Volume 25 Issue 2 Article 2 June 2023 Knowledge Hiding in Organizations: Meta-Analysis 10 Years Later Knowledge Hiding in Organizations: Meta-Analysis 10 Years Later Miha Š kerlavaj University of Ljubljana, School of Economics and Business, Ljubljana, Slovenia and BI Norwegian Business School, Oslo, Norway, miha.skerlavaj@ef.uni-lj.si Matej Č erne University of Ljubljana, School of Economics and Business, Ljubljana, Slovenia Saš a Batistič Tilburg University, Tilburg, The Netherlands Follow this and additional works at: https://www.ebrjournal.net/home Part of the Human Resources Management Commons Recommended Citation Recommended Citation Š kerlavaj, M., Č erne, M., & Batistič , S. (2023). Knowledge Hiding in Organizations: Meta-Analysis 10 Years Later. Economic and Business Review, 25(2), 79-102. https://doi.org/10.15458/2335-4216.1319 This Original Article is brought to you for free and open access by Economic and Business Review. It has been accepted for inclusion in Economic and Business Review by an authorized editor of Economic and Business Review. ORIGINAL ARTICLE Knowledge Hiding in Organizations: Meta-Analysis 10 Years Later Miha Škerlavaj a,b, * , Matej ˇ Cerne a , Saša Batistiˇ c c a University of Ljubljana, School of Economics and Business, Ljubljana, Slovenia b BI Norwegian Business School, Oslo, Norway c Tilburg University, School of Social and Behavioral Sciences, Tilburg, The Netherlands Abstract A decade since the seminal paper on knowledge hiding in organizations (Connelly et al., 2012) emerged, this research area has witnessed rapid evolution, resulting in a fragmentation of the eld and conceptual proliferation. Given the increasing interest in knowledge hiding, this study complements a set of recently published (systematic) literature reviews and proposes an organizing framework (nomological network) for antecedents and consequences of knowledge hiding, and tests it using meta-analytic procedures. Based on an effect analysis drawn from 131 studies and 147 samples, comprising 47,348 participants, the relationships between knowledge hiding and different antecedent and consequence categories are examined. The results generally support expected relationships across the vast majority of categories of knowledge-hiding antecedents, including job characteristics, leadership, attitudes and motivations, working context, personality, and individual differences. Knowledge hiding is related to outcomes, including creativity, task performance, incivility, deviance, and deterioration of workplace behavior. We also provide comprehensive empirical evidence to support the conceptual claim that knowledge hiding is not correlated with knowledge sharing. We have also tested mediations of the most salient antecedents of knowledge hiding. Through our meta-analytic review, we hope to solidify and redirect the trajectory of the growing and maturing knowledge-hiding domain after its rst decade of existence. Keywords: Knowledge hiding, Knowledge management, Meta-analysis, Nomological network, Mediation JEL classication: M10, M12 Introduction K nowledge hiding—“an intentional attempt by an individual to withhold or conceal knowledge that has been requested by another person” (Connelly et al., 2012, p. 65)—is a serious matter in organi- zations, leading to conict, deteriorated quality of relations, decreased creativity and task performance. Similar to many counter-productive phenomena, it is a low-frequency, high-impact behavior with empir- ically documented detrimental effects on important outcomes (see review studies Anand et al., 2020, 2021; Di Vaio et al., 2021; He et al., 2021; Irum et al., 2020; Issac et al., 2021; Oliveira et al., 2021; Rezwan & Takahashi, 2021; Ruparel & Choubisa, 2020; Siachou et al., 2021; Strik et al., 2021; Xiao & Cooke, 2019). Antecedents to knowledge hiding have been studied even more and include ethical leadership, abusive supervision, distrust, job insecurity, and Machiavel- lianism, to name just a few. By adding “bells and whistles,” there is an evident risk of conceptual pro- liferation. Therefore, it is important to take a more objective, meta-analytical stock of both antecedents and consequences of knowledge hiding, above and beyond single-context studies. In the period between 2012, when the seminal pa- per was published (Connelly et al., 2012), and late 2022, the knowledge-hiding eld witnessed a rapid growth in publications and their impact (Fig. 1). After a decade of development, it is time to pause and make Received 21 December 2022; accepted 14 March 2023. Available online 5 June 2023 * Corresponding author. E-mail address: miha.skerlavaj@ef.uni-lj.si (M. Škerlavaj). https://doi.org/10.15458/2335-4216.1319 2335-4216/© 2023 School of Economics and Business University of Ljubljana. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/ licenses/by-nc-nd/4.0/). 80 ECONOMIC AND BUSINESS REVIEW 2023;25:79–102 Fig. 1. Growth curve of number of publications on knowledge hiding and their citations. Note: This gure has been created based on search results as of 15 November 2022. sense of what we know about the knowledge-hiding eld. We aim to complement existing literature re- views (Anand et al., 2020; He et al., 2021; Irum et al., 2020; Strik et al., 2021; Xiao & Cooke, 2019; see a de- tailed comparative analysis in Appendix, Table A1) with meta-analytic techniques in order to further so- lidify, integrate, and even redirect the eld. We intend to do so by providing a quantitative exploration of the nomological network of knowledge hiding in or- ganizations. Our focus is therefore on summarizing empirical evidence by analyzing the direction and strength of effects and relationships with antecedents and consequences in the knowledge-hiding nomolog- ical network (cf. Donthu et al., 2021; Zupic & ˇ Cater, 2014). This will provide an evidence-driven founda- tion for the integration and advancing of the eld of knowledge hiding in the decades to come. In domains that have “exploded” over a relatively short period of time, it is very difcult to rely solely on qualitative review studies and bibliometric review (Zupic & ˇ Cater, 2014) to advance the existing theory. A meta-analytical approach is a valued contribution to summarize empirical evidence of the relation- ships among constructs within the knowledge-hiding nomological network and integrate, solidify, and ex- tend the prevalent theory, especially in the case of mixed ndings. Through our meta-analytic review, we intend to make three key theoretical contributions. First, our review shows that the topic of knowledge hiding has developed into several fragmented areas of research. A variety of different constructs stemming from different theoretical backgrounds have been investi- gated in relation to knowledge hiding. There does not seem to be a very strong consensus regarding what is more or less important to be studied in relation to knowledge hiding. An important reason for concep- tual proliferation is likely the multi-theoretical and even atheoretical basis upon which the knowledge- hiding eld has developed so far. This can make it dif- cult for researchers to see and comprehend the entire conceptual landscape and fully understand the true nature of relationships investigated in this research area (Grifn & Lopez, 2005). On the other hand, many constructs and potentially interesting phenom- ena that are conceptually proximal to the essence of the knowledge-hiding concept (e.g., employee si- lence, counterproductive work behavior, knowledge sabotage) have been barely touched upon. Therefore, it is important to examine and meta-analytically eval- uate specic elements of the nomological networks to help advance the eld and provide a direction for its future development. Second, and on a related note, we intend to ad- vance the current state-of-the-art in the eld by exploring and meta-analytically testing specic rela- tionships, addressing some of the ambiguities that exist in relation to those links. Specically, we have used the input–mediator–outcome (IMO) model de- veloped from the input–process–outcome model by Ilgen et al. (2005) to propose hypotheses about antecedents (broadly categorized into the above- mentioned ve categories), a correlate (knowledge sharing), or outcomes of knowledge hiding. Such a model clearly shows how input and antecedent fac- tors enable or constrain knowledge hiding. Outcomes are results and by-products of the knowledge-hiding process that are valued or not by the individual, team, or organization. Finally, we also delve deeper into potential indirect effects and link antecedents, knowledge hiding, and outcomes, a perspective that has been severely understudied in the extant ECONOMIC AND BUSINESS REVIEW 2023;25:79–102 81 knowledge-hiding research, and pose an exploratory research question related to the indirect effect of the phenomenon in focus. Third, our integrative meta-analytic overview is also intended to address issues of construct valid- ity in the eld. There is a great imbalance between the knowledge-hiding eld and the much more de- veloped research area of knowledge sharing. This imbalance can be a cause of confusion among read- ers, reviewers, and occasionally even authors. Con- ceptually, knowledge hiding (being intentional and occurring as a response to a specic request; Con- nelly et al., 2012) does not equal a lack of knowledge sharing. Nevertheless, reviewers would, quite often, address this particular theme and wonder whether antecedents and outcomes of knowledge hiding and sharing might be similar. A meta-analytical review that summarizes the nomological network and demonstrates the magnitude of meta-analytic correlations between knowledge hiding and its cor- relates (data-driven quantitative literature review) is thus needed, in combination with a comprehen- sive theoretical overview. Admittedly, some of these contributions have been partially addressed with a meta-analysis published exactly at the time of submit- ting this paper (Arain et al., 2022). Our meta-analysis adds value as it builds upon broader samples (47,348 vs. 31,822 participants, 131 instead of 104 studies); we also examine several mediating models between the most salient knowledge-hiding antecedents and a set of relevant outcomes, and semantically examine future research directions. 1 Literature review and hypotheses development 1.1 An integrative model of knowledge hiding in organizations We have constructed our model based on previous authors’ suggestions (Connelly et al., 2019) and re- view studies (He et al., 2021; Siachou et al., 2021), which delineate a possible list of antecedents and out- comes of knowledge hiding. Variables (antecedents, a correlate, and outcomes) in our list are chosen based on two particular reasons; a theoretical one, founded in the aforementioned IMO model and the ve- dimensional categorization we developed on its basis, and a practical/empirical one, with the variables within the categories being selected based on the em- pirical research already conducted in the knowledge- hiding eld and the most studied variables. Fig. 2 represents the overall examined model. 1.2 Hypotheses related to the antecedents of knowledge hiding 1.2.1 Job characteristics The rst set of factors that have been studied in association with knowledge hiding is related to job Fig. 2. Nomological network of knowledge hiding. 82 ECONOMIC AND BUSINESS REVIEW 2023;25:79–102 characteristics. Their foundations lie in motivational job design and the job characteristics model (Hack- man & Oldham, 1975; Morgeson & Humphrey, 2006). Specically, the job characteristics that have been studied the most extensively refer to one’s social boundaries stemming from the structure and nature of work and can be seen as polar opposites, i.e., job au- tonomy and task interdependence. Autonomy refers to one’s freedom in performing work and to both task and work scheduling discretion (Breaugh, 1985). Task interdependence, on the other hand, reects the con- nectedness of employees’ tasks to achieve a common outcome (Hertel et al., 2004). While both have been used in knowledge-hiding re- search mostly as boundary conditions to other effects ( ˇ Cerne et al., 2017; Fong et al., 2018), we can concep- tualize their direct linkage with knowledge hiding as well (Su, 2021). Job autonomy potentially makes it easier to establish territoriality over knowledge and conduct work “in secrecy” due to the inherent inde- pendence it entails, and easier to invent reasons for hiding, such as playing dumb, or for rationalizing hiding. On the other hand, task interdependence, ini- tiated, received, and reciprocal, reects the need to be related to and interconnected with colleagues in the working process, potentially preventing knowledge- hiding decisions as they would not be mutually benecial for achieving common goals (Butt et al., 2020; Staples & Webster, 2008). Job demands is an umbrella term for either pos- itive or negative impositions stemming from one’s job. Research on the matter mostly applies the job demands–resources model (Bakker & Demerouti, 2007), an occupational stress model that suggests strain is a response to an imbalance between demands on the individual and the resources the individual has to deal with those demands. Knowledge-hiding research has established that high levels of some demands (e.g., time pressure, work overload) make individuals conserve their resources (e.g., knowledge as a competitive advantage over colleagues, which might be particularly true in competitive environ- ments) and thereby hide knowledge more frequently (Gagné et al., 2019; Škerlavaj et al., 2018; Sofyan et al., 2021). We therefore propose: H1. Autonomy and job demands are positively related to knowledge hiding, whereas task interdependence is nega- tively related to knowledge hiding. 1.2.2 Leadership In recent years, high quality leader–follower rela- tions have been identied alongside collegiate rela- tions as a potential way of preventing knowledge hiding at work. Mechanisms through which leaders inuence their employees’ knowledge-hiding deci- sions relate to role modeling (especially in the case of ethical leadership (Abdullah et al., 2019; Men et al., 2020)) or positive reciprocity (in particular in the case of leader–member exchange; LMX (Babiˇ c et al., 2019; Zhao et al., 2019)). Indeed, supervisors inuence the establishment of psychological safety and high-quality relationships among team members, who tend to reciprocate fair treatment and role model positive relationships with their leaders with their colleagues as well. This logic also works the other way around, as shown by research linking “negative” leadership styles, such as abusive leadership, with knowledge hiding. Abusive supervision tends to lead to per- ceptions of injustice, unequal treatment, and distrust (Agarwal et al., 2021; Farooq & Sultana, 2021), making employees hide more knowledge (Offergelt & Venz, 2022). Therefore: H2. Abusive leadership is positively related to knowledge hiding, whereas leader–member exchange and ethical lead- ership are negatively related to knowledge hiding. 1.2.3 Attitudes and motivations The next section of knowledge-hiding antecedents refers to “positive” or “negative” attitudes related to the work environment, one’s position and relation- ships at work. Distrust and knowledge territoriality have been established as being among the strongest predictors of knowledge hiding, as they directly re- ect characteristics of poor working relationships and knowledge exchanges. When individuals distrust an- other colleague, they are more likely to not want to help them get the information they need (Connelly et al., 2012; Kumar Jha & Varkkey, 2018), and when an individual perceives they hold ground on a particular knowledge domain, they tend not to let others in to potentially steal their competitive advantage related to this knowledge (Guo et al., 2022; Singh, 2019). A similar logic applies to the case of job insecurity, which might also drive knowledge-hiding behavior for the same reasons of attempting to improve one’s chances of staying in an organization (not losing one’s position) and thriving in the eyes of others. Burnout, on the other hand, reects an individual’s emotional exhaustion in the long run, produced by excessive stress, pressure, demands, or overload. When feeling burned out, individuals tend to resort to knowledge hiding simply because of a lack of time and to con- serve resources that are already emotionally depleted (Zhao & Jiang, 2021). On the other hand, when individuals exhibit moti- vations to help one another, to care about beneting others, and protect and promote the well-being of ECONOMIC AND BUSINESS REVIEW 2023;25:79–102 83 colleagues (i.e., prosocial motivation), they tend to refrain from hiding knowledge from colleagues as they are aware of potentially harming their work- ing relationships or their colleagues’ goal attainment (Hernaus & ˇ Cerne, 2022; Hernaus et al., 2019). Thus: H3. Distrust, knowledge territoriality, burnout, and job insecurity are positively related to knowledge hiding, whereas prosocial motivation is negatively related to knowledge hiding. 1.2.4 Working context Working context and the perceptions individuals develop regarding their work surroundings have been extensively studied in relation to knowledge hiding, mostly in combination with other, mostly individual-level, variables (e.g., Banagou et al., 2021; El-Kassar et al., 2022; Han et al., 2020). The context has been covered either by multi-level research designs or by focusing on individual-level perceptions (i.e., the micro, psychological climates). In general, com- petitive environments, such as those characterized by high levels of competitive or performance climate, which are based on normative comparison, have been demonstrated to stimulate individual competi- tion and thereby hiding knowledge from coworkers in an attempt to improve one’s individual position in a work setting, obtain a competitive advantage over colleagues with particular pieces of valuable in- formation or knowledge, or improve individual goal attainment this way (Banagou et al., 2021; Hernaus et al., 2019; Zhu et al., 2019). A collaborative cli- mate (including mastery or learning), on the other hand, emphasizes effort, individual development and team cooperation, and thereby includes mechanisms of self- (as opposed to other-) referencing improve- ment, mutual support, and common goals, and thus prevents knowledge hiding (Banagou et al., 2021; Bari et al., 2019; ˇ Cerne et al., 2017). Perceived organizational support represents an- other element of a positive working environment that is conducive to knowledge exchange and could prevent knowledge hiding. When individuals feel supported by their immediate or distal actors in their work setting, they develop perceptions of not be- ing punished for voicing their opinion (even if it might go against the common and predominant line of thought). The same is true for psychological safety (climate), a personal belief that it is safe to take a risk and express oneself without fear or negative conse- quences (Edmondson & Lei, 2014; Men et al., 2020; Newman et al., 2017), and interpersonal justice, the degree to which people are treated with dignity and respect, based on equal treatment principles (John- son et al., 2014). In such a working environment, knowledge and information sharing is encouraged and employees engage in it without fear of being pun- ished for voicing out, or without the need to preserve their knowledge to be put in a superior position in relation to colleagues (Jiang et al., 2019; Men et al., 2020). Thus: H4. A collaborative climate, perceived organizational sup- port, interpersonal justice, and psychological safety are positively related to knowledge hiding, whereas a competi- tive climate is negatively related to knowledge hiding. 1.2.5 Personality and individual differences Existing research indicates that some people tend to hide knowledge more often than others, based on their personality traits or individual differences. Some individual traits with negative connotations are particularly suitable for positively predicting knowl- edge hiding. Specically, Machiavellianism, as one of the dark triad personality dimensions centered on manipulativeness, callousness, and indifference to morality (Wilson et al., 1996), may positively predict knowledge hiding since such individuals do not mind resorting to knowledge hiding as a means to achieve their own individual agenda without much consider- ation for others (Pan et al., 2016, 2018). Individuals high in neuroticism, a fundamental personality trait that is part of the core Big 5 per- sonality dimensions and reects a trait disposition to experience negative affects, including anger, anxiety, self-consciousness, irritability, and emotional instabil- ity (Cattell & Scheier, 1961; Widiger, 2009), would also tend to hide knowledge more. This is because individuals high in neuroticism tend to exhibit poor judgement in collaborative working situations, neg- atively interpret even neutral stimuli, and are thus more susceptible to hiding knowledge (Anaza & Nowlin, 2017; Arshad & Ismail, 2018). An individual’s perception of envy might also be a factor in predicting higher levels of knowledge hid- ing, as feeling envious towards a colleague might stimulate individuals to attempt to improve their so- cial or organizational status, such as reducing the comparison gap they perceive, by hiding knowledge (Li et al., 2022; Peng et al., 2020). On the other hand, when individuals exhibit high levels of self-efcacy , resorting to knowledge hiding to appear competent or perform well at work is not necessary as such in- dividuals already perceive themselves as more than capable of delivering what is expected of them. We therefore propose: H5. Machiavellianism, neuroticism, and envy are posi- tively related to knowledge hiding, whereas self-efcacy is negatively related to knowledge hiding. 84 ECONOMIC AND BUSINESS REVIEW 2023;25:79–102 1.2.6 Positive outcomes Knowledge hiding has also been studied in relation to benecial organizational outcomes that add value to organizational endeavors. High-quality social ex- change relationships between coworkers represent a valuable source of creativity (idea generation) and innovation (idea implementation), as they trig- ger knowledge-sharing crucially needed for creative problem-solving in the idea identication and veri- cation stage (Bogilovi´ c et al., 2017; Fong et al., 2018), but also in the stage where resource acquisition (e.g., support, material sources, help) is needed for novel ideas to be implemented ( ˇ Cerne et al., 2017; Guo et al., 2022). As previously mentioned, high-quality knowledge exchange relationships with minimum knowledge hiding and conservation of knowledge resources are also characterized by helping and organizational cit- izenship behavior that is aimed at increasing mutual benets and caring for the well-being of others in a social or organizational setting (Kaur & Kang, 2022). Taken together, through these mechanisms, the well- established reciprocal distrust loop that results in knowledge hiders “shooting themselves in the foot” by hiding knowledge and thereby getting knowledge that they require for their work hidden in return ( ˇ Cerne et al., 2014), knowledge hiding is also expected to decrease knowledge hiders’ task performance. H6. Knowledge hiding is negatively related to creativity, innovation, task performance, and organizational citizen- ship behaviors. 1.2.7 Negative outcomes Frequently (although not exclusively) associated with negative intentions, knowledge hiding has been shown to lead to a plethora of undesirable orga- nizational outcomes. It predicts or is an expression of incivility and deviance, as knowledge-hiding be- havior tends to appear counterproductive and goes against the legitimate interests of the collective (Irum et al., 2020; Singh, 2019). In the same vein, once rec- ognized, it is well established that knowledge hiding results in a deterioration of workplace relation- ships, producing a negative spiral of interpersonal conict, poor working associations, and negative or- ganizational outcomes (Jafari-Sadeghi et al., 2022; Miminoshvili & ˇ Cerne, 2022; Venz & Nesher Shoshan, 2022; Xiao & Cooke, 2019). On another spectrum of negative outcomes, per- ceived knowledge hiding also leads to a loss of commitment and turnover intentions (Offergelt et al., 2019; Zhang & Min, 2022), which also increase once individuals hide knowledge with an intention to quit and thereby stop contributing to the organization they no longer see themselves attached to in the long run (Jena & Swain, 2021). Thus: H7. Knowledge hiding is positively related to incivility, de- viance, turnover intention, and deterioration of workplace relationships. 1.2.8 Key correlates of knowledge hiding A common critique of knowledge-hiding research is that it builds on established linkages that are well known from the study of knowledge sharing. Indeed, many antecedents and consequences might play out in an opposite manner to those of knowledge sharing. However, knowledge hiding is not just the opposite of knowledge sharing, as conceptualized already at the outset of the study of knowledge hiding in orga- nizational settings. Knowledge hiding is not simply the absence of sharing; rather, knowledge hiding is the intentional attempt to withhold or conceal knowl- edge that has been requested by another individual (Connelly et al., 2012). As further developed by Con- nelly et al. (2012), behaviorally, the two constructs appear similar but the motivations behind knowledge hiding and a lack of knowledge sharing are patently different. Knowledge hiding might be motivated by a number of different reasons, which are already dis- cussed above, whereas a lack of knowledge sharing is likely only driven by an absence of the knowledge itself (Connelly et al., 2012). We thus propose an em- pirical meta-analytical test of this assertion: H8. Knowledge hiding is not related to (the lack of) knowl- edge sharing. 1.2.9 Knowledge hiding as mediator Knowledge hiding might also hold an important indirect place in understanding knowledge-related behavior in organizations. The processes or medi- ators represent an important element of the IMO model because they elucidate two matters. On the one hand, they describe how antecedents are re- lated to outcomes, and on the other hand, they also highlight the uniqueness of the mediators or pro- cesses (e.g., that knowledge hiding is different from knowledge sharing) (Mathieu et al., 2008). There- fore, we also delve deeper into potential indirect effects and link antecedents, knowledge hiding, and outcomes, by posing an exploratory research ques- tion related to the indirect effect of the knowledge hiding: Does knowledge hiding mediate the relationship between selected antecedents (job characteristics, leader- ship, attitudes/motivations, working context, and individ- ual differences) and outcomes (performance, organizational citizenship behavior, deviance, creativity)? ECONOMIC AND BUSINESS REVIEW 2023;25:79–102 85 2 Method 2.1 Literature search and criteria for inclusion To identify relevant studies, we rst searched for published and unpublished studies on knowledge hiding using online databases across multiple dis- ciplines including EBSCO Host, Emerald, JSTOR, Oxford Press, ProQuest, Sage Journals, Science Direct, Springer Link, Taylor and Francis, and Web of Science. We used the search term “knowledge hiding” to iden- tify relevant studies. Second, we conducted a forward citation search of the prominent knowledge-hiding scale by Connelly et al. (2012). Third, we searched for in-press articles in leading management journals and conference proceedings, as well as contacted authors for unpublished articles. In our search, we identied all the papers that include knowledge hiding any- where in the text. The broad search in March 2022 identied an initial sample of 342 documents. This initial pool included both empirical and theoretical studies, serving as the basis of our review. To provide a quantitative re- view of knowledge hiding, we additionally screened this initial pool to identify empirical studies that are suitable to be included in a meta-analysis. To be included in the meta-analysis, a study should (a) report the sample size, (b) report correlations (or other effect sizes) between knowledge hiding and its correlates, and (c) involve an adult sample. This additional screening identied 131 studies and 147 samples, comprising 47,348 participants. Two re- search assistants coded all the studies independently. The average inter-coder percentage of agreement across the study variables was 95%. When there were discrepancies among the raters, two coders and an author discussed the codings until a consensus was reached. 2.2 Meta-analytic procedures To provide a nomological network of knowledge hiding with magnitudes of effect sizes, we conducted a meta-analysis based on the random-effects ap- proach to psychometric meta-analyses advocated by Schmidt and Hunter (2014). We used the Metafor Package in R to calculate the population correla- tions between knowledge hiding and its correlates. With psychometric meta-analyses, we corrected for attenuation in observed correlations due to statistical artifacts including sampling error and measurement unreliability in both knowledge hiding and its corre- lates. For each meta-analysis, we reported the sample size (N), number of effect sizes (k), uncorrected cor- relation (r), corrected r (effect sizes corrected for reliability in knowledge hiding and its correlates), standard deviation of r, heterogeneity of the effect sizes (Q), 80% credibility interval (80% CV), and 95% condence intervals (95% CI). We applied the same procedures to analyze the population correlations be- tween knowledge hiding and its correlates. 3 Results Table 1 presents the meta-analytical relationships between knowledge hiding and other studied con- structs. Hypothesis 1 predicted that autonomy and job demands are positively related to knowledge hiding, whereas task interdependence is negatively related to knowledge hiding. Results in Table 1 did not support this hypothesis. Overall, job character- istics, including task interdependence (rD :02, 95% CID [ .19, .24]) and job autonomy (rD :00, 95% CID [ .20, .20]) are not related to knowledge hiding. Although job demands (rD :27, 95% CID [ .49, .04]) are related to knowledge hiding, the relation- ship is opposite to our hypothesis. Hypothesis 2 predicted that abusive leadership is positively related to knowledge hiding, whereas leader–member exchange and ethical leadership are negatively related to knowledge hiding. Results in Table 1 supported this hypothesis. Overall, leadership behaviors, including LMX (rD :26, 95% CID [ .50, .03]) and ethical leadership (rD :17, 95% CID [ .25, .09]) are negatively related to knowledge hid- ing, whereas abusive supervision (rD :45, 95% CID [.32, .59]) is positively related to knowledge hiding. Hypothesis 3 predicted that distrust, knowledge territoriality, burnout, and job insecurity are posi- tively related to knowledge hiding, whereas prosocial motivation is negatively related to knowledge hiding. Results in Table 1 supported this hypothesis that work attitudes and motivations are predictors of knowl- edge hiding. Specically, distrust ( rD :43, 95% CID [.37, .49]), knowledge territoriality (rD :24, 95% CID [.10, .39]), burnout (rD :54, 95% CID [.49, .60]), and job insecurity (rD :36, 95% CID [.08, .64]) are posi- tively related to knowledge hiding, whereas prosocial motivation (rD :19, 95% CID [ .27, .11]) is nega- tively related to knowledge hiding. Hypothesis 4 predicted that a collaborative climate, perceived organizational support, interpersonal jus- tice, and psychological safety are positively related to knowledge hiding, whereas a competitive cli- mate is negatively related to knowledge hiding. Results partially supported Hypothesis 4. Specically, a collaborative climate (rD :14, 95% CID [ .27, .01]), interpersonal justice (rD :39, 95% CI D [ .61, .18]), and psychological safety (rD :47, 95% CID [ .61, .32]) are negatively associated with 86 ECONOMIC AND BUSINESS REVIEW 2023;25:79–102 Table 1. Meta-analysis of the antecedents and consequences of knowledge hiding. Variable K N r r SDr Q 80% CV 95% CI Fsn Lower Upper Lower Upper Antecedents Job characteristics Job autonomy 4 1051 .00 .00 .18 33.31 .23 .23 .20 .20 0 Job demands 4 1055 .24 .27 .21 46.59 .53 .00 .49 .04 108 Task interdependence 12 3033 .02 .02 .34 337.80 .42 .46 .19 .24 0 Leadership Abusive leadership 9 2607 .41 .45 .19 139.33 .21 .69 .32 .59 2792 Leader–member exchange 11 4227 .22 .26 .18 140.94 .39 .13 .50 .03 1111 Ethical leadership 9 3067 .15 .17 .10 34.07 .29 .04 .25 .09 228 Attitudes and motivations Distrust 9 2940 .38 .43 .06 20.32 .35 .51 .37 .49 1721 Knowledge (psychological) 15 4079 .21 .24 .26 273.00 .10 .58 .10 .39 1471 ownership/territoriality Burnout 4 1094 .46 .54 .00 2.04 .54 .54 .49 .60 528 Job insecurity 6 1547 .31 .36 .33 212.95 .06 .79 .08 .64 587 Prosocial motivation 5 1284 .17 -.19 .05 8.36 .26 .12 .27 .11 67 Working contexts Collaborative climate (incl. mastery 8 1674 .11 .14 .15 36.47 .33 .05 .27 .01 74 climate) Perceived organizational support 5 1627 .10 .13 .25 88.37 .45 .20 .35 .10 52 Interpersonal justice 3 763 .37 .39 .18 34.47 .62 .16 .61 .18 203 Psychological safety 7 2385 .38 .47 .18 88.14 .70 .24 .61 .32 1533 Competitive climate (incl. performance 7 1623 .25 .29 .17 54.36 .07 .51 .14 .43 305 climate) Personalities and individual differences Machiavellianism 6 1823 .32 .37 .03 .20 .34 .41 .31 .43 465 Neuroticism 5 950 .41 .47 .25 81.71 .14 .79 .23 .70 516 Envy 9 4352 .36 .44 .11 60.54 .29 .58 .35 .53 2665 Self-efcacy 5 1572 .06 .07 .32 135.57 .48 .34 .37 .23 0 Outcomes Creativity 12 3516 .26 .30 .30 379.82 .68 .11 .50 .07 1059 Innovation 7 2479 .08 .09 .24 128.01 .39 .22 .29 .11 22 Task performance 10 2519 .21 .23 .22 130.38 .51 .05 .38 .08 640 Organizational citizenship behavior 13 4352 .16 .18 .47 1075.95 .78 .42 .45 .09 618 Incivility 5 1209 .55 .62 .09 23.37 .50 .74 .53 .72 1546 Deviance 4 1220 .37 .39 .12 23.99 .26 .53 .24 .54 337 Turnover intention 6 3808 .18 .20 .25 233.08 .11 .52 .04 .45 191 Deterioration of workplace relationships 5 1200 .25 .30 .05 7.40 .24 .37 .23 .38 157 Correlate Knowledge sharing 14 3376 .05 .06 .40 491.89 .57 .44 .30 .17 299 Note: ND combined sample size; KD number of samples; rD mean uncorrected correlation;rD estimated true score correlation corrected for measurement error; QD Q statistic (Hedges & Olkin, 1984); CVD credibility interval; CID condence interval; FsnD fail-safe N. p< .05. knowledge hiding, whereas a competitive climate is positively associated with knowledge hiding (rD :29, 95% CID [.14, .43]). However, our results indicated that perceived organizational support is not associ- ated with knowledge hiding (rD :13, 95% CID [ .35, .10]). Hypothesis 5 predicted that Machiavellianism, neuroticism, and envy are positively related to knowl- edge hiding, whereas self-efcacy is negatively re- lated to knowledge hiding. Results partially sup- ported Hypothesis 5. Specically, Machiavellianism (rD :37, 95% CID [.31, .43]), neuroticism (rD :47, 95% CID [.23, .70]), and envy (rD :44, 95% CID [.35, .53]) are positively associated with knowledge hid- ing. However, our results indicated that self-efcacy is not associated with knowledge hiding (rD :07, 95% CID [ .37, .23]). Hypothesis 6 predicted that knowledge hiding is negatively related to creativity, innovation, task per- formance, and organizational citizenship behavior. Results partially supported Hypothesis 6. Specically, knowledge hiding is negatively associated with cre- ativity (rD :30, 95% CID [ .50, .07]) and task performance (rD :23, 95% CID [ .38, .08]). How- ever, our results indicated that knowledge hiding is not associated with innovation (rD :09, 95% ECONOMIC AND BUSINESS REVIEW 2023;25:79–102 87 CID [ .29, .11]) or organizational citizenship behav- ior (rD :18, 95% CID [ .45, .09]). Hypothesis 7 predicted that knowledge hiding is positively related to incivility, deviance, turnover in- tention, and deterioration of workplace relationships. Results partially supported Hypothesis 7. Specically, knowledge hiding is positively associated with inci- vility (rD :62, 95% CID [.53, .72]), deviance (rD :39, 95% CID [.24, .54]), and deterioration of workplace relationships (rD :30, 95% CID [.23, .38]). How- ever, our results indicated that knowledge hiding is not associated with turnover intention (rD :20, 95% CID [ .04, .45]) or organizational citizenship behav- ior (rD :18, 95% CID [ .45, .09]). Hypothesis 8 predicted that knowledge hiding is not the opposite of knowledge sharing. Results supported Hypothesis 8, indicating that knowledge hiding is not associated with knowledge sharing (rD :06, 95% CID [ .30, .17]). 3.1 Supplementary mediation analysis In addition to testing knowledge hiding as an an- tecedent or outcome of specic factors that were conceptualized and hypothesized in advance, we also conducted post-hoc supplementary analyses that test each factor’s role as a mediator that could explain the impact of its antecedents on its outcomes following the logic of the IMO framework. Testing the media- tion relationships requires using the meta-analytical structural equation modeling technique with the cor- relation matrix as the data input (Viswesvaran & Ones, 1995). Because different antecedents are as- sociated with different theoretical perspectives, we tested mediation effects with only one antecedent at a time. We used two criteria for the choice of constructs that were proposed as antecedents in such mediation models: 1) that an antecedent exhibited a statistically signicant relationship with knowledge hiding in the direct effect meta-analysis; and 2) that an antecedent appeared in at least four studies of knowledge hiding. In each model, we included commonly examined behavioral outcomes, including task performance, organizational citizenship behavior, deviance, and creativity. To construct the required correlation matrix as presented in Table 2, we rst searched for correla- tions from published studies. For those that we could not nd in the literature, we searched primary studies and conducted a meta-analysis ourselves. In the mediation analysis, we started with satu- rated models because we did not hypothesize that knowledge hiding fully mediates the relationships between the antecedent and behavioral outcomes. Instead, we believe that there are other theoretical me- diators that also explain the relationships between the corresponding antecedent and behavioral outcomes (e.g., between autonomy and task performance; see for example, Langfred & Moye, 2004). Therefore, in all these mediation models, we kept the direct effects of the antecedent and outcomes. Knowledge hiding was treated as a partial mediator in these models. We present the mediation models in Figs. 3–7 and the associated indirect effects in Table 3. Overall, knowledge hiding is a mediator for most of the relationships. Specically, knowledge hiding is a mediator between job insecurity on the one hand and task performance (indirect effectD .07, p < .000), organizational citizenship behavior (indirect ef- fectD .06, p < .000), deviance (indirect effectD .14, p < .000), and creativity (indirect effectD .11, p < .000) on the other. Knowledge hiding is a mediator between psychological safety on the one hand and deviance (indirect effectD .13, p < .000) and cre- ativity (indirect effectD .14, p < .000), but not task performance (indirect effectD .02, p > .05) or organi- zational citizenship behavior (indirect effectD .02, p > .05), on the other. Knowledge hiding is a mediator between abusive supervision on the one hand and Table 2. Correlation matrix for mediation analysis. Job Abusive Distrust Psychological Neuroticism Creativity Task Organizational insecurity leadership safety performance citizenship behavior Creativity .10 .13 .59 .13 .08 (10, 5964) 1 (5, 1863) 12 (5, 1542) 12 (10, 4567) 5 (18, 7661) 7 Task performance .17 .19 .30 .43 .19 .55 (53, 21,461) 1 (16, 4012) 2 (53, 12,237) 6 (18, 4061) 5 (20, 4106) 8 (28, 7660) 10 Org. citizenship .09 .24 .34 .32 .15 .56 .29 (5, 1436) 12 (6, 1319) 3 (39, 10,615) 6 (16, 7275) 5 (36, 8629) 9 (19, 4352) 10 (38, 3097) 11 Deviance .14 .42 .41 .39 .18 .04 .32 .22 (19, 7219) 1 (29, 9447) 4 (5, 1892) 12 (4, 1064) 12 (28, 8474) 4 (3, 2315) 12 (18, 3406) 4 (43, 11,342) 4 Note: In each cell, next to the main correlation, we report the corrected correlation (r) outside the parentheses, and the number of studies (k) and number of participants (N) within the parentheses. 1 Sverke et al., 2019; 2 Mackey et al., 2017; 3 Zhang & Liao, 2015; 4 Mackey et al., 2021; 5 Frazier et al., 2017; 6 Legood et al., 2021; 7 Zare & Flinchbaugh, 2019; 8 Judge & Bono, 2001; 9 Chiaburu et al., 2011; 10 Harari et al., 2016; 11 Nielsen et al., 2009; 12 from our own meta-analysis. 88 ECONOMIC AND BUSINESS REVIEW 2023;25:79–102 Fig. 3. Mediation model with job insecurity as an antecedent. Note: ND 3047. *** p< .001. Fig. 4. Mediation model with psychological safety as an antecedent. Note: ND 2890. *** p< .001. task performance (indirect effectD .08, p < .000), organizational citizenship behavior (indirect effectD .04, p < .000), deviance (indirect effectD .31, p < .000), and creativity (indirect effectD .14, p < .000) on the other. Knowledge hiding is a mediator between neuroticism on the one hand and task performance (indirect effectD .09, p < .000), organizational cit- izenship behavior (indirect effectD .07, p < .000), deviance (indirect effectD .18, p< .000), and creativity (indirect effectD .16, p< .000) on the other. Knowl- edge hiding is a mediator between distrust on the one hand and task performance (indirect effectD .05, Fig. 5. Mediation model with abusive supervision as an antecedent. Note: ND 2951. *** p< .001. ECONOMIC AND BUSINESS REVIEW 2023;25:79–102 89 Fig. 6. Mediation model with neuroticism as an antecedent. Note: ND 3068. *** p< .001. Fig. 7. Mediation model with distrust as an antecedent. Note: ND 3048. *** p< .001, * p< .05. p < .000), organizational citizenship behavior (indi- rect effectD .02, p< .05), deviance (indirect effectD .11, p< .000), and creativity (indirect effectD .02, p< .001 on the other). 4 Discussion 4.1 Theoretical implications and general discussion This meta-analytic review takes stock, in quantita- tive terms, of the nomological network of knowledge- hiding antecedents and outcomes. It is a response to the urgent need for a comprehensive analysis of the decade-long, rapid, and rather divergent devel- opment of the knowledge-hiding topic into several fragmented multi- and even atheoretical subdomains. Our intention is to complement a set of recent qualitative literature reviews and one very recent meta-analysis (Arain et al., 2022) in order to jointly integrate, advance, and partially redirect the growing and maturing eld of knowledge hiding in organiza- tions. The meta-analytical results generally support expected relationships across the vast majority of cat- egories of knowledge-hiding antecedents, including job characteristics, leadership, attitudes and motiva- tions, working context, personality, and individual differences. Knowledge hiding is related to outcomes including creativity, task performance, incivility, de- viance, and deterioration of workplace behavior. We also provide comprehensive empirical evidence to support the conceptual claim that knowledge hiding is not correlated with knowledge sharing. Further- more, we have also tested mediations of the most salient antecedents of knowledge hiding within each of the ve categories of antecedents. Our rst theoretical contribution that will help carry the knowledge-hiding eld forward is related to establishing a nomological network of knowledge hiding (Fig. 2) based on quantitative meta-analytic measures, validating its most important antecedents, correlates, and outcomes. In terms of antecedents, theoretically interesting non-ndings are related to the relationship between knowledge hiding and job design variables, and climate. Neither autonomy nor 90 ECONOMIC AND BUSINESS REVIEW 2023;25:79–102 Table 3. Indirect effects from antecedents to outcomes via knowledge hiding (KH). Indirect effects p values Model 1 Job insecurity! KH! Performance 0.07 0.000 Job insecurity! KH! Organizational citizenship behavior 0.06 0.000 Job insecurity! KH! Deviance 0.14 0.000 Job insecurity! KH! Creativity 0.11 0.000 Model 2 Psychological safety! KH! Performance 0.02 0.056 Psychological safety! KH! Organizational citizenship behavior 0.02 0.053 Psychological safety! KH! Deviance 0.13 0.000 Psychological safety! KH! Creativity 0.14 0.000 Model 3 Abusive supervision! KH! Performance 0.08 0.000 Abusive supervision! KH! Organizational citizenship behavior 0.04 0.000 Abusive supervision! KH! Deviance 0.31 0.000 Abusive supervision! KH! Creativity 0.14 0.000 Model 4 Neuroticism! KH! Performance 0.09 0.000 Neuroticism! KH! Organizational citizenship behavior 0.07 0.000 Neuroticism! KH! Deviance 0.18 0.000 Neuroticism! KH! Creativity 0.16 0.000 Model 5 Distrust! KH! Performance 0.05 0.000 Distrust! KH! Organizational citizenship behavior 0.02 0.029 Distrust! KH! Deviance 0.11 0.000 Distrust! KH! Creativity 0.02 0.001 Note: p< .05. task interdependence have exhibited a signicant re- lationship with knowledge hiding across studies. So far it seems that individuals tend to hide knowledge regardless of how their work is structured, indicating that job design in not related to employee decisions to hide knowledge. However, it is also possible that the analyses conducted require more granularity, as there is evidence that relational job design matters for em- ployee prosocial behaviors (Grant & Berry, 2011) and could therefore mitigate motivations to hide knowl- edge. We encourage future researchers in the domain of knowledge hiding to explore the role of relational design. Individual characteristics and situational interper- sonal dynamics seem more relevant, and should be the focus of subsequent research on the matter. As for organizational climates, they do not seem to have a signicant link with knowledge hiding either. In fact, this non-nding is consistent with and corrob- orates the context theory of organizational behavior (Johns, 2006), or trait activation theory (Tett et al., 2021), which propose climates and other contextual variables are more plausible boundary conditions as opposed to direct effects of individual behavior at work. In terms of the outcomes of knowledge hiding, we have found meta-analytic evidence for the nega- tive correlation with creativity and task performance. Evidence supports the self-damaging nature (“shoot- ing oneself in the foot”) of hiding knowledge (cf. ˇ Cerne et al., 2014), which means knowledge hiders’ performance in creative or non-creative tasks is im- paired. This nding corroborates the vast amount of knowledge-hiding research that is based on the social exchange theory and norm of reciprocity and conrms this is an important future direction of the eld as well, especially in light of the established positive associations between knowledge hiding and incivility, deviance, and deterioration of workplace relationships. On the other hand, innovation does not emerge as a signicant outcome of knowledge hiding. This is in line with macro-innovation (Thayer et al., 2018; van Knippenberg, 2017) research beyond the focus on individual innovative work behavior, and is an outcome of team dynamics, resource allocation, and individual creative contributions. Turnover in- tentions, too, seem to be perhaps a too distal construct from knowledge-hiding behavior, indicating that the eld should develop further by examining proximal and theoretically coherent outcomes of knowledge hiding. Second, our supplementary mediation analyses also support knowledge hiding acting as a media- tor for most specied relationships from job design, individual and leadership phenomena leading to task performance, organizational citizenship behav- ior, creativity, and deviance. This nding advances the eld of knowledge hiding in an important way, as ECONOMIC AND BUSINESS REVIEW 2023;25:79–102 91 the vast majority of studies treat knowledge hiding either as an antecedent of a positive or a negative out- come, or as an outcome (usually negative) of its own. Our meta-analytic mediation ndings indicate that process models and those that propose knowledge hiding acts as an explanatory mechanism between two phenomena or behaviors are more than plausi- ble, and additional theoretical and empirical work is warranted in this area. Third, our meta-analytic review contributes to the broader knowledge management literature by balancing between knowledge sharing, a vast and developed eld, and the growing and maturing knowledge-hiding eld. Our ndings empirically val- idate the orthogonality between knowledge hiding and lack of knowledge sharing. While they are con- ceptually and empirically two distinct constructs, the seeming similarity is a frequent concern of review- ers and editors alike. Furthermore, it is also evident that the nomological networks of knowledge hiding and knowledge sharing (Lim, 2021; Nguyen et al., 2019; Witherspoon et al., 2013) are distinct. Our nd- ings will help authors interested in knowledge hiding strengthen their case beyond conceptual and deni- tional arguments. We hope that researchers can use our meta-analysis to refrain from having to revalidate that the two concepts are different, which happens all too frequently. Fourth, on the basis of ndings related to meta- analytic evidence on knowledge-hiding correlates, antecedents, outcomes, and mediators, this study also helps in empirically differentiating between knowl- edge hiding and related constructs that have prolifer- ated without much empirical evidence of differential effects, such as knowledge hoarding or withhold- ing. Our meta-analysis goes beyond previous review studies, not only because we use a bigger sample size of primary studies (see Appendix, Table A1), but also by avoiding conceptualization confounding of vari- ous distinctive constructs, such as knowledge hiding and knowledge hoarding. By focusing only on studies related to knowledge hiding, we provide some pre- liminary evidence of covariates and effect sizes of the knowledge-hiding nomological network, but at the same time also conceptual clarity of the possible ef- fect sizes and directions of the nomological network, which truly relate to knowledge hiding per se, rather than other similar, yet distinct constructs. Fifth, our study was submitted for publication al- most at the same time as another meta-analysis (Arain et al., 2022) emerged. Although the studies were blind to each other’s existence, we still contribute above and beyond this piece of research. First, we have a much larger sample and therefore an even more solid basis for our claims. Second, we test mediation mechanisms, which the previous meta-analysis does not. Third, we provide a comprehensive overview of the existing knowledge-hiding reviews and one meta- analysis that will be appreciated by researchers in knowledge hiding in the years to come. 4.2 Future research suggestions We have conducted a semantic analysis of sug- gested content-related limitations and future research directions by authors in the eld using the same articles as in the meta-analysis to provide a more comprehensive insight into the possible future of knowledge-hiding research. Specically, we have fo- cused on the future directions section of each article and coded each possible future direction suggested by the article. Our ndings suggest several opportu- nities, beyond merely identifying “hot topics.” Table 4 provides an overview of future research directions as mentioned in the primary articles of our meta- analytic review. Our coding has provided the follow- ing categories of potential future research directions. New variables refer to potential new variables to be included in the model or to change in the position of some variables in the model (e.g., from mediator to a moderator). In a few cases, this also relates to specic suggestions for moderators, mediators, predictors, or consequences of knowledge hiding. We argue that the choice of new variables should be much more theoret- ically driven than it was the case in the rst decade of the knowledge-hiding eld. Context relates to adding new countries, indus- tries, or groups to validate existing ndings. Fortu- nately, empirical contexts that cover the domain of knowledge hiding do not suffer from the WEIRD (Western, Educated, Industrialized, Rich, and Demo- cratic) phenomenon. Empirical context encompasses North America, Europe, Asia, and Oceania. The plu- ralistic development of the eld turns out to be an advantage in the case of context coverage. Research design focuses on suggesting executing the models presented longitudinally. The level of analysis relates to theoretical and methodological suggestions, to add different levels to the model or collect data from different levels. Sample relates to issues about the sam- ple, such as expanding the sample. Methods relate to suggestions to use different methods or triangu- late the methods used with new ones to get a better sense of the data (e.g., content analysis, use of mixed methods, etc.). Under replication, the authors suggest replicating their study. Dimensions of knowledge hid- ing relate to calls to explore the facets of knowledge hiding separately. We have to acknowledge that it is not yet possible to conduct meta-analyses for sepa- rate knowledge-hiding dimensions as there are not 92 ECONOMIC AND BUSINESS REVIEW 2023;25:79–102 Table 4. Key future research directions mentioned by primary articles. Future research direction Count New variables Most frequent role Count New variables (Moderator – 9; New variables – 58; Mediators – 5; Consequences of KH – 4; Predictors of KH – 2). 78 Support (Supportive culture and climate, social support, supervisors support, support HR) Moderator 5 Context 54 Political skill Moderator 5 Research design (longitudinal) 54 Leadership styles and behavior Moderator or mediator 5 Level of analysis 42 Moral disengagement and differences Moderator or mediator 4 Sample 32 Trust (employees’, cognitive, general) Mediator 3 Methods 14 Supervision (abusive, role-modeling capacity/inuence, supervisor-based self-esteem) Moderator 3 Replication 11 Psychological safety Moderator 3 Dimensions of knowledge hiding 10 Motivation (climate, intrinsic, mastery climate) Moderator 3 Experimental design 7 Identication (department, group, organization) Mediator 3 Tacit/explicit knowledge hiding 5 Goal interdependence and commitment Mediator 3 Theories 5 Big ve personality traits Moderator 3 Task interdependence Moderator 3 Climate (knowledge sharing, mastery motivational climate) Moderator 3 Note: Content-related suggestions related to new variables are shaded in grey. enough empirical studies distinguishing between ra- tionalized, evasive, and “playing dumb” dimensions of knowledge hiding. Under experimental design, au- thors suggest complementing their research design with an experimental design. Tacit/explicit knowledge hiding relates to calls that knowledge-hiding behavior should be divided into hiding tacit or explicit types of knowledge and information. Theories explore the notion that other, previously unused theories (e.g., affective event theory) can be used to propose new research variables. The vast majority of the authors suggested adding new variables, and the list is rather long. While this is a valid research direction, the peril of further con- ceptual proliferation and atheoretical development is imminent. The need to theoretically solidify the eld after a decade of rapid growth is pertinent. Researchers could use this meta-analytic review as a complement to a set of recent systematic litera- ture reviews in informing their theoretical choices. At a minimum, future research should avoid being atheoretical. At best, it should make sure to use over- arching theories in further advancing the eld. The most widely used theories so far are social exchange, cognitive theory of stress appraisal, conservation of resources, and coping. We nd the affective events theory promising as it could explore knowledge hid- ing as an event taking place across time and varying within a person. Furthermore, our meta-analytical results suggest the importance of context and con- textual theories. Emerging climates and designed HR practices, which form HR systems, can be potentially seen as contexts providing stimuli for how indi- viduals should behave (including behaviors such as knowledge hiding). Another such contextual variable is culture, where its constituents at and across dif- ferent levels (team, organizational, country) could be investigated. Researchers could potentially tap into multi-level theory to provide strong theorizing about such emerging contexts by appropriately describing the origin, denition/conceptualization, and oper- ationalization of contextual variables in relation to knowledge hiding. We still do not have a complete enough under- standing of the nomological network. For instance, there are numerous opportunities related to under- standing how various leadership styles are correlated with knowledge hiding. It is reasonable to expect that positive forms of leadership, such as trans- formational leadership and post-heroic leadership, could reduce the frequency of knowledge-hiding be- haviors in teams and organizations. It is important to understand antecedents that could increase or decrease knowledge-hiding behaviors. In terms of outcomes, prior research has largely focused on be- havioral outcomes at the individual level. We do not yet know how knowledge hiding relates to a large variety of outcomes at the team and organizational levels. Future studies should not shy away from empirical contributions through replication and reporting non- ndings and should also specically focus on exam- ining potentially differential effects (or non-effects) across knowledge-hiding facets; this is something that is clearly missing or is not yet studied suf- ciently. These will contribute to strengthening the ECONOMIC AND BUSINESS REVIEW 2023;25:79–102 93 meta-analytical evidence for such an important phe- nomenon as knowledge hiding. In addition to theoretically solidifying the eld, there are numerous methodological opportunities ahead. The vast majority of studies so far have been conducted at the individual level, with only four stud- ies at the team level. The opportunities ahead lie in extending the team level, expanding towards the or- ganizational level, and studying knowledge hiding across levels. It is important to see how the negative effects of knowledge hiding emerge at higher levels, such as the team level and organizational level, and vice versa, how higher-level phenomena inuence knowledge hiding at lower levels. What is perhaps the most interesting is that knowledge hiding should be studied at the within-person level more often. Thus far, this has not been adequately studied, with only recent notable exceptions of Venz and Mohr (2022), Venz and Nesher Shoshan (2022), and Xia et al. (2022). Knowledge hiding is, by denition, an event-based phenomenon as it happens in response to the request of another person. Therefore, intrapersonal variance across a series of events and time points will be most welcome in future research. Moreover, studies that capture the true nature of the dyadic phenomena of knowledge hiding using appro- priate relational statistical techniques (social network analysis, relational modeling regressions) are almost completely absent. Using classical regression statisti- cal techniques might not sufce to capture the extent of the knowledge-hiding dynamics (cf. Connelly et al., 2019) when relational aspects are in focus and can cause severe issues as well. For example, in stan- dard OLS regression, observations are assumed to be independent, whereas dyadic data (such as the conceptualization of knowledge hiding) in essence strongly violates this assumption, severely biasing the standard error estimate (Wasserman & Faust, 1994). This suggests that statistical procedures that do not assume independence of observations (e.g., social net- work analysis, multi-level analysis) might be used to alleviate such problems. 5 Conclusion After its rst decade of existence, knowledge- hiding research warranted an integrative and com- prehensive literature review backed with meta- analytical and semantic evidence. While we acknowl- edge and appreciate past efforts, we wanted to complement those with a meta-analytic review that solidies the theoretical foundations, integrates the fragmented literature, and redirects the future growth of the knowledge-hiding eld. Our sincere hope is that this paper has done exactly that by capturing theoretical origins, meta-analytically validating the most salient antecedents, outcomes, and correlates of knowledge hiding, creating a quantitatively based nomological network of knowledge hiding, and sug- gesting theoretical and methodological advances for this quickly growing, but maturing eld. Even though our meta-analytical review is critical of the fragmented nature of the knowledge-hiding research in its rst decade, we aim to be construc- tive and look forward with optimism. While facing some growth pains affecting any nascent domain, the eld of knowledge hiding is addressing an important and long-overlooked phenomenon. It should not be surprising to witness rapid growth in the quantity of publications spread across the globe, scientic disci- plines, theories, journals, and methodological tradi- tions. Our sincere hope is to simultaneously build on the diversity and richness of those perspectives, while also solidifying the theoretical foundations for further growth toward quality and impact. Funding statement This research was supported by the Slovenian Re- search Agency Core Project Funding (P5-0441). The funders had no role in the study design, data collec- tion and analysis, decision to publish, or preparation of the manuscript. References Abdullah, M. I., Dechun, H., Ali, M., & Usman, M. (2019). Ethi- cal leadership and knowledge hiding: A moderated mediation model of relational social capital, and instrumental thinking. Frontiers in Psychology, 10, 2403. https://doi.org/10.3389/fpsyg .2019.02403 Agarwal, U. A., Avey, J., & Wu, K. (2021). 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(2014). Bibliometric methods in management and organization. Organizational Research Methods, 18(3), 429– 472. https://doi.org/10.1177/1094428114562629 ECONOMIC AND BUSINESS REVIEW 2023;25:79–102 97 Appendix Table A1. Comparison of existing knowledge-hiding reviews. Objectivity Comprehensiveness and integrativeness Methods/ Meta- Biblio- Sample Time period Databases Additional ltering Keywords Focus of procedure analysis metrics covered criteria for search the review Škerlavaj, ˇ Cerne, Batistiˇ c (our study) Meta-analytic review Yes No Meta-analysis: 342 primary documents, 131 studies and 147 samples with 47,348 participants included January 2012– March 2021 EBSCO Host, Emerald, Jstor, Oxford Press, ProQuest, Sage Journals, Science Direct, Springer Link, Taylor and Francis, Web of Science Only works related to: management, library science, business, psychology applied, information systems, articial intelligence, psychology multidisciplinary, computer science theory and methods, hospitality leisure, sports tourism, communication, ethics, educational research, nursing, operations research management science, political science, psychological social, economics, ergonomics, multidisciplinary sciences, psychological experimental, social sciences interdisciplinary Growth curve: 2012–2020 “knowledge hiding” Nomological network, mediating mechanisms, comprehensive overview of meta-analyses and systematic literature reviews (continued on next page) 98 ECONOMIC AND BUSINESS REVIEW 2023;25:79–102 Table A1. (continued) Objectivity Comprehensiveness and integrativeness Methods/ Meta- Biblio- Sample Time period Databases Additional ltering Keywords Focus of procedure analysis metrics covered criteria for search the review Arain et al. (2022) Meta-analysis Yes No Meta-analysis: 104 studies with 31,822 participants included October 2010– August 2021 Google Scholar, JSTOR, APA PsycArticles, ProQuest central, ProQuest dissertation and thesis, Informs, Scopus, Taylor & Francis, and Wiley Online Library (1) knowledge hiding, (2) hiding knowledge, (3) evasive hiding, (4) playing dumb, (5) rationalized hiding, (6) knowledge withholding, and (7) withholding knowledge. Nomological network Anand et al. (2020) Systematic reviews concerned with synthesis No No 66 articles – Scopus, ProQuest, EBSCO and Google Scholar – Knowledge hiding Events leading to knowledge hiding Anand et al. (2021) Systematic literature review No No 84 articles Between 2012 and October 2020 Scopus Blind peer-reviewed journal articles “Knowledge Hiding” “Hiding Knowledge” “Knowledge Hoarding” “Knowledge Withholding” “Knowledge Detention” “Knowledge Concealment” “Non-sharing Knowledge” “Knowledge Sharing Barrier” “Knowledge Sharing Resistance” “Knowledge Sharing Disengagement” “Knowledge Sharing Obstruction” “Knowledge Sharing Hostility” “Knowledge Sharing Blockage” “Organizational Knowledge Hiding” “Organizational Knowledge Hoarding” “Organizational Knowledge Withholding” Systematic research on knowledge hiding (continued on next page) ECONOMIC AND BUSINESS REVIEW 2023;25:79–102 99 Table A1. (continued) Objectivity Comprehensiveness and integrativeness Methods/ Meta- Biblio- Sample Time period Databases Additional ltering Keywords Focus of procedure analysis metrics covered criteria for search the review Di Vaio et al. (2021) Bibliometric analyses and content analyses No No 117 articles 1988–2020 Scopus, Web of Science, Google Scholar Document types: Article, Book Chapter, Conference Papers, and Article in Press “Knowledge hiding” AND “Knowledge Management” “Knowledge hiding” AND “Business Organization” OR “Board of Directors” “Knowledge hiding” AND “consequences” “Knowledge hiding” AND “strategic performance” Systematic literature review on how KH contributes to individuals, groups, and the business processes of corporate organizations specically with regards to improving employee performance, strategic performance, and the organization’s overall knowledge management system (KMS). He et al. (2021) Systematic review process Partially, mostly pro- duc- tive indica- tors No 81 articles 2012–2020 Web of Science Core Collection Excluded those that belonged to disciplines such as information management “TitleD knowledge hiding” or “TitleD knowledge withholding” Research themes of knowledge hiding include ve clusters: concept and dimensions, antecedents, consequences, theories, and inuence mechanisms Irum et al. (2020) – No No – 2000–2019 EBSCO and Google Scholar Articles listed as A* and A under the ABDC journal list ‘Workplace incivility’, ‘uncivil behaviour’, ‘negative workplace behaviour,’ and ‘workplace mistreatment’ Workplace incivility and knowledge hiding Issac et al. (2021) Morphological analysis No No 68 articles – Scopus Only works related to business and management disciplines “Knowledge hiding” or “knowledge withholding” Systematic research on knowledge hiding (continued on next page) 100 ECONOMIC AND BUSINESS REVIEW 2023;25:79–102 Table A1. (continued) Objectivity Comprehensiveness and integrativeness Methods/ Meta- Biblio- Sample Time period Databases Additional ltering Keywords Focus of procedure analysis metrics covered criteria for search the review Oliveira et al. (2021) Systematic literature review Partially, mostly productive indicators No 50 articles Until July 20, 2020 Scopus, Web of Science, Science Direct, Emerald, and Wiley Online databases Only journal articles in the English language (“knowledge hid*” and “survey”) or (“knowledge hoard*” and “survey”), in the “title, abstract and keywords” option in Scopus and “topic” in the Web of Science. The keywords “KHo” or “knowledge hoard” or “knowledge hide,” or “KHi” and “survey” were used in Wiley Online. In Science Direct and Emerald, the keywords were “Kho,” “knowledge hoard,” “knowledge hide,” “KHi” one at a time, and articles involving “survey” were selected manually. Knowledge Hiding and Knowledge Hoarding, and the relationship with Knowledge Sharing. Rezwan and Taka- hashi (2021) Systematic literature review process No No 88 empirical articles 1900 onwards for Web of Science; 1960 for Scopus Scopus, Web of Science Excluded all books, book chapters, meeting abstracts, and articles that were not in English Checked the title and abstracts of the studies in their Excel spreadsheet database utilizing keywords in the lter function (i.e., “hide,” “hiding,” “employee,” “organization,” ”organisation,” WOS search: TOPIC: (knowledge hid) OR TOPIC: (knowledge hiding) OR TOPIC: (knowledge withhold) OR TOPIC: (knowledge withholding) Timespan: 1900–2021. Databases: WOS, KJD, RSCI, SCIELO. Scopus search: TITLE-ABS-KEY (knowledge AND hid) OR TITLE-ABS-KEY (knowledge AND hiding) OR Use a cognitive– motivational– relational (CMR) theory of emotion to create a framework for other knowledge- hiding studies’ ndings. (continued on next page) ECONOMIC AND BUSINESS REVIEW 2023;25:79–102 101 Table A1. (continued) Objectivity Comprehensiveness and integrativeness Methods/ Meta- Biblio- Sample Time period Databases Additional ltering Keywords Focus of procedure analysis metrics covered criteria for search the review Methods/ Meta- Biblio- Sample Time period Databases Additional ltering Keywords Focus of procedure analysis metrics covered criteria for search the review “hide knowledge,” “hiding knowledge,” “hid,” “knowledge hid,” “knowledge-hid,” “knowledge withhold,” “knowledge- withhold,” “withhold knowledge,” “withholding knowledge,” and “withhold”) Excluded the qualitative, theoretical, and review studies TITLE-ABS-KEY (knowledge AND withhold) OR TITLE-ABS-KEY (knowledge AND withholding). Ruparel and Choubisa (2020) Narrative analysis No No 38 articles 2008–2019 Web of Science, Scopus, Google Scholar, Emerald, Wiley, SAGE, EBSCO, and ProQuest – “knowledge hiding,” “knowledge hiding among organizations,” and “knowledge hiding in employees” Systematic and retrospective review Silva de Garcia et al. (2022) Content Analysis No No 57 articles – Web of Science and Scopus – “Knowledge hiding” and “Knowledge hoarding” Integrative framework Strik et al. (2021) Review table No No 42 articles, of which 29 are about knowledge hiding – Business Source Complete, SocINDEX, ERIC, and PsycInfo For EBSCO Business Source Complete, they enabled searches in the engine “SocINDEX with full text.” They also applied the features “apply related words,” “apply equivalent subjects,” “knowledge hoarding,” “knowledge hiding,” and “knowledge withholding” Antecedents of knowledge withholding (continued on next page) 102 ECONOMIC AND BUSINESS REVIEW 2023;25:79–102 Table A1. (continued) Objectivity Comprehensiveness and integrativeness Methods/ Meta- Biblio- Sample Time period Databases Additional ltering Keywords Focus of procedure analysis metrics covered criteria for search the review and “scholarly (peer-reviewed) journals.” In the ERIC engine, they used the default settings and enabled the feature “peer reviewed only.” The PsycInfo engine was used with default settings plus the additional selection features of “empirical evidence” in the methodology box and “peer- reviewed journals.” Xiao and Cooke (2019) – No No 52 articles 1997–2017 EBSCO, Web of Science, ProQuest, Emerald, Springer, SAGE, and Wiley. They used the Chinese equivalents of the English keywords to search CNKI (a major database of Chinese journals). Workplace knowledge- hiding behavior within the organization and related to HRM ‘knowledge hiding,’ ‘knowledge withholding,’ ‘information hiding,’ ‘information withholding,’ ‘data withholding,’ ‘partial knowledge sharing,’ ‘knowledge sharing hostile,’ ‘knowledge hoarding’ Knowledge hiding in China