The Effect of Person-Team Conscientiousness Fit on Knowledge Sharing: The Moderating Role of Internal Team Environment

Abstract

Drawing on studies of person-team fit and theory of team-member exchange, we examined the effect of fit versus misfit between a team member’s conscientiousness and his/her team’s composition of conscientiousness on the member’s knowledge sharing. We hypothesized that person-team conscientiousness fit would lead to more knowledge sharing because a member who fits his/her team with respect to conscientiousness tends to have similar achievement striving with the team and low exchange cost. Using the method of polynomial regression in two studies in different regions and research settings, we obtained consistent results that person-team conscientiousness fit is positively associated with a team member’s knowledge sharing. We further found that internal team environment moderates the relationship between person-team conscientiousness fit and knowledge sharing such that it makes the relationship weaker. Our study demonstrated that to better understand the effect of personality on knowledge sharing in teams, it is beneficial to simultaneously consider the interplay among member personality, team personality, and team contexts.

Keywords

knowledge sharing conscientiousness person-team fit team-member exchange internal team environment

In today’s knowledge economy, work teams are more reliant than ever on members’ knowledge to accomplish goals (Davenport & Prusak, 1998; Grant, 1996; Spender & Grant, 1996). For many organizations, merely using one’s knowledge to complete required jobs is no longer enough; sharing knowledge has become a highly desired behavior (Bartol & Srivastava, 2002). What influences individuals’ knowledge sharing has thus received extensive research attention (e.g., Bock, Zmud, Kim, & Lee, 2005; Cabrera, Collins, & Salgado, 2006; Matzler, Renzl, Mooradian, von Krogh, & Mueller, 2011; Witherspoon, Bergner, Cockrell, & Stone, 2013), among which personality traits have been thought to be crucial (Wang & Noe, 2010).

Personality is a fundamental personal disposition that predicts a person’s attitudes, intentions, and behaviors. The five-factor model has been identified as a robust, comprehensive, and parsimonious taxonomy of personality traits (Costa & McCrae, 1992; Digman, 1990; Goldberg, 1992), including extraversion, agreeableness, conscientiousness, emotional stability, and openness to experience. Previous research has suggested that openness to experience, agreeableness, and conscientiousness could affect an individual’s knowledge sharing (Cabrera et al., 2006; Matzler, Renzl, Müller, Herting, & Mooradian, 2008); but the mechanisms through which these traits affect knowledge sharing may differ (Wang & Noe, 2010).

Knowledge sharing is based on self-willingness and directed toward others (Hau, Kim, Lee, & Kim, 2013), and fundamentally a social exchange behavior (Kang & Hau, 2014). It is not surprising that former research found a direct positive effect of “social” personality traits like openness to experience or agreeableness on knowledge sharing (Cabrera et al., 2006; Wang, Noe, & Wang, 2014). But the mechanism that links conscientiousness and knowledge sharing seems less obvious, as the nature of conscientiousness like being organized, achievement oriented, dependable, hardworking, and persevering are not necessarily social (Barrick & Mount, 1991). For example, a hardworking and dependable member may be trusted by peers for getting jobs done, but he/she may not go further to share knowledge to others. Extant research seems to corroborate this speculation by showing mixed results; some found a positive relation between conscientiousness and knowledge sharing (Cabrera et al., 2006), but others showed that such a relation did not necessarily exist (Wang et al., 2014; Waung & Brice, 1998). Hence, a critical question remains regarding the possible mechanism(s) that could connect an individual’s conscientiousness with his/her knowledge sharing.

We expect that, in workplace, team composition would facilitate the formation of such a mechanism. Teams are not a social vacuum. The composition of team members’ personality affects an individual’s perceptions of engaging in certain behaviors in team (Prewett, Walvoord, Stilson, Rossi, & Brannick, 2009); and an individual assesses his/her personality against that of the team for desired outcomes (Kristof-Brown, Barrick, & Kay Stevens, 2005). Team conscientiousness has been noted to be both a social condition for a focal individual that may trigger his/her conscientiousness (Tett & Burnett, 2003) and a frame of reference against which the individual can tell where his/her own conscientiousness stands (Choi, Lee, & Yoo, 2010). Hence, team conscientiousness may provide a “social” element that a member needs to estimate the personal and interpersonal desirability of behaviors like sharing knowledge.

Rooted in the person-environment fit tradition of group and organization research, person-team fit stresses the equal importance of an individual and team in his/her outcomes (Edwards, 1994). Research has shown that person-team personality fit is crucial to members’ attitudes and behaviors (Peeters, Van Tuijl, Rutte, & Reymen, 2006). For example, Kristof-Brown et al. (2005) found a complementary fit between individual extraversion and team extraversion such that a member was more attracted to a team when his/her extraversion is opposite to the team. Given that person-team fit makes exchange desirable (Edwards, 1994) and knowledge sharing reflects person-team exchange quality (Bock et al., 2005), we suggest that, to explore the relation between conscientiousness and knowledge sharing, it is important to examine conscientiousness fit between a member and his/her team instead of individual conscientiousness alone.

Person-team fit literature proposes that composition of certain individual-level characteristics to team level constitutes the environment that a person fits or not. However, the composition of individual characteristics at team level is not the whole team environment; other team environment variables (e.g., social support, cohesion, or leadership) are also important because they are the ones in which person-team fit exists and they may affect the extent to which person-team fit matters (Edwards, 1996). Therefore, team environment may become an overarching context for person-team fit such that it either facilitates or inhibits the degree that person-team fit affects knowledge sharing.

In this study, drawing upon person-team fit literature and team-member exchange theory (Seers, 1989; Seers, Petty, & Cashman, 1995), we examine the supplementary fit of member-team conscientiousness and its effect on member knowledge sharing in two studies in different regions and research settings (Study 1 and Study 2). In Study 2, we further explore the moderating effect of internal team environment (Carson, Tesluk, & Marrone, 2007) on the relationship between person-team fit and knowledge sharing. Our research contributes to the knowledge sharing and person-team fit literature in three important ways. First, we propose and examine supplementary fit, that is, the similarity of conscientiousness between a member and team, as a mechanism that links conscientiousness with knowledge sharing in teams. This mechanism explores cross-level interplay of member and team conscientiousness, allowing us to understand how personality traits affect knowledge sharing beyond individual level. Second, most former personality fit research took similarity attractiveness as their theoretical explanation. In this research, we apply team-member exchange theory to the relation between conscientiousness fit and knowledge sharing, thus extending our knowledge of personality fit to a team dynamic perspective. Third, previous fit research generally ignored its environment (Edwards, 1996). By examining the role of internal team environment in influencing the effect of conscientiousness fit on knowledge sharing, we disclose that person-team fit is not without its context. Figure 1 shows the overall theoretical model.

Figure 1.

Theoretical model.

Theory and Hypotheses

Knowledge Sharing and Person-Team Conscientiousness Fit

Knowledge sharing refers to providing task information and know-how to help and collaborate with others to solve problems, implement procedures, and complete tasks (Cummings, 2004; Pulakos, Dorsey, & Borman, 2003). Two characteristics of knowledge sharing are relevant to our study. First, knowledge sharing in teams is goal driven, that is, it depends on the goals and particular tasks of a team. When team goals and tasks require mutual interdependence among members, knowledge sharing would be desirable as it removes barriers to mutual understanding of work processes or outcomes (Lin, 2007a). Knowledge sharing raises the ability of a member and team to work toward the common end (Cummings, 2004), and they could use knowledge sharing as a means to achieving team goals (Wang & Noe, 2010). But if team tasks do not require too much interdependence, more knowledge sharing might not be necessary. In today’s organizations, team members seem more likely to work interdependently in responding to fast changes in business environment, making knowledge sharing desirable and welcome (Grant, 1996; Spender & Grant, 1996).

Second, knowledge sharing is a social exchange behavior that incurs benefits and costs (Bartol, Liu, Zeng, & Wu, 2009). Team-member exchange, derived from social exchange theory (Blau, 1964), aims to understand the reciprocity between a member and team with respect to the member’s contribution of ideas to the team and, in turn, receipt of information and help from the team. For knowledge sharing, a sharer could have positive exchange with team by getting benefit when the knowledge he/she shares receives feedback that enhances his/her own knowledge. But at the same time, knowledge sharing is also costly and, in many cases, considered relinquishing power or control (Lin, 2007b). Therefore, a member needs to consider the benefits and costs involved in team-member exchange when sharing knowledge.

Research showed that conscientiousness also has multiple aspects (Barrick & Mount, 1991; Hough, 1992). Costa and McCrae (1992) identified six facets—competence, order, dutifulness (dependability), achievement striving, self-discipline, and deliberation. Recently, Chae, Park, and Choi (2019) looked inward at individual-level conscientiousness and examined how two facets, achievement striving and dependability, respectively, affect knowledge sharing. Instead, in this research, we look outward and suggest that the cross-level person-team fit in conscientiousness plays important roles in a member’s knowledge sharing in team. Theoretically, like Chae et al. (2019), we also focus on achievement striving and dependability. Achievement striving is focused on setting goals and working hard to achieve them, which corresponds to the goal-driven characteristic of knowledge sharing; and dependability deals with commitment and caution, which corresponds to the social exchange part of knowledge sharing (Bartol et al., 2009; Marinova, Moon & Kamdar, 2013). The person-team fit could influence the member’s incentive to initiate knowledge sharing and/or respond to the team’s requests for knowledge. We do not rule out the role of the rest four facets in knowledge sharing as they are closely related to achievement striving or dependability. For example, competence strengthens achievement striving; achievement striving points out the direction for competence. Order or being organized may be considered as a cue for how dependable a person is.

There are four scenarios of person-team conscientiousness fit or misfit. First, a member and a team can both have high conscientiousness and fit (similarly high conscientiousness). Second, they can both have low conscientiousness and fit (still similar but at low conscientiousness). Third, a member can be more conscientious than the team (one scenario of misfit). And finally, a member is less conscientious than the team (the other scenario of misfit). We argue that these four scenarios would have significantly different implications for the member’s team-member exchange and knowledge sharing behavior in team.

First, when a member and team are similarly high on conscientiousness (i.e., high–high fit), exchange between them should be positive and reciprocal, which prompts knowledge sharing. For achievement striving, the goals set by the member and team should be high; they also tend to agree on the direction and level of effort for achieving the goals (Prewett et al., 2009). When both parties are aligned on goals and effort, the member may strongly believe sharing knowledge as part of his/her effort, which contributes to team achievements and his/her own individual achievements. For dependability, the member and team would have strong faith in each other’s trustworthiness; and sharing knowledge is mutually positively reciprocal and expected (Chow & Chan, 2008; Hofmann & Jones, 2005). The member is highly likely to consider sharing knowledge as an in-role behavior and do it without thinking twice (Lin, 2007a). Therefore, shared high achievement striving and mutual dependability should motivate the member to proactively initiate knowledge sharing and actively respond to others’ knowledge requests.

Second, when a member and team are similarly low on conscientiousness (low–low fit), the member would still share knowledge to certain extent as he/she could perceive some consistency between him/her and the team. For achievement striving, the member and team should still have agreed goals and effort direction/level—probably meeting the minimum work requirements with little effort. Team-member exchange seems nonnegative, if not positive, as neither party worries about being challenged or threatened by others’ high achievement (Marinova, et al., 2013; Tasa, Sears, & Schat, 2010), thus allowing a relaxing context for communication (Seers et al., 1995). In such a context, the member would share knowledge because, on the one hand, he/she may perceive a low barrier to initiating knowledge sharing; on the other hand, his/her teammates may not hesitate to request knowledge from him/her. As for dependability, being mutually low reduces unrealistic overexpectations and the likelihood of being judged negatively. Over time, team-member exchange would be stabilized in a benefit–cost balanced manner (Seers, 1989); the social cost of sharing knowledge such as losing personal control is unlikely to exceed its benefit such as getting the team job done. Sharing knowledge, thus, is safe. In all, the member should not restrain from sharing knowledge (Waung & Brice, 1998), as doing so is safe and has low barrier.

Third, when a member has higher conscientiousness than the team (high–low misfit), team-member exchange could involve great disappointment for the member. For achievement striving, the goals set by the team may not be challenging enough for the member; the two parties may also have significant disagreement on the direction/level of work effort. Misalignment of goals and effort makes exchange difficult (De Dreu & Weingart, 2003). The team could even regard the member as “rate-buster” and reject knowledge proactively shared by the member, which would demotivate his/her tendency to share. For dependability, former research suggested that it is other-centered (Moon, 2001); however, even a dependable other-centering member needs to compare benefit and cost. He/she may share knowledge several times out of high dependability, overlooking equal reciprocity from the team. But in the long run, a noticeable imbalance that the member is the one who always takes the cost will make him/her think twice before sharing knowledge with the team (Bock et al., 2005; Lin, 2007b). The member could be demotivated enough and withhold knowledge.

Fourth, when a member has lower conscientiousness than the team (low–high misfit), team-member exchange could marginalize the member. For achievement striving, the team may believe that the member cannot meet its achievement expectation (Humphrey, Hollenbeck, Meyer, & Ilgen, 2007), thus ignoring or degrading his/her knowledge. Any knowledge shared by the member may be easily regarded as irrelevant, unnecessary, or useless, which discourages the member from initiating knowledge sharing. For dependability, the team may avoid assigning important jobs to the member or asking him/her for knowledge, given their assumption that the member is not dependable. The member’s chance of responding to knowledge requests becomes low. In addition, the member is also likely to be excluded from team brainstorming or decision-making, further discouraging him/her from sharing what he/she knows.

By comparing the four scenarios above, we posit that the similarity scenarios are likely to either encourage a member to share knowledge or lower the barrier to sharing and make sharing safe; whereas dissimilarity scenarios would discourage or demotivate a member’s knowledge sharing. Thus:

Hypothesis 1: A member whose conscientiousness fits that of the team will engage in more knowledge sharing than a member whose conscientiousness does not fit the team.

Knowledge Sharing at High–High Fit Versus Low–Low Fit of Conscientiousness

As mentioned above, in the two fit scenarios, a member and a team can fit at either high or low conscientiousness. We propose that the high–high fit scenario should prompt a member to engage in more knowledge sharing than the low–low fit scenario. For achievement striving, the member and team are more oriented toward collectively high achievement in the high–high fit scenario. A sense of mutual accomplishment could occur and shape the team-member exchange. For the member, sharing more knowledge is personally rewarding; for the team, sharing knowledge increases the chance of achieving high team goals. But in the low–low fit scenario, knowledge sharing seems less rewarding as team and personal goals are lower. A member may also have less incentive to share knowledge if he/she finds that it is energy consuming to explain what he/she knows to the team (such as in the case of tacit knowledge).

For dependability, in the high–high fit scenario, team-member exchange is characterized by mutual trust and probably positive emotional investment (Blau, 1964). The member’s high dependability gives him/her strong motivation to be highly responsive to the teams’ requests for knowledge, especially when he/she knows that others are also dependable and responsive to his/her knowledge request. Sharing knowledge tends to be socially reinforced. But in the low–low fit scenario, dependability seems not a great concern; mutual expectations between the member and the team for reciprocation are less likely to involve long-term emotional investment (Ryan & Kristof-Brown, 2003). Hence, a member may just share knowledge to the extent that benefit–cost balance is roughly achieved. We hypothesize that:

Hypothesis 2: A member will engage in more knowledge sharing when he/she fits with team at high conscientiousness than fits with team at low conscientiousness.

Study 1: Method

Participants and Procedure

The goal of Study 1 was to test Hypothesis 1 and 2 in real-world teams. Data were collected from medical professionals who worked on quality control circle (QCC) teams in three large hospitals in Taiwan. Teams were formed to conduct medical and patient care research projects assigned by the hospitals. A team generally lasted for several years working on the same project, and then disbanded after the research was finished. A QCC team comprised one team leader (a head nurse) and several team members who were also nurses. Knowledge sharing was not part of performance evaluation for participants but was important for success of their team projects.

At Time 1, we distributed surveys to 62 team leaders and 512 members, asking them to assess their own personality traits. One year later, at Time 2, members and leaders were asked to assess their own knowledge sharing within teams in the previous year. We chose time lag of 1 year because their research projects used 1 year as a cycle; the hospitals evaluated project progress at the end of each cycle and decided to stop or continue it into next year. At both Time 1 and 2, the researcher distributed questionnaires during team meetings and confidentiality was ensured. As introduced above, these teams did not continue indefinitely and disbanded after their research topics finished. Among the 62 teams at Time 1, 44 teams were still in place at Time 2. Of the 44 teams, we were able to collect usable personality traits data from 27 teams and 200 participants. On average, participants have been working on their teams for 2.63 years (sd = 1.08). An average of 9 persons (3–15) were on each team and completed the surveys. 96 (48%) participants were men. Their average age was 32.01 years old (SD = 8.45), with an average education of undergraduate, and average organizational tenure of 4.33 years (sd = 2.57). To determine whether the high attrition rate led to nonrandom sampling, we examined whether the participants included in the attrition data were significantly different in terms of age, gender, or education from those included in the final data. Following Goodman and Blum (1996), we created a binary outcome model, with the results indicating that age, gender, and education were not significantly different between those in and out of the final sample.

Measures

All questions were administered in Chinese, having been translated and back translated into English (Brislin, 1980). All items were assessed on a five-point Likert scale ranging from “strongly disagree” (1) to “strongly agree” (5).

Personality

Personality was measured using the Big Five Inventory, versions 4a and 54 (John, Donahue, & Kentle, 1991). Like Costa and McCrae (1992), this measure also contains six facets for conscientiousness, with fewer items for each facet. The alpha coefficients for conscientiousness (.82), extraversion (.67), agreeableness (.70), neuroticism (.75), and openness to experience (.83) showed reliability. Extraversion was slightly lower than the threshold of .70, but because it was not our primary target and did not show any significant effect on knowledge sharing in analyses (Table 2), we concluded its reliability as acceptable. We further tested the polynomial regressions with and without extraversion; the overall results did not change. Hence, for analytical consistency between our two studies, we included extraversion in the model. Conscientiousness was the independent variable and the other four were controls.

Team average conscientiousness

Team average conscientiousness was calculated by aggregating all people’s conscientiousness on a team (Jansen & Kristof-Brown, 2005). The intraclass correlation coefficients (ICC(1) = .07, F(26, 170) = 1.56, p < .05; ICC(2) = .36) and the mean r_wg (.79) indicated it was reasonable for aggregation. Although ICC(2) was lower than .70, the conventional threshold, Schneider, Smith, Taylor, and Fleenor (1998) proposed that a moderate ICC(2) with an acceptable r_wg score is sufficient for aggregation. For example, Hofmann and Jones (2005) reported ICC(2) for personality traits from .38 (openness) to .52 (conscientiousness). Therefore, given that we had a statistically significant ICC(1) (Klein & Kozlowski, 2000) and the mean r_wg was high, the aggregation was determined to be reasonable (Bliese, 2000).

Other controls

Team conscientiousness variation (standard deviation), team size, gender, age, education, and team tenure were controlled in the regressions. Independent variables and controls were collected at Time 1.

Knowledge sharing

Knowledge sharing was measured at Time 2 by four items from Lin (2007a). One example item was “I share my expertise at the request of my coworkers.” The coefficient alpha was .87. This measure examines participants’ behavior of sharing job experience, expertise, ideas, and tips. We made sure that the participants rated their within-team knowledge sharing as they worked full time with their teammates.

Analyses

We used polynomial regression and response surface methodology to test our Hypotheses 1 and 2 (Edwards, 1994; Edwards & Parry, 1993). Based on the procedures recommended for multilevel polynomial regression, we regressed knowledge sharing on control variables and the five polynomial terms: member conscientiousness (M), team average conscientiousness (T) (Kristof-Brown et al., 2005), member conscientiousness squared (M²), member conscientiousness times team conscientiousness (M × T), and team conscientiousness squared (T²) in mixed-effect models. The overall combined model was as follows

Y = b_{0} + b_{1} M + b_{2} T + b_{3} M^{2} + b_{4} M × T + b_{5} T^{2} + e

(1)

where Y is knowledge sharing and e is the combination of team-level and individual-level error terms. To reduce multicollinearity, M and T were centered on the pooled grand mean in the polynomial regressions and in the response surface plots (Hofmann & Gavin, 1998). Control variables were omitted from equation (1) for simplicity.

To test Hypotheses 1 and 2, we examined two key features of the three-dimensional response surfaces as specified by Edwards and Cable (2009). For Hypothesis 1, the first feature involves the curvature along the incongruence line (M = –T) on which member conscientiousness score is the opposite of the team score. This curvature characterizes the “congruence effect” for knowledge sharing. To show this effect, the curvature should be negative (i.e., an inverted U-shape) and significant such that knowledge sharing increases when member conscientiousness and team conscientiousness move from either end point of the incongruence line toward the middle, approaching the congruence line (M = T) on which member conscientiousness score equals the team score, that is, a member and team fit on conscientiousness. This curvature is calculated by the coefficient combination of (b₃ – b₄ + b₅) in polynomial regressions. For Hypothesis 2, the second feature involves the slope of the congruence line, calculated as (b₁ + b₂), and the curvature of the congruence line, calculated as (b₃ + b₄ + b₅). A significantly positive slope and a nonsignificant curvature on the congruence line indicate that person-team fit at high conscientiousness is associated with more knowledge sharing than fit at low conscientiousness.

Results

Table 1 reports the descriptive statistics and the correlations for Study 1. Given that all independent variables and the dependent variable were collected from participants’ self-reports, we conducted two tests to identify possible common source bias. First, Harman’s single-factor test (Harman, 1976) disclosed a single factor accounting for 18% of the variance among all variables, which is far below the 50% threshold. Second, the common latent factor test (Podsakoff, MacKenzie, Lee, & Podsakoff, 2003) demonstrated that the common latent factor model, including a common latent factor, independent variables, and dependent variable, was not significantly better than the traits model, including independent variables and dependent variables (Δtli = .00, Δχ²(1) = .18, n.s.). Therefore, common source bias should not be a concern.

Table 1.

Means, Standard Deviations, Correlations, and Reliabilities—Study 1.

	M	SD	1	2	3	4	5	6	7	8	9	10	11	12	13
1. Team size	9.16	3.68	—
2. Gender	1.18	.39	−.18*	—
3. Age	32.01	8.45	−.10	.25**	—
4. Education	2.69	.72	−.11	.14^†	.12^†	—
5. Team tenure	2.63	1.08	−.05	−.07	−.23**	−.08	—
6. Individual extraversion	3.08	.55	−.04	.01	.01	.01	−.02	(.67)
7. Individual agreeableness	3.56	.54	−.01	.18**	.10	.09	−.07	.37***	(.70)
8. Individual neuroticism	2.92	.65	.15*	−.16*	−.22**	−.10	.06	−.25**	−.43***	(.75)
9. Individual openness to experience	3.34	.63	−.17*	.21**	.08	.14^†	−.01	.51***	.26***	−.09	(.83)
10. Team conscientiousness variation	.63	.15	−.05	.12^†	.04	.02	.00	.01	.03	−.05	.11	—
11. Individual conscientiousness	3.47	.64	−.08	.11	.21**	.17*	−.09	.11	.22**	−.34***	.18*	.05	(.82)
12. Team average conscientiousness	3.47	.22	−.23**	.18**	.08	.10	.04	.05	.14^†	−.07	.10	.14^†	.34***	—
13. Knowledge sharing	4.31	.57	−.03	−.02	.12^†	.07	−.04	.10	.26***	−.08	.19*	.06	.11	.01	(.87)

obs = 200. Reliabilities are reported along the diagonal in parentheses. Team conscientiousness variation is operationalized as standard deviation of conscientiousness on each team (team leaders and members were both included). ^†p < .10; *p < .05; **p < .01; ***p < .001.

Table 2 shows the polynomial regression results for Study 1.¹ We drew response surface plots for knowledge sharing in Figure 2. For Hypothesis 1, Model 1 in Table 2 shows the results of all control variables, disclosing a significant positive effect of agreeableness on knowledge sharing (b = .28, SE = .08, p < .01). Model 2 shows the results of all control variables and the two independent variables, that is, member conscientiousness (M) and team conscientiousness (T). Model 3 shows the results of the full polynomial regression, including the three quadratic terms (M², M × T, and T²); the three quadratic terms were jointly significant in predicting knowledge sharing (likelihood ratio = 8.80, p < .05) and explained 2% more of its variation. The curvature along the incongruence line was significantly negative (b₃–b₄ + b₅ = −1.77, SE = .84, p < .05). Panel 2-1, Figure 2, shows the response surface, which appears as an inverted U-shape along the incongruence line. Thus, Hypothesis 1 was supported. However, Hypothesis 2 was not supported; the slope along the congruence line was insignificant and appeared to be negative (b₁ + b₂ = −.21, SE = .22, n.s.). We drew the response surface shape on the congruence line in Panel 2-2, Figure 2, to facilitate visualization and interpretation.

Table 2.

Polynomial Regression Results of Knowledge Sharing—Study 1.

Variable	Knowledge sharing
Variable	Model 1	Model 2	Model 3
Constant	2.65*** (.54)	2.61*** (.55)	2.55*** (.55)
Controls
Team size	−.00 (.01)	−.00 (.01)	−.00 (.01)
Gender	−.19^† (.12)	−.18 (.12)	−.16 (.11)
Age	.06^† (.03)	.06^† (.03)	.06^† (.03)
Education	.01 (.07)	.01 (07)	−.01 (.07)
Team tenure	.00 (.00)	.00 (.00)	.00 (.00)
Individual extraversion	−.05 (.09)	−.05 (.09)	−.07 (.08)
Individual agreeableness	.28** (.08)	.29** (.08)	.34*** (.08)
Individual neuroticism	.04 (.07)	.05 (.07)	.02 (.07)
Individual openness to experience	.14^† (.07)	−.13^† (.08)	.15^† (.08)
Team conscientiousness variation	.11 (.32)	.14 (.32)	.31 (.32)
Polynomial terms
b1 individual conscientiousness (M)		.04 (.06)	−.00 (.06)
b2 team average conscientiousness (T)		−.18 (.23)	−.21 (.23)
b3 M²			−.18** (.07)
b4 M × T			.57^† (.32)
b5 T²			−1.02 (.66)
R ²	.09	.10	.12
Congruence line (M = T)
Slope (b1 + b2)			−.21 (.22)
Curvature (b3 + b4 + b5)			−.63 (.63)
Incongruence line (M = −T)
Slope (b1−b2)			.21 (.24)
Curvature (b3−b4 + b5)			−1.77* (.84)
Likelihood ratio for the 3 quadratic terms			8.80
ΔR² compared with previous model	—	.01	.02*

obs = 200. Unstandardized regression coefficients (standard errors in the parentheses) are reported. ^†p < .10; *p < .05; **p < .01; ***p < .001.

Figure 2.

Response surface for knowledge sharing—Study 1. (a) Panel 2-1: Response surface. (b) Panel 2-2: Response surface shape along the congruence line.

Limitations of Study 1

There are several limitations of Study 1. First, Hypotheses 1 and 2 assumed knowledge sharing as a valued and desired phenomenon in organizations. However, the knowledge people share could be very specific, and its measure differs based on the goals, tasks, or values of teams (Wang & Noe, 2010). As knowledge sharing is generally defined as providing know-how or task information to help others (Pulakos et al., 2003), its measure could focus on sharing behavior or shared contents (Cummings, 2004; Srivastava, Bartol & Locke, 2006). In Study 1, our measure (Lin, 2007a) mainly reflects sharing behavior, which may lower the generalizability of Hypotheses 1 and 2. Second, although we argued that person-team fit is embedded in team environments, we did not have an opportunity to collect team environment data. The average team size was relatively large and may have diverse implications for internal team environment. Third, Study 1 was carried out in Asia and we did not know whether the results could hold elsewhere. To address these issues, we conducted Study 2 in another region, taking internal team environment into account and using a content measure of knowledge sharing.

Internal Team Environment—The Moderating Effect

Carson et al. (2007) argued that an internal team environment that enhances shared purpose, provides social support, and encourages members to raise voice can decrease cost of social exchange and strengthen sense of sharedness. We posit that internal team environment is a particularly important team-level context for the relationship between person-team conscientiousness fit and knowledge sharing. Shared purpose, social support, and voice characterize the quality of exchange in a team (Banks et al., 2013), with high quality making it easy to initiate and reciprocate information but low quality making it difficult (Seers et al., 1995). As such, internal team environment may affect the degree that a member still wants to share knowledge without person-team fit. In this study, we posit that a positive internal team environment would make person-team fit less crucial for a member to share knowledge; but lack of positive environment makes person-team fit more pivotal.

In positive internal team environment, team-member exchange should be mutually supportive and benevolent; and the member’s dispositional differences with the team may not be salient as his/her attention focuses on their shared purpose and mutual support. Person-team fit would become less a necessity for determining the member’s intention or behavior. On the one hand, when person-team conscientiousness fits, it seems less necessary for the member to rely on similarity to have shared goals or mutual trust with team; and he/she can share knowledge simply because the positive team environment encourages doing so. On the other hand, when person-team conscientiousness misfits, this dissimilarity seems less noticeable in a positive environment; the member may still share knowledge as positive environment should largely counterbalance the possible negative effects of dissimilarity. Hence, the positive environment could provide an overarching context that facilitates knowledge sharing without person-team fit; thus, the effect of person-team conscientiousness fit on knowledge sharing should be weaker.

On the contrary, if a team lacks positive environment, raising voice is costly and a member may not perceive shared purpose or social support; his/her concern for being similar or not with team becomes salient. Resorting to person-team fit as a prerequisite condition for sharing knowledge looks reasonable. When person-team conscientiousness fits, the member is motivated to share knowledge as fit provides a reason that he/she would be reciprocated. The positive effect of fit on knowledge sharing should be stronger. However, when person-team conscientiousness does not fit, the member tends to set mentality at self-protection mode and minimizing loss becomes a priority. He/she may significantly reduce knowledge sharing, leading to a stronger negative effect of misfit on knowledge sharing. Putting together, we expect the effect of person-team fit on knowledge sharing to be stronger when a team lacks positive internal environment.

Combining arguments above, we propose that internal team environment moderates the effect of person-team conscientiousness fit on knowledge sharing. We hypothesize:

Hypothesis 3: Internal team environment moderates the relationship between person-team conscientiousness fit and a member’s knowledge sharing such that the relationship will be weaker when internal team environment is more positive (i.e., higher rated by members).

Study 2: Method

Participants and Procedure

Participants included 336 undergraduate students enrolled in management courses in two public universities in the United States. University 1 locates in the Northeast region and University 2 locates in the south. All students were asked to participate in the study voluntarily. Those who agreed to participate completed a personality survey at the beginning of the semester. The instructor randomly assigned members to teams, and membership remained unchanged throughout the semester. Participants evaluated their own knowledge sharing within their teams at the end of the semester. The course assignments were designed to require students to work interdependently to complete business plans and team projects throughout the semester.

At University 1, 354 students from 64 teams were invited; 238 in 63 teams agreed to participate in the study and completed the surveys at the beginning and end of the semester (67.23% response rate). At University 2, 108 students from 28 teams were invited; 98 in these 28 teams agreed to participate and completed the surveys (90.74% response rate). In all, we collected data from 336 students in 91 teams, with an average of 3.69 members per team (from 2 to 7). Participants’ ages ranged from 18 to 42 years (mean = 24.90); 186 were women (55%).

Measures

All items were assessed on a six-point Likert scale ranging from “strongly disagree” (1) to “strongly agree” (6) for personality traits and internal team environment, and from “never” (1) to “a lot” (6) for knowledge sharing.

Personality

Personality measures were the same as in Study 1. The alpha coefficients for conscientiousness (.83), extraversion (.85), agreeableness (.71), neuroticism (.78), and openness to experience (.75) demonstrated reliability.

Team average conscientiousness

Team average conscientiousness was calculated by aggregating all members’ conscientiousness in a team. The intraclass correlation coefficients (ICC(1) = .27, F(90, 245) = 2.36, p < .001; ICC(2) = .58) and the mean r_wg (.86) indicated that conscientiousness can be aggregated to team level.

Control variables

Participants’ team conscientiousness variation (standard deviation), university, team size, gender, and age were controlled for in the regressions. Independent variables and controls were collected at the beginning of the semester.

Internal team environment

Internal team environment was collected at the end of the semester and measured by Carson et al.’s (2007) 10 questions. The coefficient alpha was .90. Carson et al’s. measure includes three sub-constructs: (1) shared purpose (one example item was, “The members of my team devise action plans and time schedules that allow for meeting our team’s goals”), (2) social support (one example item was, “The members of my team recognize each other’s accomplishments and hard work”), and (3) voice (one example item was, “Everyone on this team has a chance to participate and provide input”). We computed its convergent validity to assure that the three sub-constructs converged to a higher-order construct of internal team environment. The composite reliability (.93) and average variance extracted (.65) were both high, indicating high convergent validity. The intraclass correlation coefficients (ICC(1) = .41, F(90, 245) = 3.41, p < .001; ICC(2) = .71) and the mean r_wg (.83) indicated that this variable can be aggregated to team level. We aggregated it to team level in the analyses.

Knowledge sharing

Knowledge sharing was collected at the end of the semester and measured by five items from Cummings (2004); the coefficient alpha was .91. This measure focuses more on the frequency that a specific content of knowledge was shared than the sharing behavior rated in Study 1. One example item was, “On average, how often did you share this type of knowledge during the semester in team projects with your team members? Project results (e.g., preliminary findings, unexpected outcomes, or clear recommendations).” We used this measure in the hope of increasing our confidence that the theoretical approach of this article has more general implications across different knowledge sharing measures.

Analysis

The test for Hypothesis 1 and 2 was the same as that in Study 1. To test the moderating effect in Hypothesis 3, we adopted the approach of Edwards (1996). The first step was to create product terms by multiplying polynomial terms with the moderator (internal team environment [at team level], labeled V). These product terms are V × M, V × T, V × M², V × M × T, and V × T². Step two was to test whether the increment in pseudo R-squared (i.e., ΔR²) of the polynomial regression yielded by these product terms significantly improves the fit of the model. If the increment is statistically significant, then the third step was to determine whether higher rating of internal team environment weakened the relationship between person-team conscientiousness fit and knowledge sharing. Specifically, when the moderator is low, the curvature of response surface along incongruence line should be more negatively curved; but when the moderator is high, the curvature should be less negatively curved. The third step was realized by rerunning the polynomial regression at three levels of internal team environment: one standard deviation below its mean, at its mean, and one standard deviation above its mean. We drew response surface plots for these three levels and computed the curvatures along the incongruence line for each plot (Figure 4) to interpret the moderation effect (Edwards, 1996).

Results

Table 3 reports the descriptive statistics. For the common method bias tests, Harman’s single-factor test disclosed a single factor accounting for 17% of the variance among all variables. The common latent factor test showed that the common latent factor model was not significantly better than the traits model (Δtli = .01, Δχ²(1) = 1.34, n.s.). Thus, common source bias seems not a concern. Table 4 shows the polynomial regression results for Study 2. We drew response surface for knowledge sharing (Figure 3) and the moderation effect of internal team environment (Figure 4). Model 1 in Table 4 showed that the curvature along the incongruence line was significantly negative (b₃–b₄ + b₅ = −1.62, SE = .68, p < .05). Figure 3 depicts the response surface, showing an inverted U-shape along the incongruence line. Thus, Hypothesis 1 was supported. However, the slope along the congruence line was not significant and appeared to be negative (b₁ + b₂ = −.07, SE = .22, n.s.). Hence again, Hypothesis 2 was not supported.

Table 3.

Means, Standard Deviations, Correlations, and Reliabilities—Study 2.

	M	SD	1	2	3	4	5	6	7	8	9	10	11	12
1. Team size	3.69	1.33	—
2. Gender	1.55	.05	.08	—
3. Age	24.90	6.30	−.24***	−.03	—
4. Internal team environment	4.91	.77	−.01	−.02	.00	(.90)
5. Individual extraversion	4.36	.93	−.07	−.08	.04	.13*	(.85)
6. Individual agreeableness	4.31	.63	−.07	.23***	.02	.17**	.19***	(.71)
7. Individual neuroticism	2.97	.79	−.02	.07	−.01	−.11^†	−.40***	−.44***	(.78)
8. Individual openness to experience	4.08	.62	−.06	.00	.10^†	.12*	.45***	.26***	−.26***	(.75)
9. Team conscientiousness variation	.64	.26	.31***	.05	−.05	−.03	.08	.00	.02	−.06	—
10. Individual conscientiousness	4.65	.71	−.00	.20**	.05	.08	.33***	.56***	−.50***	.28***	−.12*	(.83)
11. Team average conscientiousness	4.65	.38	−.01	.16**	.11^†	−.02	.19**	.34***	−.32***	.18**	−.22***	.54***	—
12. Knowledge sharing	4.61	.97	−.08	.06	−.01	.59***	.09	.14*	−.13*	.04	−.03	.12*	.01	(.91)

obs = 336. Reliabilities are reported along the diagonal in parentheses. Team conscientiousness variation operationalized the standard deviation. ^†p < .10; *p < .05; **p < .01; ***p < .001.

Table 4.

Polynomial Regression Results of Knowledge Sharing—Study 2.

Variable	Knowledge sharing
Variable	Model 1	Model 2
Constant	5.24*** (.57)	5.20*** (.58)
Controls
University	−.26^† (.14)	−.23 (.14)
Team size	−.16* (.07)	−.17* (.07)
Gender	.16 (.10)	.16 (.10)
Age	.00 (.01)	.00 (.01)
Individual extraversion	.06 (.06)	.05 (.06)
Individual agreeableness	.08 (.10)	.08 (.09)
Individual neuroticism	−.04 (.07)	−.04 (.08)
Individual openness to experience	−.03 (.09)	−.03 (.09)
Team conscientiousness variation	.02 (.24)	.07 (.24)
Moderator
Internal team environment (V)	.85*** (.10)	.56*** (.16)
Polynomial terms
b1 individual conscientiousness (M)	−.02 (.12)	.02 (.12)
b2 team average conscientiousness (T)	−.05 (.21)	−.15 (.23)
b3 M²	−.12 (.12)	−.07 (.12)
b4 M × T	.77* (.33)	.64^† (.33)
b5 T²	−.73* (.35)	−.56 (.37)
Congruence line (M = T)
Slope (b1 + b2)	−.07 (.22)	—
Curvature (b3 + b4 + b5)	−.08 (.26)	—
Incongruence line (M = −T)
Slope (b1−b2)	.03 (.28)	—
Curvature (b3−b4 + b5)	−1.62* (.68)	—
Polynomial terms for moderation
V × M	—	.03 (.218)
V × T	—	.26 (.48)
V × M²	—	.47* (.20)
V × M × T	—	−1.80*** (.53)
V × T²	—	1.27^† (.70)
Models fit
R²	.18	.22
ΔR² (likelihood ratio comparison against previous model)	—	.04* (12.75)

obs = 336. Unstandardized regression coefficients (standard errors in the parentheses) are reported. ^†p < .10; *p < .05; **p < .01; ***p < .001.

Figure 3.

Response surface of knowledge sharing—Study 2.

Figure 4.

Response surfaces with moderation effect of internal team environment—Study 2. (a) Panel 4-1: 1-sd below the mean of internal team environment. (b) Panel 4-2: At the mean of internal team environment. (c) Panel 4-3: 1-sd above the mean of internal team environment.

Hypothesis 3 predicted that internal team environment would moderate the relationship between person-team conscientiousness fit and knowledge sharing, rendering the relationship weaker when internal team environment scores were high. We ran the regression with product terms between the moderator and the five polynomial terms. Model 2, Table 4, shows that the coefficients for two of five product terms were significant (V × M² = .47, SE = .20, p < .05; V × M × T = −1.80, SE = .52, p < .001). The increase in pseudo R-squared from Model 1 to Model 2 was 4% and significant (likelihood ratio = 12.75, p < .05), indicating that Model 2 was significantly better than Model 1. In Figure 4, we drew comparative response surface plots corresponding to one standard deviation below the mean of internal team environment (Panel 4-1), at the mean (Panel 4-2), and one standard deviation above the mean (Panel 4-3). As expected, Panel 4-1 shows a much stronger congruence effect, rendering the curvature along the incongruence line strongly negative and significant ([b₃–b₄ + b₅] = −2.98, SE = .73, p < .001). Panel 4-2 demonstrates that the curvature along the incongruence line was negative and significant ([b₃–b₄ + b₅] = −1.62, SE = .68, p < .05); but the degree of significance was lower than Panel 4-1, indicating that the congruence effect became weaker. Panel 4-3 shows that the curvature became slightly positive and insignificant ([b₃–b₄ + b₅] = .43, SE = .72, n.s.), which indicates that the congruence effect disappeared. The three panels in Figure 4 demonstrate that as internal team environment becomes more positive (i.e., its score increases), the congruence effect weakens, which provides evidence for the moderation effect. Hence, Hypothesis 3 was supported. In addition to the moderation effect, internal team environment was also positively associated with knowledge sharing (Model 1, Table 4, b = .85, SE = .10, p < .000).

Discussion

Theoretical Implications

This study tested the effect of person-team conscientiousness fit on members’ knowledge sharing and the moderation effect of internal team environment. Knowledge sharing is a social exchange behavior; an investigation of how conscientiousness affects knowledge sharing needs to bring the social aspect into picture. Chae et al. (2019) regarded the dependability facets of conscientiousness as other-centered and found a positive effect on knowledge sharing. In this study, we took a step further by examining team conscientiousness as a “social reality” (Berge & Luckmann, 1967) that shapes the relation between individual conscientiousness and knowledge sharing. In work teams, this social reality provides a cue for a member’s individual conscientiousness (Tett & Burnett, 2003) and a frame of reference against which the member tells where he/she stands in terms of conscientiousness. Therefore, person-team fit in conscientiousness plays a crucial role in enhancing a member’s knowledge sharing. This finding extends our understanding on personality by showing that individual conscientiousness and team conscientiousness interplay with one another in affecting a member’s outcomes in team.

Knowledge sharing largely represents the quality of person-team interdependence due to its simultaneous presence of benefits versus costs and the degree of trust invested (Wang & Noe, 2010). Team-member exchange thus provides us with a theoretical explanation that goes beyond the traditional reasoning for person-team fit in which a member’s positive attitudes or behaviors come from the attractiveness resulted from dispositional similarity between him/her and the team (Edwards, 1994). As knowledge sharing is a complicated phenomenon with wide scope including sharing behavior and shared contents, team-member exchange approach gives us the explanatory power and theoretical flexibility to understand this wide scope as it focuses on the reciprocal exchange of ideas, information, feedbacks and help between a member and his/her team (Seers, 1989; Seers, et al., 1995).

We further argued that the degree to which an individual considers person-team fit as necessary for sharing knowledge should not be the same among all teams; that is, person-team fit is not without its context. We provided initial evidence that internal team environment moderates the effect of person-team conscientiousness fit on knowledge sharing. This finding is consistent with the argument that strong team support neutralizes the effect of personal disposition on knowledge sharing (Chae et al., 2019). But more importantly, it extends the current person-team personality fit literature by showing that person-team fit does not act alone in influencing an individual’s behavior; rather, its strength depends on other team contexts (Edwards, 1996). Positive internal environment tends to form a “strong culture” in team which guides members’ attitudes and behaviors toward team norms and shared goals (O’Reilly & Chatman, 1996); thus, whether their dispositional characteristics fit one another may be less a concern.

Managerial Implications

This study also has managerial implications. Previous research emphasized selecting the right members to enhance knowledge sharing (Cabrera, et al., 2006). Our study showed that the right fit also matters; specifically, for conscientiousness, a member who possesses similar level of achievement striving and dependability with a team is more likely to fit into the team and feel motivated to share knowledge. An individual’s achievement striving was found to have negative effect on knowledge sharing because of its self-centeredness (Chae et al., 2019); but practically, member-team fit on achievement striving might overcome this negativity as this fit could allow both parties to pursue the same goals. Hence, managers could take a more holistic view when selecting members for a team by choosing candidates whose conscientiousness fits that of the team. Moreover, as workforce is highly diversified in today’s organizations, selecting team members who have similar conscientiousness may be rather difficult; in this case, managers could devote efforts to promoting a positive internal team environment, which allows prosocial mentality among members and thus makes conscientiousness fit less a concern. In this sense, managers could engage in practices like procedural fairness, coworker support, and transformational leadership to enhance a positive team environment (Ng & Sorensen, 2008).

Limitations and Future Research

This study has limitations and opportunities for future research. First, by investigating person-team fit in conscientiousness, we assume that there exists a composition of team conscientiousness (Barry & Stewart, 1997; Bell, 2007). Although this assumption is meaningful theoretically and empirically and widely used in team personality research, a member’s conscientiousness fit with each teammate, respectively (i.e., a dyadic person-coworker fit) may also play important roles in the member’s knowledge sharing; specifically, this member may share knowledge with some coworkers whose conscientiousness fits his/her own and withhold knowledge from other coworkers whose conscientiousness does not fit his/hers. Moreover, past relationships between team members may result in certain similarity in experience or expertise such that these similarities make knowledge sharing easier with some teammates but not others. Future research could probe this possibility and extend our knowledge about the relationship between person-coworker fit and knowledge sharing.

Surprisingly, this study did not find that person-team fit on high conscientiousness leads to more knowledge sharing than fit on low conscientiousness (Hypothesis 2). There may be several reasons for this result. For example, in a high–high fit team, a member may pause before sharing until he/she is absolutely sure that doing so will be helpful, and he/she may spend much more efforts in making sure his/her knowledge is really delivered and absorbed by others. But in a low–low fit team, a member may simply initiate knowledge sharing but does not guarantee actual delivery or absorption. This reasoning highlights the limitation of our study that we did not investigate the quality versus quantity of knowledge sharing. It is possible that a member in the high–high fit scenario shares high-quality knowledge but not high quantity. Whereas a member in the low–low fit scenario shares high quantity of knowledge, but the quality is low. We suspect that in today’s work teams, the quality of knowledge is more desirable than the quantity; and more sharing may not be welcome if the quality of knowledge shared is low. Future research should distinguish quality from quantity and investigate how personality fit affects them respectively.

There is another possible reason for Hypothesis 2 being rejected. Knowledge sharing may highly depend on the tasks in which a team engages. Colloquially, a high conscientious member working on a high conscientious team may strictly follow task requirements, which could lead to rule-following or box-checking behaviors. For example, in Study 1, the tasks of medical research determined that the QCC teams’ priority was to carefully follow hospital protocols and make no mistakes. This was also true for our student participants in Study 2 who needed to abide by the course instructions. As such, tasks may determine whether sharing more knowledge is always preferred. For a high–high fit team, a member may restrain from proactively sharing certain knowledge that looks going off schedule for team tasks, leading to less knowledge sharing. Future research could investigate the relationship among types of team tasks, member conscientiousness, and knowledge sharing. It is possible that there are moderation effects between types of team tasks and types of team-level conscientiousness such as prominent member’s conscientiousness, dispersion of members’ conscientiousness, or a threshold of team conscientiousness.

Third, in Study 2, we only examined internal team environment as the moderator. Team cohesion, leadership, and many other team-level variables were also proposed to be important for shaping relationships between personality traits and knowledge sharing (Wang & Noe, 2010). For example, Chae et al. (2019) found that supervisor and coworker support moderate the effects of achievement striving and dependability on a member’s knowledge sharing. We believe our reasoning that a positive environment makes person-team fit less crucial could extend to other team-level variables. Future research can investigate the role of other team-level moderators in the relations between person-team personality fit and knowledge sharing.

In conclusion, in this study, we obtained convergent findings in two studies about the effects of person-team conscientiousness fit on knowledge sharing. Given the importance of knowledge sharing and personality traits in teams, we hope our research encourages others to further investigate the intriguing phenomena related to the effects of person-team personality fit on individuals’ attitudes and behaviors.

Footnotes

Acknowledgments

The authors are indebted to Dr. Meir Shemla and the three anonymous reviewers for their insights and suggestions in improving this manuscript.

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: The Ministry of Science and Technology (grant # MOST 104-2410-H-035-038), the National Natural Science Foundation of China (72022005; 71572017), and Beijing Social Science Research Foundation of China (20GLA073).

ORCID iDs

Guozhen Zhao

Meng Yu Cheng

Note

Associate Editor: Meir Shemla

Author Biographies

Guozhen Zhao is an associate professor at the College of Business, Delta State University, Mississippi, U.S. He received his PhD in Organization Management at Rutgers, the State University of New Jersey. His research interests include person-environment fit, social network and knowledge management. His work has been published in Journal of Experimental Social Psychology, Family Business Review, IEEE Transactions on Engineering Management, among others.

Holly H. Chiu is an Associate Professor in the Department of Business Management at Brooklyn College of the City University of New York. Her research interests include influence tactics, innovation implementation, and knowledge sharing. Her works can be found in journals such as British Journal of Management, and Journal of Knowledge Management.

Hao Jiao is a professor of management at Business School, Beijing Normal University, Beijing, China. His research interests include strategy, entrepreneurship management, innovation management, and dynamic capabilities view within the context of emerging markets, among others. He has published over fifty articles in major refereed journals in entrepreneurship and innovation management such as the Academy of Management Perspectives, Technovation, Technological Forecasting & Social Change, Journal of Product Innovation Management, Asia Pacific Journal of Management and Journal of Engineering and Technology Management, among others.

Meng-Yu Cheng is an associate professor at the Department of Business Administration, Feng Chia University, Taiwan. He received his PhD at Yuan Ze University. His research interests include social network, leadership, team management, and Chinese organizational behavior. His work has been published in Journals of Business Ethics, Asia Pacific Journal of Management and American Behavioral Scientist.

Ying Chen is an assistant professor at the College of Business, University of Rhode Island. She received her PhD in organization studies at Vanderbilt University. Her research centers on leader-member exchange, Chinese guanxi, and labor relations. Her work has been published in the Journal of Organizational Behavior, Leadership Quarterly, and Advances in Industrial and Labor Relations, among other.

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