Discussion : Team Performance, Productivity And Rewording Teamwork

Discussion : Team Performance, Productivity And Rewording Teamwork

Primary Post Assignment: Team Performance, Productivity and Rewording Teamwork :(400+ words)

This week module focuses on performance, productivity, and rewarding teamwork. Based on your understanding, discuss the following.

>How to achieve team productivity:

>What conditions need to be in place for teams to excel and why?

>Suggest ways to design teamwork so that threats to performance are minimized.

>As a manager, how would you reward teamwork?

-Support your work with specific citations from this week’s learning resources and other sources.

Respond to post in one of the following ways:(200+ words)

• Share an insight from having read your colleagues’ postings, synthesizing the information to provide new perspectives.

• Make suggestions based on additional evidence drawn from readings or after synthesizing multiple postings.

Team climate, empowering leadership, and knowledge sharing

Yajiong Xue, John Bradley and Huigang Liang


Purpose – The purpose of this research is to investigate the impact of team climate and empowering

leadership on team members’ knowledge-sharing behavior.

Design/methodology/approach – A research model was developed based on prior knowledge

management studies. Survey data were collected from 434 college students at a major US university,

who took courses that required team projects. The partial least squares technique was applied to test

the research model.

Findings – Team climate and empowering leadership significantly influence individuals’

knowledge-sharing behavior by affecting their attitude toward knowledge sharing. These two

constructs also have significant direct effects on the knowledge-sharing behavior.

Research limitations/implications – The student sample and US setting might limit the generalizability

of the findings. Nonetheless, this study is based on and extends prior research, which provides a

deepened understanding of knowledge sharing in the team context.

Practical implications – This research has practical implications for how to design teams to facilitate

knowledge sharing. It suggests that cohesive, innovative teams with members trusting one another and

led by empowering leaders will have a higher level of knowledge sharing.

Originality/value – This research originally examines the effects of both team climate and empowering

leadership on knowledge sharing. Little prior research has carried out such an integrated analysis. This

paper will have significant value for organizations trying to redesign teams to enhance knowledge


Keywords Team working, Empowerment, Leadership, Knowledge management

Paper type Research paper

1. Introduction

As an organizational process, knowledge sharing plays a fundamental role in generating

new ideas and creating business opportunities (Grant, 1996). Effectively communicated

knowledge benefits all of the involved organizational actors by improving their performance

and eventually improving financial, marketing, and general outcomes of the organization

(Alavi and Leidner, 1999). Yet, in practice, inadequate sharing has been found to be a major

impediment to effective knowledge management (Davenport and Prusak, 1998). Therefore,

understanding employees’ knowledge sharing behavior has important implications for


Although empirical evidence has uncovered some of the complex dynamics of knowledge

sharing in general (Ipe, 2003), there is a paucity of research that explains how individuals

share knowledge in organizational settings. In particular, an in-depth understanding of

knowledge sharing within teams is desirable because team-based design is widely adopted

by contemporary organizations. About 82 percent of companies with 100 or more

employees have team-based mechanisms (Gordon, 1992) and new collaborative job

designs and work practices require teamwork (Capelli and Rogovsky, 1994). Therefore, it is

DOI 10.1108/13673271111119709 VOL. 15 NO. 2 2011, pp. 299-312, Q Emerald Group Publishing Limited, ISSN 1367-3270 j JOURNAL OF KNOWLEDGE MANAGEMENT j PAGE 299

Yajiong Xue is an Assistant

Professor, John Bradley is

Professor of Management

Information Systems and

Huigang Liang is an

Assistant Professor, all in

the College of Business,

East Carolina University,

Greenville, North Carolina,


Received: 16 June 2010 Accepted 18 October 2010

imperative to understand how team-related factors influence individuals’ knowledge sharing


Given that it is people who actually create, share, and use knowledge, an organization

cannot effectively exploit knowledge unless its employees are willing and able to share their

own knowledge and assimilate the knowledge of others (Ipe, 2003). Thus, knowledge

sharing within organizations can be seen as a multifaceted, complex process that involves

intricate human behaviors (Hendriks, 1999). It implies a voluntary act by individuals who

participate in the exchange of knowledge even though there are no compulsory pressures

(Davenport, 1997). It often involves the communication of tacit knowledge that cannot be

reported through formal channels and is difficult to be compelled. Hence, the most

appropriate measure to enhance knowledge sharing seems to be ‘‘soft’’ strategies relying on

the climate and leadership role of the specific organizational unit (Hulsheger et al., 2009;

Srivastava and Bartol, 2006).

In this research, the authors investigate knowledge sharing in light of two team-related

factors: team climate and empowering leadership. First, team climate refers to an implicit

frame that shapes individual perceptions, attitudes and behaviors within the group context

(Seibert et al., 2004). It has long been known as one of the most important sources of social

influence that affects individual behavior in the team environment (Hulsheger et al., 2009;

West and Anderson, 1996). Second, prior research has highlighted the importance of the

leader’s role in organizational processes (Liang et al., 2007), particularly in knowledge

management (Crawford, 2005; Singh, 2008; Srivastava and Bartol, 2006). A variety of leader

behaviors have been studied, among which empowering leadership is found to improve

employee’s job autonomy (Bennis and Townsend, 1997). Such autonomy is essential for

employees to undertake conscious, voluntary knowledge sharing.

Specifically, in this paper the authors investigate the impact of both team climate and

empowering leadership on individuals’ knowledge sharing behavior. This will help

researchers understand how knowledge sharing within the team environment is

influenced by team-related factors. It will also help organizations attend to the team

environment and team leaders when trying to enhance knowledge sharing within


This paper proceeds as follows. The next section presents the literature review and research

model development. The construct operationalization, data collection, data analysis, and

model testing results are described in the method section, after which the authors interpret

the findings and discuss their implications for research and practice. Finally, limitations and

directions for future research are discussed.

2. Theoretical development

Based on the extant research on knowledge management, the authors develop a research

model (Figure 1) to explain why teammembers engage in knowledge sharing. It is proposed

that team climate and empowering leadership help to shape individuals’ attitudes, which in

turn lead to the desired knowledge sharing behavior. In addition, team climate and

empowering leadership both have a direct impact on the knowledge sharing behavior. The

major constructs and hypotheses are discussed as follows.

‘‘ As a social behavior, an individual’s knowledge sharing is inevitably susceptible to social influences arising from other people. ’’


2.1 Team climate

As a social behavior, an individual’s knowledge sharing is inevitably susceptible to social

influences arising from other people. Individuals need to be proximal to the referent others to

be exposed to social influences. Salancik and Pfeffer (1978) suggest that the immediate

social environment is an important source of information which individuals use to construct

reality and formulate perceptions, attitudes, and behaviors. While multiple social networks

can exert influences on individual behaviors, prior research in social psychology shows that

stronger social influence takes place in work teams because individuals are likely to identify

most closely with their work team and thus are more willing to comply with team norms (Fulk,

1993). Liang et al. (2010) also find that team climate significantly influences individuals’

perceptions, normative beliefs, and technology usage. In this research, therefore, the

authors contend that a desirable team climate can create an environment in which

knowledge sharing is encouraged.

The extant literature shows that team climate is a composite construct consisting of three

dimensions: affiliation, trust, and innovation (Bock et al., 2005). Affiliation, equivalent to

cohesion in nature, refers to the perception of a sense of togetherness among members.

Cohesion, defined as members’ attraction to the team (Hogg, 1992), can be considered as a

psychological force that binds people together (Keyton and Springston, 1990). The sense of

affiliation or cohesion tends to enhance team members’ willingness to care for or help one

another. As a result, they are more likely to share knowledge with one another.

Trust in the team environment is defined as a member’s willingness to accept vulnerability

based on a confident expectation of teammates’ competence, integrity, and benevolence

(Pavlou et al., 2007). Effective communication occurs in an environment in which trust and

commitment are prevalent (Te’eni, 2001). Huemer et al. (1998) argue that team members

with stronger trust are more likely to work together cooperatively and conscientiously. Zand

(1972) finds that team members share information more freely when they trust one anothers’

capabilities and competencies. Similarly, Weick and Roberts (1993) argue that to coordinate

knowledge among team members, they need to trust one anothers’ capabilities. Hsu et al.

(2007) find that social relationships based on trust have a significant influence on an

individual’s attitude toward sharing knowledge.

Figure 1 Research model

Team Climate

Empowering Leadership

Attitude KS behavior

Control variables

Gender Age

Note: Second-order constructs


H3 H4



Participative Decision Making





Showing Concern

Lead by Example



Innovativeness in a team refers to the degree to which change and creativity are actively

encouraged and rewarded within the team. Innovative teams emphasize learning, open

information flows, and reasonable risk-taking (Bock et al., 2005). Members of such teams

approve innovations and provide practical support to peers’ innovative initiatives.

Consequently, individuals in the innovative team environment are more empowered to

share new and creative ideas with each other than individuals in a non-innovative

environment (Kim and Lee, 1995).

In this study these three constructs – cohesion, trust, and innovativeness – were used as

measures of team climate with the expectation that it not only influences an individual’s

attitude toward knowledge sharing, but also facilitates the actual knowledge sharing

behavior. Therefore, the following hypotheses are derived:

H1. Team climate has a positive influence on knowledge sharing attitude.

H2. Team climate has a positive influence on knowledge sharing behavior.

2.2 Empowering leadership

One of the ways organizations could improve efficiency and performance is to empower

their employees. Knowledge sharing is a critical aspect of empowered teams (Argote,

1999). Prior research has shown that knowledge sharing is a significant determinant of

organizational performance and a team’s leader plays a pivotal role in making knowledge

sharing possible in the team (Srivastava and Bartol, 2006). In an empowering organizational

structure, leaders are capable of increasing team members’ self-efficacy and control over

their work environment. When teammembers are empowered to make job-related decisions

on their own, they need to possess adequate information to ensure that the decisions are

reasonable and justifiable given the decision contexts. As a result, they are more likely to

share knowledge with one another before and during the decision process. Therefore,

empowering leadership is the enzyme that stimulates and nurtures the occurrence of

knowledge sharing.

Arnold et al. (2000) show that empowering leadership has five dimensions:

1. leading by example, referring to a set of behaviors that show the leader’s commitment to

his or her own work as well as the work of his/her team members;

2. coaching, referring to a set of behaviors that educate team members and help them to

become self-reliant;

3. participative decision making, referring to a leader’s use of team members’ information

and input in making decisions;

4. showing concern, referring to a collection of behaviors that demonstrate a general regard

for team members’ well-being; and

5. informing, referring to the leader’s dissemination of company wide information such as

mission and philosophy as well as other importation information.

An empowering leader who possesses these attributes will be seen as a supportive leader

who provides guidance to followers, treats them fairly, and recognizes the value of their

input. Given that team members expect to receive fair recognition by an empowering leader

for their contribution of ideas and information, they are likely to be motivated to share their

unique knowledge with others (Srivastava and Bartol, 2006).

All of the five dimensions of empowering leadership contribute to knowledge sharing. First,

an empowering leader can set an example for subordinates by sharing his or her own

knowledge first, which signifies his or her support for team-wide knowledge sharing.

Second, the coaching behavior of an empowering leader includes teaching team members

how to effectively communicate with one another and encouraging them to collaboratively

solve problems, thereby providing opportunities for them to share their knowledge (Arnold

et al., 2000). Third, when a leader advocates participative decision making, team members

havemore opportunities to voice their opinions and provide suggestions (Locke et al., 1997).


Under such leadership, team members are likely to see themselves as an important part of

the decision process and more motivated to share their knowledge. Fourth, employees

might have concerns when sharing knowledge with peers because their social status in the

organization is often related to their unique knowledge. An empowering leader is able to

identify and alleviate such concerns, thus removing barriers to knowledge sharing. Finally,

Srivastava and Bartol (2006) suggest that informing motivates a search for solutions both

inside and outside a team and a greater collaborative attempt to help one another through

knowledge sharing. Overall, the preceding points suggest that empowering leadership will

strongly influence individuals’ attitudes toward knowledge sharing and increase the extent of

their knowledge sharing behavior:

H3. Empowering leadership has a positive influence on knowledge sharing attitude.

H4. Empowering leadership has a positive influence on knowledge sharing behavior.

2.3 Attitude

Based on theory of reasoned action, attitude is defined as an individual’s positive or negative

feelings about performing knowledge sharing (Fishbein and Ajzen, 1975). The theory of

reasoned action posits that attitude determines behavioral intention, which in turn

determines behavior. Numerous empirical studies have confirmed the significant influence

of attitude on intention (e.g., Bock et al., 2005). In this research, the authors decide to

investigate the direct relationship between attitude and behavior because they are

interested in explaining individuals’ actual knowledge sharing behavior rather than

predicting their future behavior. Behavioral intention, as a predictor of actual behavior, has

limitations (Venkatesh et al., 2008). It has been criticized that there exists an

intention-behavior gap (Sheeran, 2002). Therefore, the authors propose that the more

favorable individuals’ attitude toward knowledge sharing, the more likely they will share

knowledge with others. Hsu et al. (2007) state that the biggest challenge in knowledge

sharing is the willingness (attitude) of the individual. That is, negative attitude tends to

decrease the likelihood of knowledge sharing. Overall, it is suggested that there is a positive

relationship between knowledge sharing attitude and behavior:

H5. Knowledge sharing attitude has a positive influence on behavior.

2.4 Control variables

Team members’ knowledge sharing behavior is likely to be influenced by their demographic

characteristics. Gratton et al. (2007) find that at large companies in Europe and the USA

many failures in collaboration and knowledge sharing result from subgroups that have

emerged within teams based on age and gender. Miller and Karakowsky (2005) show that

team members’ gender has a significant impact on their feedback seeking from others.

Therefore, the authors control for the influence of age and gender on knowledge sharing


3. Method

3.1 Measurement development

Measures for the four constructs were developed based on prior research. Consistent with

Bock et al.’s (2005) study, team climate is modeled as a second order formative construct

consisting of three first order reflective constructs: cohesion, trust, and innovation. Cohesion

was measured using three items adapted from (Xue et al., 2004/2005). Innovativeness was

adapted fromBocketal. (2005),measuredby two items.Trustwasmeasuredusing three items

adapted from Langfred (2004). Following Arnold et al. (2000), empowering leadership is

modeledasasecondorder reflectiveconstructcomprisingfivefirstorder reflectiveconstructs:

lead by example, participative decision making, coaching, informing, and showing concern.

Themeasurement items for theseconstructswereadapted fromArnoldet al. (2000). Thescale

for attitude includes three items adapted from Bock et al. (2005). The scale for knowledge

sharing behavior was adapted fromHsu et al. (2007). Except attitude items that are evaluated

byafive-pointsemanticscale,allof the itemswereevaluatedbyafive-pointLikertscalewhere1


represents ‘‘strongly disagree’’ and 5 represents ‘‘strongly agree.’’ The Appendix, Figure A1

shows themeasurement items. In addition, age wasmeasured as a ratio variable and gender

as a categorical variable with male coded as 1 and female as 2.

3.2 Procedure

Anonline surveywasdeveloped tomeasure the theoretical constructs. A total of 650 students,

undergraduates and graduates, whowere taking business courses at a large university in the

USA were invited to take the survey. These students were recruited from both management

and management information system (MIS) courses where teamwork assignments were

major course requirements. These team assignments range from case studies, requirement

analyses, and essay writing, to project design and development. Students were grouped into

teams to work on several projects. In each team, a team leader was chosen to act as a

coordinator between the instructor and team members. Team leaders were responsible for

reporting their team members’ activities and involvement and workload allocation within

teams.Peerevaluationwasused toassesseachmember’sperformanceon the teamprojects.

To simulate the real work environment, team leaders’ evaluations were given a higher weight

when aggregatingall of thepeer evaluation scores. The surveywas administeredat the endof

the semester. Participation in the survey was completely voluntary and anonymous. Extra

course credits were employed as an incentive for completing the survey. A total of 434

completed surveys were collected resulting in a response rate of 66.8 percent.

Among the 434 respondents, 219 are male (50.5 percent), and 215 are female students

(49.5 percent). Their average age is 25.81, ranging from 18 to 63 (SD ¼ 7:78). Most of them have some work experiences ranging from 0 year to 35 years (mean ¼ 5:54 and SD ¼ 7:33).

3.3 Data analysis

The authors used partial least squares (PLS) to validate the measurements and test the

hypotheses. PLS employs a component-based approach for model estimation and is not

highly demanding on sample size and residual distribution (Chin, 1998). It is best suited for

testing complex structural models as it avoids two problems: inadmissible solutions and

factor indeterminacy (Fornell and Bookstein, 1982). Both reflective and formative constructs

can be estimated by PLS (Chin, 1998). Hence, this method was chosen to accommodate the

formative second-order construct (team climate) since covariance-based SEM techniques

do not allow formative constructs to be estimated easily.

4. Results

4.1 Measurement validation

The reliability of the measurements was evaluated using Cronbach’s alpha and the

composite reliability scores. As Table I shows, the reliability scores of all of the constructs are

considered adequate as they exceed the recommended cutoff of 0.70 (Nunnally, 1978).

The convergent and discriminant validity of the measurements were confirmed by four tests.

First, as Table I shows, the square root of the average variance extracted (AVE) of each

construct is much larger than all cross-correlations between the construct and other

Table I Construct reliability, AVE, and correlations

Construct Cronbach’s alpha Composite reliability AVE 1 2 3 4 5

1. Team climate – – – – 2. Empowering leadership 0.98 0.98 0.71 0.49 0.84 3. Attitude 0.89 0.93 0.82 0.44 0.38 0.91 4. KM behavior 0.83 0.89 0.74 0.36 0.36 0.41 0.86 5. Gender – – – 0.07 0.13 0.10 0.05 – 6. Age – – – 0.10 0.03 0.12 0.10 0.10

Note: The diagonal elements (in italics) are square roots of AVE


constructs (Chin, 1998). Second, all AVEs are well above 0.50, which suggests that the

principal constructs capture much higher construct-related variance than error variance

(Hair et al., 1998). Third, the correlations among all of the constructs are well below the 0.90

threshold, suggesting that the constructs are distinct from each other (Bagozzi et al., 1991).

Fourth, PLS analysis shows that each item’s loading on its underlying construct is above the

recommended 0.70 level (Chin et al., 2003) and significant at the 0.01 level (Table II). Jointly,

these tests suggest adequate convergent and discriminant validity of the measurements.

The authors paid particular attention to the two second-order constructs – team climate and

empowering leadership. Since empowering leadership is a reflective second-order

construct, its validity is indicated by the path weights of its five first-order constructs

(Jarvis et al., 2003). As Figure 2 shows, the path weights of lead by example, participative

decision making, coaching, informing, and showing concern are 0.92, 0.92, 0.94, 0.93, and

0.91, respectively (p , 0:01), suggesting that they are significantly determined by the

underlying higher order construct.

Traditional methods assessing construct validity and reliability are inappropriate for

formative constructs whose causal direction flows from measures to constructs

(Diamantopoulos and Winklhofer, 2001; Jarvis et al., 2003). Following the formative

measures assessment guidelines recommended by Petter et al. (2007), the authors

evaluated team climate’s construct validity and reliability. First, the PLS analysis shows that

all of the three first-order constructs of team climate have significant weights (Figure 2),

providing evidence for construct validity (Diamantopoulos and Winklhofer, 2001).

Specifically, the weights for affiliation, trust, and innovation are 0.41, 0.46, and 0.25,

respectively (p , 0:01). Second, to assess multicollinearity, the authors computed latent

Table II Factor loadings

Construct Item Mean SD Loading

Innovation 1 3.85 0.92 0.89* 2 3.57 0.86 0.87*

Cohesion 1 3.86 0.81 0.85* 2 3.76 0.97 0.88* 3 4.17 0.79 0.84*

Trust 1 3.80 1.01 0.93* 2 3.79 1.11 0.93* 3 3.80 1.04 0.93*

Lead by example 1 3.90 0.96 0.88* 2 4.09 0.91 0.94* 3 4.03 0.96 0.91* 4 4.07 0.91 0.94*

Participative DM 1 4.03 0.89 0.93* 2 4.10 0.87 0.95* 3 4.14 0.83 0.95*

Coaching 1 3.89 0.93 0.92* 2 3.97 0.87 0.93* 3 3.93 0.92 0.92*

Informing 1 3.94 0.92 0.92* 2 3.90 0.93 0.95* 3 3.80 0.95 0.91* 4 3.94 0.90 0.90*

Showing concern 1 3.73 0.95 0.86* 2 3.89 0.88 0.92* 3 4.11 0.86 0.84* 4 3.91 0.88 0.90*

Attitude 1 4.06 0.71 0.90* 2 3.97 0.69 0.93* 3 4.01 0.66 0.89*

KS behavior 1 3.75 0.85 0.88* 2 3.42 0.90 0.82* 3 3.73 0.81 0.87*

Note: *p , 0:01


variable scores for each first-order team climate component and then tested its variance

inflation factor (VIF)[1]. The VIFs for cohesion, trust, and innovation are 1.62, 1.58, and 1.36,

respectively. It is recommended that the VIF statistic for formative measures should not

exceed 3.3 (Diamantopoulos and Siguaw, 2006). All of the VIFs are under 3.3, which suggest

that the formative measure is reliable.

Since all of the constructs are measured by single-source self-report data, common method

variance (CMV) may bias the construct relationships (Podsakoff et al., 2003). The authors

conducted the Harmon’s one factor test (Podsakoff and Organ, 1986) to evaluate whether

CMV is a serious concern. All of the measurement items were entered into a factor analysis

using the Varimax rotation. No single dominant factor emerged from the analysis. Ten

components were extracted and their explained variance ranged from 2.4 percent to 36.4

percent, indicating that common method variance is unlikely to be serious.

4.2 Model testing

The structural model testing results are shown in Figure 2. Team climate is found to

significantly affect knowledge sharing attitude (b ¼ :34, p , 0:01), as is empowering leadership (b ¼ 0:21, p , 0:01). These two factors account for 23 percent of variance in knowledge sharing attitude, thus supporting H1 and H3. Team climate is found to

significantly affect knowledge sharing behavior (b ¼ 0:14;p , 0:05), thus supporting H2. The link between empowering leadership and knowledge sharing behavior is significant

(b ¼ 0:18, p , 0:01), providing support to H4. Knowledge sharing attitude is also found to have a significant positive influence on behavior (b ¼ 0:28, p , 0:01), thus supporting H5. About 24 percent of variance in knowledge sharing behavior can be explained by the three

determinants. The two control variables, age and gender, do not have a significant effect on

knowledge sharing behavior.

5. Discussion

This study examines the impact of team related factors on individuals’ attitude and

knowledge sharing behavior, which makes important theoretical and practical contributions

to team based research. Our results highlight the importance of both team climate and

empowering leadership on individuals’ knowledge sharing attitude and behavior. Previous

Figure 2 Model testing results

Team Climate

Empowering Leadership

Attitude KS behavior

Control variables Gender Age

* p < 0.05; ** p < 0.01; ns = non-significant


0.21** 0.18**



0.23 0.24 Participative Decision Making





Showing Concern

Lead by Example







0.94** 0.93**


ns ns

Notes: Second-order constructs


research only studied the impact of one of these two important team factors independent of

the other. By putting them together, this study integrates two important perspectives – the

social environment of the team and the value of the team leader.

In addition, our research shows that the impact of these two factors are complementary –

they can work together to cultivate individuals’ knowledge sharing attitude and lead to more

knowledge sharing behavior. The authors find that both team climate and empowering

leadership have two pathways to influence knowledge sharing – besides the indirect

influence via attitude, they also have a direct impact. This suggests that their effects are both

internal and external. Internally, they sway individuals’ subjective attitude which in turn

increases knowledge sharing. Externally, social pressures from team climate or facilitating

conditions from empowering leadership can be created to directly encourage knowledge


These findings extend the existing literature on knowledge sharing. For example, Bock et al.

(2005) found that team climate affects knowledge sharing by influencing attitude, but they

focused on intention to share knowledge and did not examine knowledge sharing behavior.

Srivastava and Bartol (2006) uncovered the direct relationship between empowering

leadership and knowledge sharing behavior, but they did not examine the mediating role of

attitude. Thus, our research integrates discrete findings of prior research and should deepen

our understanding of the dynamics of knowledge sharing within teams.

Practically, this study draws special attention to team design in organizations. In order to

promote knowledge sharing, besides considering other relevant organizational and

individual factors, managers need to cultivate a nurturing team environment since team is

the most proximal social context for individuals within which they frequently interact with

peers (Fulk, 1993; Liang et al., 2010). They need to create cohesive, innovative teams whose

members trust one another. Team climate can help members develop a favorable attitude

toward knowledge sharing. The members might also feel obliged to sharing knowledge with

others due to normative pressures arising from the strong team cohesion and trust on peers.

In addition, empowering leadership skills should be emphasized when selecting or

evaluating team leaders. The empowering leadership skills of current team leaders can be

strengthened by improving each of the five components identified by Arnold et al. (2000):

lead by example, coaching, participating decision making, informing, and showing concern.

Appropriate training programs can be provided to help team leaders identify their

weaknesses and develop the specific skills that they lack. Such training is likely to transform

the organization’s current managerial practice and difficult to achieve, but it has great

potential to stimulate employees’ knowledge sharing behavior and subsequently

organizational performance.

Although this study has important implications for organizations, some limitations related to

the university setting of this study might limit its extrapolation to a wider business context.

The differences between universities and companies give rise to several concerns. First, this

study is based on data collected from college students in a major American university.

Students and employees tend to have different views over their unique knowledge and their

knowledge sharing behavior might be influenced by different sets of factors. Therefore,

researchers should be cautious when generalizing the findings of this study to real business

settings. Second, the leaders of the student teams the authors studied did not have the real

hierarchical power as in a real business setting. The effect of their empowering leadership

might not be as strong as that of team leaders in real organizations. The findings of this study

need to be validated in real-world organizational settings. Finally, the American cultural

background of the students might play a role in influencing their knowledge sharing attitude

and behavior. Cultural differences should be taken into account when applying our findings

to other countries.

These concerns essentially arise from one basic issue: whether it is appropriate to use

students as surrogates for non-students (e.g., employees). This issue ought to be

addressed to afford credibility to the findings of this study. Using student samples in

academic research has been criticized to have low external validity because the findings


cannot be easily generalized to non-student settings. However, Locke (1986) argues that in

the areas of organizational psychology and organizational behavior using student samples

is not as serious a concern as it seems to be. He states:

[. . .] we must begin to rethink the whole issue of external validity. The evidence indicates that a

detailed, point-by-point similarity with respect to subjects, tasks, settings, and so forth is not

necessarily required in order to achieve generalizability. Both college students and employees

appear to respond similarly to goals, feedback, incentives, participation, and so forth, perhaps

because the similarities among these subjects (such as in values) are more crucial than their

differences. Task differences do not seem overwhelmingly important. Perhaps all that is needed is

that the participants in either setting become involved in what they are doing (Locke, 1986, p. 6).

In this study, the focus is individual perceptions, attitude, and behavior in the team context,

and falls in the domain of organizational behavior research. Based on Locke (1986), student

subjects and employee subjects are likely to have similar responses to team climate and

leadership styles in spite of differences between university and company contexts. There is

also empirical evidence showing that students and managers respond similarly to

leadership questions (Singer, 1990).

Although the university environment and business environment differ in some aspects, they

do share many common characteristics. In particular, it can be argued that the student

teams in this study are relatively similar to project teams in companies. Like a project team in

a company, students teamed up to complete their course project. Each member plays a

specific role in the project. During their collaboration, students, just like employees in a

project team, will develop perceptions of the team climate and leadership style. Although the

strength of relationships between these perceptions and knowledge sharing behavior might

differ between employee and student, the authors contend that the direction of the

relationships will not differ. Therefore, the authors believe that the findings of this study can

be generalized to the project team context with a certain degree of confidence. Regarding

the generalizability to other team settings (e.g., product development team, scientific

research team, topmanagement team, etc.), since the team characteristics vary a lot, further

research is strongly recommended.

In conclusion, this study furthers our understanding of the impact of team climate and

empowering leadership on individuals’ knowledge sharing attitude and behavior. The

findings are helpful to practitioners when they develop strategies to foster knowledge

sharing to achieve better organizational outcomes.


1. VIFi ¼ 1=ð12 R2i Þ where R 2 i is the variance explained from regressing the independent variable Xi

on all other independent variable Xs.


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Figure A1

Team Climate Innovativeness

1. My team encourages suggesting ideas for new opportunities 2. My team encourages finding new methods to perform a task

Affiliation 1. I feel I am really a part of my team 2. If I had a chance to do the same work again in a team, I would rather stay in the same

team 3. If I had a chance to do the same work again in a team, I would rather join another

team (revised) Trust

1. We trust one another a lot in my team 2. I know I can count on the other team members 3. I trust all of the other team members

Empowering Leadership My team leader…

Lead by Example 1. Sets high standards for performance by his/her own behavior 2. Works as hard as he/she can 3. Works as hard as anyone in my team 4. Sets a good example by the way he/she behaves

Participative Decision Making 1. Encourages team members to express ideas/suggestions 2. Listens to my team’s ideas and suggestions 3. Gives all team members a chance to voice their opinions

Coaching 1. Suggests ways to improve my team’s performance 2. Encourages team members to solve problems together 3. Encourages team members to exchange information with one another

Informing 1. Explains instructor decisions/comments 2. Explains course/assignment-related materials 3. Explains rules and expectations to my team 4. Explains his/her decisions and actions to my team

Showing Concern 1. Cares about team members’ personal problems 2. Shows concern for team members’ wellbeing 3. Treats team members as equals 4. Takes the time to discuss team members’ concerns patiently

Attitude My knowledge sharing with other colleagues is …

1. Very bad 1 2 3 4 5 Very good 2. Very worthless 1 2 3 4 5 Very valuable 3. Very harmful 1 2 3 4 5 Very beneficial

Knowledge-Sharing Behavior 1. I frequently participate in knowledge-sharing activities in this course 2. I usually spend a lot of time conducting knowledge-sharing activities in this course 3. When participating in this course, I usually actively share my knowledge with others


About the authors

Yajiong Xue is an Assistant Professor in the College of Business at East Carolina University. She received her PhD from Auburn University in 2004. Her research appears or is forthcoming in such journals as MIS Quarterly, Information Systems Research, Journal of the AIS, Communications of the ACM, Communications of the AIS, Decision Support Systems, IEEE Transactions on Information Technology in Biomedicine, Journal of Strategic Information Systems, International Journal of Production Economics, and International Journal of Medical Informatics. Her current research interests include the strategic management of IT, IT governance, and healthcare information systems. She was among the top ten globally in terms of MISQ and ISR publications between 2007 and 2009. Yajiong Xue is the corresponding author and can be contacted at: yajiong.xue@gmail.com

John Bradley is a Professor of Management Information Systems in the MIS Department at East Carolina University. His research interests are expert systems, case-based reasoning, team performance, and IS implementation and organizational impact. He has published in journals such as Expert Systems with Applications, Heuristics, Small Group Research, Information & Management, Journal of Computer Information Systems, and others.

Huigang Liang is an Assistant Professor in the College of Business at East Carolina University. His current research interests focus on IT issues at both individual and organizational levels such as IT avoidance, adoption, compliance, assimilation, decision process, IT strategy, and healthcare informatics. He was among the top ten worldwide in terms of MISQ and ISR publications between 2007 and 2009. His research has appeared or will appear in scholarly journals, including MIS Quarterly, Information Systems Research, Journal of the AIS, Communications of the ACM, Decision Support Systems, the Journal of Strategic Information Systems, IEEE Transactions on Information Technology in Biomedicine, Communications of the AIS, International Journal of Production Economics, International Journal of Medical Informatics, Journal of the American Pharmacists Association, among others. He received his PhD from Auburn University.


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