the recipient, and proposed a knowledge transfer model(Szulanski, 2000). However, these seminal studies seem to assume that members of an organization
are motivated to share effective knowledge. Nevertheless, knowledge sharing among organizational
members is not obligatory (Davenport, 1997; Li et al., 2020). Rather, CKB, such as intentionally notsharing knowledge or transferring incorrect knowledge, are frequently observed (Serenko, 2019). The
CKB has negative effects on task performance (Chatterjee et al., 2021; Singh, 2019), teamperformance (Wang et al., 2019), and creativity (Chen et al., 2020; Peng et al., 2019). Consequently,
the factors causing CKB have recently attracted attention in knowledge management research (Issac
et al., 2021; Di Vaio et al., 2021; Xiao and Cooke, 2019).
A well-known type of CKB is knowledge hiding, which is “an intentional attempt by an individual towithhold or conceal knowledge that has been requested by another person” (Connelly et al., 2012;p.65). Originally, three kinds of knowledge hiding behaviors were observed: playing dumb, evasivehiding, and rationalized hiding (Bari et al., 2020; Connelly et al., 2012). The mechanisms of not
sharing knowledge and knowledge hiding are not identical. Not sharing knowledge may occur
unintentionally due to the individual’s poor communication skills (Ford et al., 2015) or lack ofshareable knowledge (Connelly et al., 2012). In contrast, knowledge hiding behavior is intentional ina particular context. Intentional CKB includes knowledge hiding, partial knowledge sharing (Ford andStaples, 2010), counter-questioning knowledge hiding (Jha and Varkkey, 2018; Zhai et al., 2021),
bullying knowledge hiding (Yuan et al., 2020), counter-knowledge sharing (Bolisani and CegarraNavarro, 2021), and knowledge sabotage (Serenko, 2019). Though rarely observed, the distribution ofincorrect knowledge significantly impacts organizations (Serenko, 2019, 2020). In this study,
knowledge hiding and partial knowledge sharing, which are more common and should be assessedfrom the perspective of organizational efficiency, are considered as CKBs.

Theory of Planned Behavior: TPB

The TPB is used to predict and explain the intentions behind human behavior in a particular context(Ajzen, 1991). Intention refers to the effort that individuals put into a behavior and is influenced bythree elements: subjective norms, attitudes, and perceived behavioral control. Subjective norms referto the expectations of others and social pressures regarding whether a behavior should be performed.
Meanwhile, attitudes refer to the favorable or unfavorable evaluations of a behavior, and perceived
behavioral control refers to the ease/difficulty of performing a behavior. In other words, the TPB is aframework to explain the background of individuals’ intentional behavior in terms of theorganizational climate’s influence and their attitudes and perceptions toward organizational behavior,considering them as organizational personnel (or personnel who belong to some community or group).
Socially desirable behavior is the theme of many TPB studies. Knowledge management research has
adopted TPB to understand knowledge sharing in business settings (Chennamaneni et al., 2012; Jeonet al., 2011; Lin and Lee, 2004; Ranasinghe and Dharmadasa, 2013), educational settings (Göksel andAydintan, 2017), and online communities (Alajmi, 2012; Erden et al., 2012; Kuo and Young, 2008;
Zhao et al., 2016). The three elements of the TPB framework focus on organizational pressures andindividual perceptions of knowledge sharing (e.g., Gagné, 2009), although they vary slightly acrossresearch topics. However, in the results of a meta-analysis of 26 studies analyzing knowledge sharing
via the TPB until 2017, eight out of 26 extended the original TPB model to the context of knowledge
sharing, while 18 added their own supplementary factors (Nguyen et al., 2019). Thus, the constructionof analytical models based on the TPB permits flexible design according to the research target.

Counterproductive Knowledge Behavior and the TPB
The TPB has explanatory power for dishonest actions, such as cheating and lying in tests (Beck andAjzen, 1991). Since CKB can be considered a dishonest action, we assume that the application of the
TBP framework is appropriate in examining its mechanism. Xiong et al.’s (2021) qualitative study on
the antecedents of CKB among R&D personnel found that the three elements of the TPB may have
explanatory power in knowledge hiding behavior; thus, we hypothesize:
Hypothesis 1: CKBs such as knowledge hiding and partial knowledge sharing can be explained by the
TPB framework.

The main facet of subjective norms in the TPB view is the impact of organizational pressure on CKB.
Competitive work environments (Anand et al., 2020; Qureshi and Evans, 2015) and time pressure(Škerlavaj et al., 2018) can promote knowledge hiding. In a competitive organizational environment,
those who achieve rapid results have an advantage, which may cause organizational members to lose
the incentive to share knowledge or to intentionally hide knowledge. On the contrary, the formationof a knowledge-sharing climate is encouraged in many organizations as a form of knowledgemanagement that aims to increase efficiency (Davenport and Prusak, 1998). Sharing knowledge withothers basically requires a cooperative relationship, which promotes positive characteristics amongorganizational members, such as a willingness to enhance the power of the other through effective
communication, while competitive relationships tend to have negative effects, such as the motivation
to reduce the power of the other (Deutsch, 2006). Banagou et al. (2021) examined the relationshipamong human personality, cooperative organizational climate, and knowledge hiding, and found thatpeople with high openness hide knowledge less under a high communal sharing climate. However, theeffect of a knowledge-sharing organizational climate on CKB in relation to a competitive
organizational climate has not been demonstrated. Under the conflicting organizational pressures ofcompetition and cooperation, organizational members, who are aware of the competitive environment,
may distort the meaning of knowledge sharing and be motivated to share superficial knowledge. In
this context, it is difficult to fully determine whether the organization’s knowledge-sharing climate is
positive or negative, and how it affects CKB. Thus, we formulate the following two hypotheses
including the exploratory oriented hypothesis 1.1 (b):Hypothesis 1.1 (a): As a subjective norm element of the TPB, the perception of an organization’scompetitive climate positively affects volunteers’ CKB.
Hypothesis 1.1 (b): As a subjective norm element of the TPB, the perception of an organization’s
knowledge sharing climate has an impact on the volunteers’ CKB.

In the original TPB approach, preferences for CKBs (like/dislike, attractive/unattractive, etc.) might
be recommended to identify the attitude toward the behavior. However, questionnaire surveys require
respondents to make ethical judgments. In a study that applied the TPB to dark side behaviors, ethicalattitudes did not have sufficient explanatory power as a background for deviant behavior (Beck andAjzen, 1991); i.e., even if the importance of ethical attitudes about socially unacceptable behavior is
known, actual behaviors often differ from these attitudes. Therefore, we examine attitudes towardknowledge sharing, which is considered socially “good” rather than directly examining attitudes
toward CKB, which is considered socially “bad.”
Therefore, in this study, we set the sense of psychological ownership of knowledge as an attitudinalelement in the TPB. Knowledge sharing is “a set of individual behaviors involving sharing one’s workrelated knowledge and expertise with other members within one’s organization” (Yi, 2009, p.68),
which implies sharing knowledge ownership with others. However, since it is difficult to see theownership of knowledge (Grant, 1996), psychological ownership becomes important. The
psychological ownership that knowledge creators have over their discoveries (Jha and Varkkey, 2018)creates a territorial sense of knowledge, which leads to knowledge hiding (Bhattacharya and Sharma,
2019; Huo et al., 2016; Li et al., 2020; Peng, 2013). In addition, negative attitudes toward sharing

psychological ownership of knowledge promote partial knowledge sharing (Ford and Staples, 2010).
Therefore, to judge the appropriateness of introducing the psychological ownership of knowledge into
the TPB framework, we suggest:
Hypothesis 1.2: As an attitudinal element of the TPB, the sense of psychological ownership ofknowledge positively affects CKB.

For perceived control, the question is whether CKB is easy or difficult to perform. However, CKB in
this study refers to intentional CKB in response to requests from others, which is a context-dependent
behavior. Xiong et al. (2021) noted that the sense of perceived control varies depending on whether
the target of the CKB is smart or not, which is difficult to estimate in advance. The knowledge hider
often discovers later whether the knowledge seeker is smart, and the former’s estimates are sometimes
wrong. Therefore, we focus on insecurity about knowledge sharing, which depends on context rather
than self-efficacy over CKB. An individual’s lack of confidence in their knowledge (Jha and Varkkey,2018) can induce knowledge hiding. In addition, the fear of losing one’s advantage while sharing
knowledge (Koay et al., 2020) can influence rational knowledge hiding, i.e., not sharing knowledge
for plausible reasons. Thus, we hypothesize:
Hypothesis 1.3: As an element of the TPB’s perceived control, insecurity about knowledge sharing
positively affects CKB.

Counterproductive Knowledge Behavior and Well-being
Well-being generally refers to happiness. In psychology, well-being is based on subjective perceptions,and there is a vast amount of research on this topic (Diener, 1984). There are two research traditions:eudaimonic well-being, which focuses on functioning in life, and hedonic well-being, which focuses
on feelings about life (Keyes, 2006). Eudaimonic well-being is a state of possession of human potentialthat can lead to positive functions in life (Keyes, 2006; Ryff and Singer, 1996). Volunteering gives
participants a sense of purpose through role identification (Greenfield and Marks, 2004) and allows
them to experience personal growth (Macleod et al., 2016). Therefore, volunteering without losing
sight of one’s intrinsic motivation for the activity (Ryan and Deci, 2000) is thought to inhibit CKB
because counterproductive behaviors decrease volunteers’ ability to thrive (Jiang et al., 2019), which
is an obstacle to well-being creation. Thus, we formulate the following hypothesis:
Hypothesis 2.1: The creation of organizational members’ well-being positively affects CKB.

Self-determination (Ryan and Deci, 2000) is considered an important driving force in eudaimonic
well-being creation. Self-determination includes autonomy, competence (the perception of highperformance), and relatedness (the perception that the results of one’s activities are related to others)(Ryan and Deci, 2000). This is also relevant to the concept of psychological well-being as a form ofeudaimonic well-being. Ryff and Singer (1996) proposed the concept of psychological well-being byfocusing on mental health and discovered the positive meaning of being mentally healthy, which
includes self-acceptance, autonomy, and environmental mastery (Ryff, 1989; Ryff and Singer, 1996,2008). A sense of burnout at work also impacts knowledge hiding (Ali et al., 2021). If an individual
loses sight of the purpose of their work or is not satisfied with their performance, they may conceal
knowledge. In other words, when people are self-determined, they are not likely to choose CKBs.
Thus, we hypothesize:
Hypothesis 2.2: Organizational members’ sense of self-determination negatively affects CKB (directly
and indirectly mediated by well-being).

Hedonic well-being, meanwhile, is based on the human tendency to maximize the amount and durationof positive, pleasant emotions and minimize negative, unpleasant emotions, and it attempts tounderstand well-being in terms of both cognitive judgments and emotional responses (Diener, 1984;
Diener et al., 1985). Negative emotions cause knowledge hiding behaviors (Ali et al., 2021; Koay etal., 2020); in particular, emotional distrust in relationships within an organization leads to knowledge
hiding (Pereira and Mohiya, 2021; Su, 2021; Yuan et al., 2020). For example, experiences of
mistreatment (Rasheed et al., 2020) and disrespect (Irum et al., 2020) elicit negative emotions andproduce knowledge hiding behavior. Knowledge hiding due to distrust is more likely to occur in theearly years of employment, when relationships are not yet mature (Issac et al., 2020). Distrust ininterpersonal relationships not only causes stress in the form of interpersonal conflicts but also
deprives organizational members of a positive mood. This process results in the depletion of resources
and a defensive posture to preserve remaining resources, which leads to knowledge hiding (LosadaOtálora et al., 2021). However, organizational members may inhibit knowledge hiding behavior bytrusting, and being trusted by others (de Geofroy and Evans, 2017). This process implies the creationof well-being through the construction of human relationships. Positive emotions enable people tocope better with problems in the organization and inhibit knowledge hiding (Jahanzeb et al., 2020).
Thus, we hypothesize:
Hypothesis 2.3: Trustworthy relationships in the organization negatively affect CKB (directly andindirectly mediated by well-being).

Research Framework
The study’s hypotheses are illustrated in Figure 1. The mechanism of CKB as an intentional behavior

in volunteer activities was analyzed from two different perspectives. The first is based on the TPB
perspective of volunteers as members of NPOs, while the second is based on volunteer participants
being autonomous individuals. The “trustworthy relationships” factor related to positive emotions, andthe “degree of self-determination” factor related to eudaimonic well-being. This study integrates
organizational and individual well-being perspectives and identifies the relationship among the two
perspectives and CKB in volunteer activities.
After testing the hypotheses, we investigated the relationship between the most influential TPB-related
and well-being-related factors to understand the relationship between finding meaning in volunteering
as a form of individual well-being creation and the perception of knowledge sharing as anorganizational member.
[Insert Figure 1]

MethodSample and Data Collection
Data were collected through a survey panel of Macromill, a Japanese internet research company.
Online surveys provide more demographically diverse samples than other methods, while thereliability of their data is comparable (Buhrmester et al., 2011). However, the participants may
sometimes respond multiple times (Wright, 2017). The Macromill system does not allow double
responses, and responses with extremely short response times are not registered. Questions with thesame content presented in different ways were also created to prevent bogus responses.
The survey was conducted between March 12–14, 2021. The screening conditions were (i) those whocurrently belonged to a volunteer organization, and (ii) those who participated in the organization’s
activities (before the COVID-19 pandemic) for more than four days in a year (more than one day every
three months). Since the research topic was knowledge sharing in volunteer organizations, regularparticipation in volunteer activities was considered important. In total, 552 data items from
respondents in the age group 30-70 or older were collected during the survey period, of which 496
were valid, excluding 42 with clearly contradictory answers and 14 in which the respondents answeredthat on average only one person participated in the activities. The respondents’ basic information isshown in Table I.
[Insert Table I]
Measurement Items

The scales used in this study (listed in Table II) were based on those that have been tested and validated
in previous research. To measure organizational climate, we applied Lei et al. (2019) and Nerstad etal.’s (2013) scales and fit them into the context of knowledge behavior. To measure insecurity aboutknowledge sharing as a perceptual control, we created questions about the anxiety in sharing
knowledge by referring to the concept of knowledge power loss, which is the perception of power andunique value loss due to knowledge contributed to others (Kankanhalli et al., 2005). The psychologicalownership of knowledge was tested by applying Avey et al.’s (2009) research to knowledge behavior.
To examine knowledge hiding, we used Connelly et al.’s questionnaire (2012), and for selfdetermination, we used the basic ideas of self-determination theory (competence, autonomy,
relatedness, and intrinsic motivation) (Ryan and Deci, 2000). The concept of trustworthy humanrelationships was developed from the social capital theory (Coleman, 1988), with a particular focus
on the trust-focused relational dimension (Martín-Alcázar et al., 2019). Well-being gained fromvolunteer activities was captured using items based on psychological well-being (Ryff and Singer,
1996), which was studied mainly from the perspective of the benefits that good mental health andbeing in good physical shape offers.
The responses were measured using a Likert scale with responses from 1 (strongly disagree) to 5
(strongly agree). While the TPB is a particularly useful framework to consider the effects on behavioral
intentions, it is difficult to measure the intentions that could lead to behaviors using a questionnaire,
and the essential issue is whether the behavior was actually implemented (Kuo and Young, 2008;
Nguyen et al., 2019). Therefore, we considered CKB to be an intentional behavior and asked
respondents whether they engaged in it.
[Insert Table II]
The measures of the internal consistency of the constructs (Cronbach’s α, Average Variance Extracted(AVE), and Composite Reliability (CR)) are shown in Table II, while the constructs’ validity and thecorrelation between the constructs are shown in Table III. All constructs were greater than 0.5 except
for “knowledge sharing organizational norm” that had an AVE value of 0.48, which was very close to
the cutoff value of 0.5 (Gefen et al., 2000; Peter, 1979). The CR values ranged from .73 to .91. It is
desirable for α to be greater than 0.7, AVE to be greater than 0.5 (Fornell and Larcker, 1981; Joe et al.,2014), and CR to be greater than 0.7 (Grewal et al., 2004). Our results showed low AVE and CR values
for some constructs; however, Cronbach’s α, which was above 0.7, showed that the data had sufficientreliability and convergent validity.
Discriminant validity indicates the extent to which the constructs differ (Erden et al., 2012). As shownin Table III, this can be confirmed by comparing the square root of the AVE with the correlation of theother constructs (Fornell and Larcker, 1981). The results showed that the AVE values were more

correlated than the other constructs, meaning that each construct was perceived to be different fromthe others.

Analysis
Since the internal consistency of the constructs was ensured, the mean value of each observed variable
was used as the score of the construct. For example, the competitive organizational climate wasrepresented by the average value of the three observed variables. A structural equation model wasconstructed based on the analytical model shown in Figure 1, and the relationships among theconstructs were estimated using the maximum likelihood method (Kline, 2015) using Stata17. Since
the model included mediation effects, we conducted 2,000 bootstrapping runs to obtain confidence
intervals, which allowed us to analyze the direct and indirect effects (Preacher and Hayes, 2008;
Preacher and Kelley, 2011).
The relationship between individual perceptual and attitudinal elements related to intentional behavior
and the well-being obtained from the activity and its major antecedents was examined based on thetest of difference. First, normality tests were conducted for individual perceptions and attitudinalelements related to intentional behavior. The variables did not satisfy normality; therefore, as a
nonparametric analysis, Kruskal-Wallis tests were conducted on the individual perceptual andattitudinal elements related to intentional behavior, with self-determination and well-being as
conditional variables, to analyze whether there were significant differences among the items.
Thereafter, the Dunn test was conducted as a post-hoc test to identify those categories that hadsignificant differences.

Results
The mean scores for counterproductive behaviors were all in the 2-point range (Table III); however,
the NPO volunteers did perform CKBs. In particular, the mean score for partial knowledge sharing
was relatively high, thus indicating that knowledge senders do not always teach knowledge seekers
everything they know but transfer knowledge at some cost to the seekers. This result may appear tobe an educational form of knowledge sharing; however, the correlations with “playing dumb” and“evasive hiding” were high (r=.78 and r=.80, respectively). Therefore, it cannot necessarily beconsidered an educational behavior. The CKB also negatively correlated with generation and years ofservice in the NPO.
[Insert Table III]Regarding the structural equation modeling (SEM) analysis, the goodness of fit of the structural
equation model was Chai-square (27)=34.349, p=.156, CFI=.997, TLI=.996, RMSEA=.023,
SRMR=.019. If the SRMR and RMSEA scores are less than .07 and the CFI and TLI scores are greaterthan .90, the model fit is good (Hopper et al., 2008; Hu and Bentler, 1999). Therefore, this study’s
model fit the data well, which also means that the TPB framework explains CKBs such as knowledge
hiding and partial knowledge sharing. Figure 2 and Table IV show the standardized path coefficientsand significance levels associated with the hypotheses. H1.1(a) was supported by the high significancelevel (p<.001) for the relationship between the TPB elements and CKB. H1.2 and H1.3 were also
confirmed by the high level of significance (p<.001). Among the three elements in the TPB framework,
CKB was most influenced by “insecurity about knowledge sharing” as a perceived control (β=.38;
p<.001), followed by the “competitive organizational norm” as a subjective norm (β=.31; p<.001), and“psychological ownership of knowledge” as an attitude (β=.24; p<.001). An organizational norm thatencourages knowledge sharing, however, did not have a significant path coefficient.
[Insert Figure 2]
Regarding the hypothesis on well-being creation, H2.1 and H2.3 showed no significant pathcoefficient; therefore, they were discarded. However, for H2.2, the direct effect of self-determination
on CKB had a significant negative path (β=-.14; p<.05), i.e., the effect of “degree of self-determination”
on CKB before the inclusion of mediation effects. The mediation effect of well-being from the “degreeof self-determination” to CKB was not significant (β=-.01, n.s.). The “degree of self-determination”
had a significant effect on well-being creation in volunteer activities (β=.62; p<.001); thus, well-being
creation does not necessarily affect the promotion/suppression of CKB. However, the combination of
the direct and indirect effects of the degree of self-determination on CKB had a negative pathcoefficient and was significant at the 1% level (β=-. 14; p<.01), thereby indicating that increased selfdetermination suppresses CKB.
[Insert Table IV]
To understand the relationship between the TPB perspective and the well-being perspective withregard to CKB, we analyzed relationships among “insecurity about knowledge sharing,”“psychological knowledge ownership,” “well-being creation,” and “degree of self-determination.”
Since the variables “insecurity about knowledge sharing” and “psychological knowledge ownership”
were non-parametric data that did not satisfy normality, quartiles were derived for the degrees of wellbeing creation and self-determination, and four classes were defined. Kruskal-Wallis tests wereconducted to find differences between the non-parametric data.
The Kruskal-Wallis test showed a significant difference (chi2(3) = 32.615, p<.001) between the fourgroups based on “well-being creation” and “insecurity about knowledge sharing.” Pairwise

comparisons using the Dunn test showed a significant difference between the groups in the fourth
quartile compared to the other groups (first quartile (p<.001); second quartile (p<.001); third quartile(p<.001)). In addition, there was a significant difference (chi2(3) = 11.271, p= .01) between the fourgroups based on the degree of self-determination against respondents’ “insecurity about knowledge
sharing.” Pairwise comparisons using Dunn’s test observed a significant difference between the groups
in the fourth quartile compared to the other groups (first quartile (p<.01); second quartile (p<.05)).
There was also a significant difference (chi2(3) = 20.777, p<.001) between the four groups based on
the “degree of well-being” for “possession of a sense of psychological ownership of knowledge.”
Further pairwise comparisons using the Dunn test revealed a significant difference between the groups
in the fourth quartile compared to the other groups (first quartile (p<.01); second quartile (p<.01); third
quartile (p<.001). However, there was no significant difference in the possession of psychologicalknowledge ownership among the four groups based on the degree of self-determination (chi2(3) = .802,
p= .849).

Discussion
Theoretical Implications
This study determined the kind of CKBs that NPO volunteers tend to engage in and the factors that
contribute to these behaviors in terms of TPB and well-being. There were three distinctive findings.
The first was that CKB, especially partial knowledge sharing, occurs in volunteer activities. The study
explained the mechanism of CKBs through a combination of organizational factors, individual
attitudes, and perception factors. In particular, insecurity about knowledge sharing was the mostsignificant factor that affected CKBs. When organizational members are concerned that knowledge
sharing will dissipate their knowledge advantage or negatively affect their beliefs, they intentionallyconceal their knowledge.
Further, since H1.1(a) was supported while H1.1(b) was rejected, an organizational knowledge-sharing
norm did not significantly impact CKB, but a competitive organizational norm induced CKB. Since
there was no statistically significant correlation between organizational knowledge-sharing norm andcompetitive organizational norm, volunteers perceive cooperation and competition as separate entities.
The results suggest that no matter how actively an organization promotes a knowledge-sharing culture,when individuals perceive competition-oriented cultural norms (e.g., the perception that theorganization prioritizes high performers over others), they tend to conceal their knowledge. Thisbehavior indicates that the tendency of competitive environment in a company promoting knowledge
hiding and sabotage (Oubrich et al., 2021; Serenko and Choo, 2020) is also found in NPOs.

Furthermore, this finding suggests that knowledge sharing and CKB are fundamentally distinct andthat promoting knowledge sharing has no positive or negative effect on CKB. It empirically supports
the findings of existing research that knowledge sharing and knowledge hiding are formed throughdifferent mechanisms (Connelly et al., 2012), and extends it to the NPO context.
The second finding revealed that the more self-determined volunteers are, the more they tend to
suppress CKBs. Previous studies on self-determination theory and knowledge hiding have notsufficiently represented knowledge senders’ perspectives. When knowledge seekers perceive that theircounterparts have concealed knowledge, they are intrinsically motivated to adjust the negative
psychological effects they have experienced and perform better to reduce the hider’s knowledge
advantage (Wang et al., 2019). However, this study showed that the self-determination mechanism
also works in the CKB of knowledge senders.
Previous studies have shown that reduced well-being at work promotes CKB (Ali et al., 2021);
however, this study did not find a direct negative relationship between well-being and CKB. Moreover,
we found that volunteers who had high levels of well-being and self-determination had significantly
lower insecurity about knowledge sharing than those who did not. When the participants increase theirwell-being through volunteering, they might become confident in knowledge sharing within theorganization, which, in turn, reduces CKB. However, a lack of well-being arising from volunteer
activities may lead to insecurity about knowledge sharing, which may further motivate CKB as adefensive routine to protect themselves and their weaknesses through knowledge hiding (CegarraNavarro et al., 2021).
This study integrated aspects of volunteers as both organizational personnel and autonomous,
spontaneous individuals in an analytical framework. The third major finding was the empiricaldemonstration of the relationship between well-being and the perceived self-control of knowledge
sharing in the organization, which adds a new perspective to knowledge management in volunteer
organizations. Although many empirical studies on knowledge hiding have been conducted incorporate settings (e.g. Siachou et al., 2021), few have examined CKB in NPOs that engage involunteer activities. Unlike corporate entities, volunteer organizations have a role in amelioratingsocial problems and providing opportunities for participants to increase their well-being. This study
found that even in an NPO setting, participants’ CKBs depend on organizational factors and individual
attitudes, and it clarified the characteristics of this mechanism.

Practical Implications
This study shows that NPOs must improve their organizational efficiency while working towardtackling social issues. Volunteer activities in NPOs provide opportunities for the participants todevelop multifaceted well-being. Thus, it is necessary to promote effective knowledge sharing andreduce intentional CKB, such as knowledge hiding, among members, for the sake of creating social
value and participants’ well-being.
Volunteers at NPOs are diverse in terms of their age, gender, and experience (Grant, 1996); therefore,
it is important to create a psychologically safe (Edmondson, 2012) environment to reduce theirinsecurity about sharing knowledge and assure them that they will be recognized for doing so.
Our analysis showed that those who achieved greater well-being had less insecurity about knowledge
sharing compared to those who did not. Volunteers who feel that their knowledge behavior contributes
societies may be less conscious of how they are viewed by organizational members after they haveshared their knowledge. They may also avoid CKB because they are truly motivated by the social
activity rather than a sense of competition with others. Consequently, NPO managers should provide
intrinsically motivating tasks through sufficient dialog with volunteers to prevent CKB.
The degree of well-being generated from volunteer activities depends on their content. In the case ofinterpersonal service activities, regardless of the effort involved, value can be co-created or codestructed by others’ activities (Plé and Chumpitaz Cáceres, 2010). Therefore, organizational
managers must understand the kind of experiences that volunteers have and support them as much as
possible so as not to damage their sense of fulfillment.

Conclusion and Future Directions
This study identified the CKB of volunteers in NPOs and its influencing factors, based on TPB andthe well-being theory. An analysis of data obtained from 496 online survey responses showed that
insecurity about knowledge sharing as a perceived control in TPB had the greatest impact on CKB. It
was found that a competitive organizational norm under the subjective norm of TPB could induce
CKB, while a knowledge-sharing organizational norm did not have a significant influence. We
analyzed the relationship between CKB and three aspects: psychological wellbeing status, selfdetermination as the driving force of eudaimonic well-being, and trustworthy human relationships as
the driving force of hedonic well-being. The results showed that the more self-determined thevolunteer activity was, the more the CKB was suppressed. However, the status of well-being did nothave a significant direct effect.
The results of the analysis using the framework integrating the two perspectives, TPB and well-being
theory, showed the impact of each on CKB. They also revealed a relationship between the perspectives
such that the volunteers with high levels of well-being and self-determination had significantly lowerlevels of insecurity about knowledge sharing, which mitigates CKB compared to those who did not.
This finding provides a variety of strategies for NPO managers to avoid CKB among volunteers, andadds a new perspective to the study of knowledge management in NPOs, where that of knowledge
sharing as productive knowledge behavior has been dominant.
While this study makes a significant contribution to the understanding of CKB in NPOs, it has several
limitations. First, it deals only with transmitting knowledge to others (i.e., knowledge senders) anddoes not examine experiences of knowledge hiding from others. Therefore, we could not fully
determine whether the questionnaire respondents were hiding knowledge as a retaliatory behavior
based on their past experiences or purely due to organizational influences or individual thinking.
Second, we could only partially demonstrate how the influence of self-determination is related to themitigation of CKB. Studies have shown that altruism negatively affects knowledge hiding. In the caseof intrinsically motivated individuals with a sense of self-determination, it is important to distinguishwhether the target of the motivation is self-oriented or other-oriented. If the motivation is otheroriented, it may negatively affect knowledge hiding; if it is self-oriented, it may further induce
knowledge hiding. Finally, this study examined the CKB mechanism in NPOs. In recent years, due tothe growing awareness of the sustainable development goals, many companies have been promoting
decent work, i.e., the creation of a productive working environment in which employees can workwith human dignity. In that context, the integrated aspects of volunteers as both organizational
personnel and autonomous, spontaneous individuals in an analytical framework will be a usefulperspective to consider the CKB mechanism in the for-profit sector too, which will need to be tested
in the future.

References
Ajzen, I. (1991), “The theory of planned behavior”, Organizational Behavior and Human Decision
Processes, Vol. 50 No. 2, pp. 179–211.
Alajmi, B.M. (2012), “The intention to share: Psychological investigation of knowledge sharing
behaviour in online communities”, Journal of Information and Knowledge Management, Vol. 11
No. 3, available at:https://doi.org/10.1142/S0219649212500220.
Ali, M., Ali, I., Albort-Morant, G. and Leal-Rodríguez, A.L. (2021), “How do job insecurity andperceived well-being affect expatriate employees’ willingness to share or hide knowledge?”,
International Entrepreneurship and Management Journal, Vol. 17 No. 1, pp. 185–210.
Anand, A., Centobelli, P. and Cerchione, R. (2020), “Why should I share knowledge with others? A
review-based framework on events leading to knowledge hiding”, Journal of Organizational
Change Management, Vol. 33 No. 2, pp. 379–399.

Avey, J.B., Avolio, B.J., Crossley, C.D. and Luthans, F. (2009), “Psychological ownership: theoreticalextensions, measurement and relation to work outcomes”, Journal of Organizational Behavior, Vol.
30 No. 2, pp. 173–191.
Banagou, M., Batistič, S., Do, H. and Poell, R.F. (2021), “Relational climates moderate the effect of
openness to experience on knowledge hiding: a two-country multi-level study”, Journal of
Knowledge Management, Vol. 25 No. 11, pp. 60–87.
Bari, M.W., Ghaffar, M. and Ahmad, B. (2020), “Knowledge-hiding behaviors and employees’ silence:
mediating role of psychological contract breach”, Journal of Knowledge Management, Vol. 24 No.
9, pp. 2171–2194.
Beck, L. and Ajzen, I. (1991), “Predicting dishonest actions using the theory of planned behavior”,
Journal of Research in Personality, Vol. 25 No. 3, pp. 285–301.
Bhattacharya, S. and Sharma, P. (2019), “Dilemma between ‘It’s My or It’s My Organization’s
Territory’: Antecedent to knowledge hiding in Indian knowledge base industry”, International
Journal of Knowledge Management, Vol. 15 No. 3, pp. 24–44.
Bolisani, E. and Cegarra-Navarro, J.-G. (2021), “Bad Counter Knowledge: Case Studies andCountermeasures”, in Dima, A.M. and D’Ascenzo, F. (Eds.), Business Revolution in a Digital Era,
Springer, pp. 1–13.
Buhrmester, M., Kwang, T. and Gosling, S.D. (2011), “Amazon’s mechanical Turk: A new source of
inexpensive, yet high-quality, data?”, Perspectives on Psychological Science, Vol. 6 No. 1, pp. 3–5.
Cegarra-Navarro, J.-G., Wensley, A., Batistic, S., Evans, M. and Para, C.C. (2021), “Minimizing theeffects of defensive routines on knowledge hiding though unlearning”, Journal of BusinessResearch, Vol. 137, pp. 58–68.
Chatterjee, S., Chaudhuri, R., Thrassou, A. and Vrontis, D. (2021), “Antecedents and consequences ofknowledge hiding: The moderating role of knowledge hiders and knowledge seekers inorganizations”, Journal of Business Research, Vol. 128, pp. 303–313.
Chen, X., Wei, S. and Rice, R.E. (2020), “Integrating the bright and dark sides of communication
visibility for knowledge management and creativity: The moderating role of regulatory focus”,
Computers in Human Behavior, Vol. 111, available at:https://doi.org/10.1016/j.chb.2020.106421.
Chennamaneni, A., Teng, J.T.C. and Raja, M.K. (2012), “A unified model of knowledge sharing
behaviours: Theoretical development and empirical test”, Behaviour and Information Technology,
Vol. 31 No. 11, pp. 1097–1115.
Coleman, J.S. (1988), “Social Capital in the Creation of Human Capital”, American Journal of Sociology,
University of Chicago Press, Vol. 94, pp. S95–S120.
Connelly, C.E., Zweig, D., Webster, J. and Trougakos, J.P. (2012), “Knowledge hiding in organizations”,
Journal of Organizational Behavior, Vol. 33 No. 1, pp. 64–88.
Davenport, T.H. (1997), “Ten principles of knowledge management and four case studies”, Knowledgeand Process Management, Vol. 4 No. 3, pp. 187–208.
Davenport, T.H. and Prusak, L. (1998), Working Knowledge: How Organizations Manage What They
Know, Harvard Business School Press, Boston, MA.
Deutsch, M. (2006), “Cooperation and Competition”, in Deutsch, M., Coleman, P.T. and Marcus, E.C.
(Eds.), The Handbook of Conflict Resolution: Theory and Practice, Jossey-Bass, San Francisco, pp.
23–40.
Diener, E. (1984), “Subjective well-being.”, Psychological Bulletin, American Psychological Association,
US.
Diener, E., Emmons, R.A., Larsen, R.J. and Griffin, S. (1985), “The Satisfaction With Life Scale.”,Journal of Personality Assessment, Vol. 49 No. 1, pp. 71–75.
Dury, S., De Donder, L., De Witte, N., Buffel, T., Jacquet, W. and Verté, D. (2014), “To Volunteer orNot: The Influence of Individual Characteristics, Resources, and Social Factors on the Likelihoodof Volunteering by Older Adults”, Nonprofit and Voluntary Sector Quarterly, Vol. 44 No. 6, pp.
1107–1128.
Edmondson, A.C. (2012), Teaming: How Organizations Learn, Innovate, and Compete in the Knowledge
Economy, John Wiley & Sons, Inc.
Erden, Z., Von Krogh, G. and Kim, S. (2012), “Knowledge sharing in an online community ofvolunteers”, European Management Review, Vol. 9 No. 4, pp. 213–227.
Ford, D., Myrden, S.E. and Jones, T.D. (2015), “Understanding ‘disengagement from knowledge
sharing’: engagement theory versus adaptive cost theory”, Journal of Knowledge Management, Vol.
19 No. 3, pp. 476–496.
Ford, D.P. and Staples, S. (2010), “Are full and partial knowledge sharing the same?”, Journal of
Knowledge Management, Vol. 14 No. 3, pp. 394–409.
Fornell, C. and Larcker, D.F. (1981), “Evaluating Structural Equation Models with Unobservable
Variables and Measurement Error”, Journal of Marketing Research, American Marketing
Association, Vol. 18 No. 1, pp. 39–50.
Gagné, M. (2009), “A model of knowledge-sharing motivation”, Human Resource Management, Vol. 48
No. 4, pp. 571–589.
Gefen, D., Straub, D. and Boudreau, M. (2000), “Structural Equation Modeling and Regression:
Guidelines for Research Practice”, Communications of the Association for Information Systems,
Vol. 4 No. 7, pp. 1–77.
de Geofroy, Z. and Evans, M.M. (2017), “Are Emotionally Intelligent Employees Less Likely to Hide
Their Knowledge?”, Knowledge and Process Management, Vol. 24 No. 2, pp. 81–95.
Göksel, A. and Aydintan, B. (2017), “How can tacit knowledge be shared more in organizations? A
multidimensional approach to the role of social capital and locus of control”, Knowledge
Management Research and Practice, Vol. 15 No. 1, pp. 34–44.

Grant, R.M. (1996), “Toward a knowledge-based theory of the firm”, Strategic Management Journal,
Vol. 17 No. S2, pp. 109–122.
Greenfield, E.A. and Marks, N.F. (2004), “Formal volunteering as a protective factor for older adults’
psychological well-being”, Journals of Gerontology - Series B Psychological Sciences and Social
Sciences, Vol. 59 No. 5, pp. S258–S264.
Grewal, R., Cote, J.A. and Baumgartner, H. (2004), “Multicollinearity and Measurement Error in
Structural Equation Models: Implications for Theory Testing”, Marketing Science, Vol. 23 No. 4,
pp. 519–529.
Hopper, D., Coughlan, J. and Mullen, M. (2008), “Structural Equation Modelling: Guidelines for
Determining Model Fit”, Electronic Journal of Business Research Methods, Vol. 6 No. 1, pp. 53–
60.
Hu, L. and Bentler, P.M. (1999), “Cutoff criteria for fit indexes in covariance structure analysis:
Conventional criteria versus new alternatives”, Structural Equation Modeling: A Multidisciplinary
Journal, Vol. 6 No. 1, pp. 1–55.
Huck, J., Al, R. and Rathi, D. (2011), “Finding KM solutions for a volunteer-based non-profit
organization”, VINE, Vol. 41 No. 1, pp. 26–40.
Huo, W., Cai, Z., Luo, J., Men, C. and Jia, R. (2016), “Antecedents and intervention mechanisms: a
multi-level study of R&amp;D team’s knowledge hiding behavior”, Journal of Knowledge
Management, Vol. 20 No. 5, pp. 880–897.
Irum, A., Ghosh, K. and Pandey, A. (2020), “Workplace incivility and knowledge hiding: a research
agenda”, Benchmarking, Vol. 27 No. 3, pp. 958–980.
Issac, A.C., Baral, R. and Bednall, T.C. (2020), “Don’t play the odds, play the man: Estimating thedriving potency of factors engendering knowledge hiding behaviour in stakeholders”, European
Business Review, Vol. 32 No. 3, pp. 531–551.
Issac, A.C., Baral, R. and Bednall, T.C. (2021), “What is not hidden about knowledge hiding:
Deciphering the future research directions through a morphological analysis”, Knowledge andProcess Management, Vol. 28 No. 1, pp. 40–55.
Jahanzeb, S., Clercq, D.D. and Fatima, T. (2020), “Bridging the Breach: Using Positive Affectivity toOvercome Knowledge Hiding after Contract Breaches”, Journal of Psychology: Interdisciplinary
and Applied, Vol. 154 No. 3, pp. 249–272.
Jeon, S., Kim, Y. and Koh, J. (2011), “An integrative model for knowledge sharing in communities‐of‐practice”, Journal of Knowledge Management, Emerald Group Publishing Limited, Vol. 15 No. 2,
pp. 251–269.
Jha, J.K. and Varkkey, B. (2018), “Are you a cistern or a channel? Exploring factors triggeringknowledge-hiding behavior at the workplace: evidence from the Indian R&D professionals”,
Journal of Knowledge Management, Vol. 22 No. 4, pp. 824–849.

Jiang, Z., Hu, X., Wang, Z. and Jiang, X. (2019), “Knowledge hiding as a barrier to thriving: The
mediating role of psychological safety and moderating role of organizational cynicism”, Journal of
Organizational Behavior, Vol. 40 No. 7, pp. 800–818.
Joe, F.H.J., Marko, S., Lucas, H. and Volker, G.K. (2014), “Partial least squares structural equation
modeling (PLS-SEM): An emerging tool in business research”, European Business Review,
Emerald Group Publishing Limited, Vol. 26 No. 2, pp. 106–121.
Kankanhalli, A., Tan, B. and Wei, K. (2005), “Contributing Knowledge to Electronic Knowledge
Repositories: An Empirical Investigation”, MIS Quarterly, Vol. 29 No. 1, pp. 113–143.
Keyes, C.L.M. (1998), “Social well-being.”, Social Psychology Quarterly, American Sociological Assn,
US, Vol. 61 No. 2, pp. 121–140.
Keyes, C.L.M. (2006), “Mental health in adolescence: is America’s youth flourishing?”, The American
Journal of Orthopsychiatry, Vol. 76 No. 3, pp. 395–402.
Kline, R.B. (2015), Principles and Practice of Structural Equation Modeling, Fourth Edition, Guilford
Publications.
Koay, K.Y., Sandhu, M.S., Tjiptono, F. and Watabe, M. (2020), “Understanding employees’ knowledge
hiding behaviour: the moderating role of market culture”, Behaviour and Information Technology,
available at:https://doi.org/10.1080/0144929X.2020.1831073.
Kuo, F.-Y. and Young, M.-L. (2008), “A study of the intention-action gap in knowledge sharing
practices”, Journal of the American Society for Information Science and Technology, Vol. 59 No. 8,
pp. 1224–1237.
Lei, H., Do, N.K. and Le, P.B. (2019), “Arousing a positive climate for knowledge sharing through moral
lens: the mediating roles of knowledge-centered and collaborative culture”, Journal of Knowledge
Management, Vol. 23 No. 8, pp. 1586–1604.
Lettieri, E., Borga, F. and Savoldelli, A. (2004), “Knowledge management in non‐profit organizations”,
Journal of Knowledge Management, Vol. 8 No. 6, pp. 16–30.
Li, X., Xu, Z. and Men, C. (2020), “The transmission mechanism of idea generation on idea
implementation: team knowledge territoriality perspective”, Journal of Knowledge Management,
Vol. 25 No. 6, pp. 1508–1525.
Lin, H. and Lee, G. (2004), “Perceptions of senior managers toward knowledge‐sharing behaviour”,
Management Decision, Vol. 42 No. 1, pp. 108–125.
Losada-Otálora, M., Peña-García, N. and Sánchez, I.D. (2021), “Interpersonal conflict at work andknowledge hiding in service organizations: the mediator role of employee well-being”,
International Journal of Quality and Service Sciences, Vol. 13 No. 1, pp. 63–90.
Macleod, A., Skinner, M.W., Wilkinson, F. and Reid, H. (2016), “Connecting Socially Isolated Older
Rural Adults with Older Volunteers through Expressive Arts”, Canadian Journal on Aging, Vol. 35
No. 1, pp. 14–27.

Martín-Alcázar, F., Ruiz-Martínez, M. and Sánchez-Gardey, G. (2019), “Assessing social capital inacademic research teams: a measurement instrument proposal”, Scientometrics, Vol. 121 No. 2, pp.
917–935.
Mohd Noor, N.H., Hajar, S.A.B. and Idris, M.A. (2015), “The Determinant of Nonprofit External andInternal Effectiveness: The Role of Knowledge Sharing, Collaborative Culture, and Beneficiary
Participation”, Human Service Organizations Management, Leadership and Governance, Vol. 39
No. 5, pp. 459–474.
Morrow-Howell, N., Hinterlong, J., Rozario, P.A. and Tang, F. (2003), “Effects of volunteering on thewell-being of older adults”, Journals of Gerontology - Series B Psychological Sciences and Social
Sciences, Vol. 58 No. 3, pp. S137–S145.
Nerstad, C.G.L., Roberts, G.C. and Richardsen, A.M. (2013), “Achieving success at work: development
and validation of the Motivational Climate at Work Questionnaire (MCWQ)”, Journal of AppliedSocial Psychology, Vol. 43 No. 11, pp. 2231–2250.
Nguyen, T.-M., Nham, P.T. and Hoang, V.-N. (2019), “The theory of planned behavior and knowledge
sharing: A systematic review and meta-analytic structural equation modelling”, VINE Journal of
Information and Knowledge Management Systems, Vol. 49 No. 1, pp. 76–94.
Nonaka, I. and Konno, N. (1998), “The Concept of ‘Ba’: Building a Foundation for Knowledge
Creation”, California Management Review, Vol. 40 No. 3, pp. 40–54.
Nonaka, I. and Takeuchi, H. (1995), The Knowledge-Creating Company: How Japanese Companies
Create the Dynamics of Innovation, Oxford University Press.
O’Shea, E. (2006), “An economic and social evaluation of the Senior Help Line in Ireland”, Ageing andSociety, Vol. 26 No. 2, pp. 267–284.
Oubrich, M., Hakmaoui, A., Benhayoun, L., Solberg Söilen, K. and Abdulkader, B. (2021), “Impacts ofleadership style, organizational design and HRM practices on knowledge hiding: The indirect rolesof organizational justice and competitive work environment”, Journal of Business Research, Vol.
137, pp. 488–499.
Pavlova, M.K. and Silbereisen, R.K. (2012), “Participation in voluntary organizations and volunteer work
as a compensation for the absence of work or partnership? Evidence from two German samples ofyounger and older adults.”, The Journals of Gerontology. Series B, Psychological Sciences andSocial Sciences, Vol. 67 No. 4, pp. 514–524.
Peng, H. (2013), “Why and when do people hide knowledge?”, Journal of Knowledge Management, Vol.
17 No. 3, pp. 398–415.
Peng, J., Wang, Z. and Chen, X. (2019), “Does Self-Serving Leadership Hinder Team Creativity? A
Moderated Dual-Path Model”, Journal of Business Ethics, Vol. 159 No. 2, pp. 419–433.
Pereira, V. and Mohiya, M. (2021), “Share or hide? Investigating positive and negative employee
intentions and organizational support in the context of knowledge sharing and hiding”, Journal of

Business Research, Vol. 129, pp. 368–381.
Peter, J.P. (1979), “Reliability: A Review of Psychometric Basics and Recent Marketing Practices”,
Journal of Marketing Research, Vol. 16 No. 1, pp. 6–17.
Plé, L. and Chumpitaz Cáceres, R. (2010), “Not always co‐creation: introducing interactional co‐
destruction of value in service‐dominant logic”, Journal of Services Marketing, Vol. 24 No. 6, pp.
430–437.
Preacher, K.J. and Hayes, A.F. (2008), “Asymptotic and resampling strategies for assessing andcomparing indirect effects in multiple mediator models”, Behavior Research Methods, Vol. 40 No.
3, pp. 879–891.
Preacher, K.J. and Kelley, K. (2011), “Effect size measures for mediation models: quantitative strategies
for communicating indirect effects.”, Psychological Methods, Vol. 16 No. 2, pp. 93–115.
Qureshi, A.M.A. and Evans, N. (2015), “Deterrents to knowledge-sharing in the pharmaceutical industry:
A case study”, Journal of Knowledge Management, Vol. 19 No. 2, pp. 296–314.
Ranasinghe, S.B. and Dharmadasa, P. (2013), “Intention to Knowledge Sharing: From Planned Behavior
and Psychological Needs Perspectives”, International Journal of Knowledge Management, Vol. 9
No. 4, pp. 33–50.
Rasheed, K., Mukhtar, U., Anwar, S. and Hayat, N. (2020), “Workplace knowledge hiding among frontline employees: moderation of felt obligation”, VINE Journal of Information and Knowledge
Management Systems, available at:https://doi.org/10.1108/VJIKMS-04-2020-0073.
Rathi, D., Given, L.M. and Forcier, E. (2014), “Interorganisational partnerships and knowledge sharing:
The perspective of non-profit organisations (NPOS)”, Journal of Knowledge Management, Vol. 18
No. 5, pp. 867–885.
Rebok, G.W., Carlson, M.C., Glass, T.A., McGill, S., Hill, J., Wasik, B.A., Ialongo, N., et al. (2004),“Short-Term Impact of Experience Corps® Participation on Children and Schools: Results from a
Pilot Randomized Trial”, Journal of Urban Health, Vol. 81 No. 1, pp. 79–93.
Ryan, R.M. and Deci, E.L. (2000), “Self-determination theory and the facilitation of intrinsic motivation,social development, and well-being.”, American Psychologist, Vol. 55 No. 1, pp. 68–78.
Ryff, C.D. (1989), “Happiness is everything, or is it? Explorations on the meaning of psychological wellbeing.”, Journal of Personality and Social Psychology, Vol. 57 No. 6, pp. 1069–1081.
Ryff, C.D. and Singer, B. (1996), “Psychological well-being: meaning, measurement, and implications
for psychotherapy research.”, Psychotherapy and Psychosomatics, Vol. 65 No. 1, pp. 14–23.
Ryff, C.D. and Singer, B.H. (2008), “Know Thyself and Become What You Are: A Eudaimonic
Approach to Psychological Well-Being”, Journal of Happiness Studies, Vol. 9 No. 1, pp. 13–39.
Serenko, A. (2019), “Knowledge sabotage as an extreme form of counterproductive knowledge behavior:conceptualization, typology, and empirical demonstration”, Journal of Knowledge Management,
Vol. 23 No. 7, pp. 1260–1288.

Serenko, A. (2020), “Knowledge sabotage as an extreme form of counterproductive knowledge behavior:
the perspective of the target”, Journal of Knowledge Management, Vol. 24 No. 4, pp. 737–773.
Serenko, A. and Choo, C.W. (2020), “Knowledge sabotage as an extreme form of counterproductive
knowledge behavior: the role of narcissism, Machiavellianism, psychopathy, and competitiveness”,
Journal of Knowledge Management, Vol. 24 No. 9, pp. 2299–2325.
Siachou, E., Trichina, E., Papasolomou, I. and Sakka, G. (2021), “Why do employees hide theirknowledge and what are the consequences? A systematic literature review”, Journal of BusinessResearch, Vol. 135, pp. 195–213.
Singh, S.K. (2019), “Territoriality, task performance, and workplace deviance: Empirical evidence onrole of knowledge hiding”, Journal of Business Research, Vol. 97, pp. 10–19.
Škerlavaj, M., Connelly, C.E., Cerne, M. and Dysvik, A. (2018), “Tell me if you can: time pressure,prosocial motivation, perspective taking, and knowledge hiding”, Journal of Knowledge
Management, Vol. 22 No. 7, pp. 1489–1509.
Su, C. (2021), “To Share or Hide? A Social Network Approach to Understanding Knowledge Sharing and
Hiding in Organizational Work Teams”, Management Communication Quarterly, Vol. 35 No. 2,
pp. 281–314.
Szulanski, G. (1996), “Exploring internal stickiness: Impediments to the transfer of best practice within
the firm”, Strategic Management Journal, Vol. 17 No. S2, pp. 27–43.
Szulanski, G. (2000), “The Process of Knowledge Transfer: A Diachronic Analysis of Stickiness”,
Organizational Behavior and Human Decision Processes, Vol. 82 No. 1, pp. 9–27.
Di Vaio, A., Hasan, S., Palladino, R., Profita, F. and Mejri, I. (2021), “Understanding knowledge hiding
in business organizations: A bibliometric analysis of research trends, 1988–2020”, Journal ofBusiness Research, Vol. 134, pp. 560–573.
Wang, Y., Han, M.S., Xiang, D. and Hampson, D.P. (2019), “The double-edged effects of perceived
knowledge hiding: empirical evidence from the sales context”, Journal of Knowledge Management,
Vol. 23 No. 2, pp. 279–296.
Wilson, J. and Musick, M. (1997), “Who cares? Toward an integrated theory of volunteer work.”,
American Sociological Review, Vol. 62 No. 5, pp. 694–713.
Wright, K.B. (2017), “Researching Internet-Based Populations: Advantages and Disadvantages of Online
Survey Research, Online Questionnaire Authoring Software Packages, and Web Survey Services”,
Journal of Computer-Mediated Communication, Vol. 10 No. 3, available
at:https://doi.org/10.1111/j.1083-6101.2005.tb00259.x.
Xiao, M. and Cooke, F.L. (2019), “Why and when knowledge hiding in the workplace is harmful: areview of the literature and directions for future research in the Chinese context”, Asia Pacific
Journal of Human Resources, Vol. 57 No. 4, pp. 470–502.
Xiong, C., Chang, V., Scuotto, V., Shi, Y. and Paoloni, N. (2021), “The social-psychological approach inunderstanding knowledge hiding within international R&D teams: An inductive analysis”, Journalof Business Research, Vol. 128, pp. 799–811.
Yi, J. (2009), “A measure of knowledge sharing behavior: scale development and validation”, Knowledge
Management Research & Practice, Vol. 7 No. 1, pp. 65–81.
Yuan, Y., Yang, L., Cheng, X. and Wei, J. (2020), “What is bullying hiding? Exploring antecedents andpotential dimension of knowledge hiding”, Journal of Knowledge Management, available
at:https://doi.org/10.1108/JKM-04-2020-0256.
Zhai, X., Wang, M., Chen, N.-S., Ghani, U. and Cacciolatti, L. (2021), “The secret thoughts of social
network sites users: a scale for the measurement of online knowledge-hiding in a knowledge
exchange (KE) context”, Interactive Learning Environments, available
at:https://doi.org/10.1080/10494820.2021.1913608.
Zhao, L., Detlor, B. and Connelly, C.E. (2016), “Sharing Knowledge in Social Q&A Sites: The
Unintended Consequences of Extrinsic Motivation”, Journal of Management Information Systems,
Vol. 33 No. 1, pp. 70–100.

Table I. Characteristics of survey respondents
Variables
Age

GenderYears ofexperience

30–39
40–49
50–59
60–69
70 and over

n
95
99
98
102
102

percent
19
20
20
20
21

Male
Female1 year or less
1–3 years
3–5 years
Over 5 years

343
153
32
113
81
270

69
31
6.5
22.8
16.3
54.4

VariablesHow
many
peopledo youregularly
work
with?

2–4
5–9
10–14
15–19
Over 20

n
47
110
100
45
194

percent
9.5
22.2
20.1
9.1
39.1

Table II. Details and internal validity of the measurement items

Construct(alpha | AVE | CR)
Knowledge sharingorganizational norm
(0.72 | 0.48 | 0.73)
Competitive
organizational norm
(0.84 | 0.76 | 0.86)
Insecurity aboutknowledge sharing(0.91 | 0.78 | 0.91)

Psychologicalknowledge ownership(0.77 | 0.54 | 0.78)

Knowledge hiding
Playing dump
(0.91 | 0.78 | 0.91)
Evasive hiding(0.87 | 0.81 | 0.89)
Rationalized hiding
Partial knowledge
sharing(0.81 | 0.60 | 0.82)

Self-determination(0.71 | 0.54 | 0.73)

Trustworthy
relationships(0.71 | 0.55 | 0.74)
Well-being creationfrom work(0.80 | 0.58 | 0.81)

Items

Key references

In my organization, members are encouraged to collaborate and exchange ideas.
In my organization, knowledge sharing is encouraged so that members canimplement new initiatives in their activities.

Members can help each other by sharing information and knowledge.

In my organization, we are encouraged to compete against each other for the best
results.

In my organization, only those who have achieved the best results are respected asrole models.

Knowledge sharing may cause me to lose my strengths in the organization.
Knowledge sharing may make people think my knowledge is insignificant (oldfashioned, stale, etc.)Knowledge sharing may make people feel that my values are insignificant (oldfashioned, stale, etc.)
I consider the ownership of the know-how and knowledge that I’ve used in myactivities belongs to me.
I am not comfortable sharing my know-how and knowledge about the activity withother members.

I don’t think that know-how and knowledge that is useful for activities should be
distributed anonymously in organizations.
Playing dumbI’ve said that I didn't know, even though I did.
I’ve pretended that I didn't know what people were talking about.
I’ve said that I was not very knowledgeable about the topic.
Evasive hidingI’ve told people that I would help them out later but stalled as much as possible.
I’ve offered people some other information instead of what they really wanted.
Rationalized hidingI’ve told people that I would not share information for a rational reason.
Partial knowledge sharing
I have shown only part of my overall knowledge and communicated it as incomplete
knowledge.
I’ve offered some insignificant knowledge.
I’ve shared documents related to the content, rather than teaching it directly.
I think this activity will allow me to use the experience and knowledge I have gainedso far.

I like to be engaged in the activity.
I think I’m contributing to society by doing this activity.
I think I am able to act autonomously based on my own ideas in this activity.

Organization members are trustworthy people.

I regularly communicate with organization members for activities.
I believe that the members of the organization share the same aspirations.

I’ve been in contact with members during the COVID-19 pandemic, regardless of
their activities.
This activity has made life worth living for me.
I believe that engaging in this activity has a positive impact on my physical health.
I believe that engaging in this activity has a positive impact on my mental health.

Lei et al. (2019);
Nerstad et al. (2013)

Nerstad et al. (2013)

Kankanhalli et al.
(2005)

Avey et al. (2009)

Connelly et al.
(2012);
Ford and Staples(2008, 2010)

Ryan and(2000)

Deci

Martin-Alcazaral. (2019)et

Ryff and(1996)

SingerTable III. Correlations among major variables
Construct
Generation

M
4

s.t.d

CC

KSC

KO

IK

SD

TR

WB

1.41

Years of experience

3

1.00

Competitive climate (CC)
Knowledge sharing culture(KSC)
Knowledge ownership (KO)

2.28

1.14

0.87

3.77

0.74

0.06

2.7

0.96

0.64

0.17

0.74

Knowledge sharing anxiety (IK)

2.36

1.04

0.66

0.21

0.69

0.88

Sense of self-determination (SD)

3.89

0.63

0.03

0.42

0.04

0.09

Good human relations (TR)

3.64

0.73

0.01

0.61

0.06

0.12

0.49

0.74

Well-being (WB) from activities

3.77

0.72

0.02

0.38

0.02

0.11

0.71

0.48

0.76

Playing dumb (PD)

2.27

1.08

0.65

0.16

0.63

0.69

0.12

0.11

0.12

PD

EK

RK

PK

0.31
0.23

0.32
0.28

0.23
0.16

0.28
0.23

0.69

0.74

0.88

Evasive knowledge hiding (EK)

2.15

1.08

0.67

0.14

0.65

0.71

0.11

0.11

0.13

0.87

0.90

Rational knowledge hiding (RK)

2.23

1.22

0.59

0.09

0.56

0.61

0.03

0.07

0.07

0.72

0.74

-

Partial knowledge sharing (PK)

2.49

1.04

0.57

0.07

0.57

0.62

0.02

0.06

0.05

0.78

0.80

0.70

0.77

Note. M = medium only for Generation and Years of Experience and = mean for other factors. The numbers in boldindicate the square roots of AVE.

Table IV. Results of structural equation modeling analysis
Structural pathPathcoefficient

Bootstrap
Std. err.

z-value

95% CI

Conclusion

Counterproductive knowledge
behavior
Competitive
H1.1(a). 31***. 05
5.98(0.21, 0.41)
Supportedorganizational norm
TPB
Knowledge sharing
Not*
H1.1(b)
. 05
. 04
1.32
(-0.03, 0.13)
organizational norm
supported
CKB
PsychologicalH1.2. 24***. 05
4.91(0.14, 0.33)
Supported
knowledge ownership
Insecurity about
H1.3. 38***. 06
6.82(0.27, 0.49)
Supported
knowledge sharing
Direct effects
Counterproductive knowledge behavior
Well-being creation
Not
H2.1
-.01
. 05
0.17
(-0.11, 0.09)
from work
supportedDegree of selfH2.2
-.14*
. 06
2.36
(-0.25, -0.02)
Supported
determination
Trustworthy human
Not
H2.3
-.05
. 06
0.79
(-0.16, 0.07)
relationships
supported
Indirect effects (mediated by well-being creation from work)
WBC
Counterproductive knowledge behavior*
Degree of self-.01
. 04
0.17
(-0.08, 0.06)
CKB
determination
Trustworthy human
-. 00
.00
0.17
(-0.02, 0.02)
relationships
Total effects (direct and indirect effects)
Counterproductive knowledge behavior
Degree of self-.14**
. 05
2.76
(-0.24, -0.04)
determination
Trustworthy human
-.05
. 06
0.81
(-0.16, 0.07)
relationships
Well-being creation from work
Degree of self. 62***
. 04
16.16
(0.55, 0.70)
determination
Trustworthy human. 17***. 04
4.55(0.10, 0.25)
relationships
Note. ***p<.001, **p<.01, *p<.05. TPB: Theory of planned behavior; CKB: Counterproductive knowledge behavior;
WBC: Well-being creation.

Figure 1. Analysis modelFigure 2. Results of structural equation modeling analysis